mirror of
https://gitee.com/mymagicpower/AIAS.git
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添加 IOCR 自定义模板识别。
This commit is contained in:
Calvin
parent
423e96e055
commit
da798ef98a
120
6_web_app/iocr/README.md
Normal file
120
6_web_app/iocr/README.md
Normal file
@ -0,0 +1,120 @@
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||||
### 目录：
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||||
https://www.aias.top/
|
||||
|
||||
### 模型下载：
|
||||
- 链接：https://pan.baidu.com/s/1-OEOcYHjSeqbfu7XD3ASgw?pwd=f43t
|
||||
|
||||
### OCR 自定义模板识别(支持表格识别)
|
||||
|
||||
文字识别（OCR）目前在多个行业中得到了广泛应用，比如金融行业的单据识别输入，餐饮行业中的发票识别，
|
||||
交通领域的车票识别，企业中各种表单识别，以及日常工作生活中常用的身份证，驾驶证，护照识别等等。
|
||||
OCR（文字识别）是目前常用的一种AI能力。
|
||||
一般OCR的识别结果是一种按行识别的结构化输出，能够给出一行文字的检测框坐标及文字内容。
|
||||
但是我们更想要的是带有字段定义的结构化输出，由于表单还活着卡证的多样性，全都预定义好是不现实的。
|
||||
所以，设计了自定义模板的功能，能够让人设置参照锚点（通过锚点匹配定位，图片透视变换对齐），以及内容识别区
|
||||
来得到key-value形式的结构化数据。
|
||||
|
||||
当前版本包含了下面功能：
|
||||
1. 模板自定义
|
||||
2. 基于模板识别（支持旋转、倾斜的图片）
|
||||
3. 自由文本识别（用于调试）
|
||||
4. 文本转正（用于调试）
|
||||
|
||||
|
||||
|
||||
### 1. 前端部署
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||||
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||||
#### 1.1 直接运行：
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||||
```bash
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npm run dev
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||||
```
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||||
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#### 1.2 构建dist安装包：
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```bash
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npm run build:prod
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```
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||||
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#### 1.3 nginx部署运行(mac环境部署管理前端为例)：
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```bash
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cd /usr/local/etc/nginx/
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vi /usr/local/etc/nginx/nginx.conf
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# 编辑nginx.conf
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server {
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listen 8080;
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server_name localhost;
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location / {
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root /Users/calvin/ocr_ui/dist/;
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index index.html index.htm;
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}
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......
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# 重新加载配置：
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sudo nginx -s reload
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# 部署应用后，重启：
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cd /usr/local/Cellar/nginx/1.19.6/bin
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# 快速停止
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sudo nginx -s stop
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# 启动
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sudo nginx
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```
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### 2. 后端jar部署
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#### 环境要求：
|
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- 系统JDK 1.8+，建议11
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||||
|
||||
### 3. 运行程序：
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运行编译后的jar：
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||||
```bash
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# 运行程序
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nohup java -Dfile.encoding=utf-8 -jar xxxxx.jar > log.txt 2>&1 &
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```
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### 4. 打开浏览器
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- 输入地址： http://localhost:8089
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|
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#### 1. 自定义模板 - 参照锚点设置
|
||||
|
||||
|
||||
#### 2. 自定义模板 - 内容识别区设置
|
||||
|
||||
|
||||
#### 3. 基于模板文字识别
|
||||
|
||||
|
||||
#### 4. 通用文本识别
|
||||
|
||||
|
||||
#### 5. 文本转正
|
||||
|
||||
|
||||
|
||||
|
||||
#### 使用建议：
|
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- 1. 请先用 ocr sdk 识别文字，查看自动检测的文本框位置，及识别文字的精度
|
||||
- 2. 标注模板不能成功匹配，主要有两点原因：
|
||||
- 1）标注的文本框位置，与自动检测的文本框位置不一致，所以请参考上面建议，先运行sdk查看自动检测的效果
|
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- 2）另一个原因是，文字识别精度不够（可能是图片文字过于模糊，也可能是算法本身精度不够）
|
||||
|
||||
#### 待修复的Bug：
|
||||
- 1. 模板标注文本框的时候，需要从左上角向右下角拉框（代码没有自动排序，所以如果从右下角往左上角拉框会报错）
|
||||
|
||||
#### 下一步的改进功能：
|
||||
- 1. 不使用锚点匹配，而是通过文本转正对齐，将表单对齐，然后根据内容区域IoU，判断匹配度。解决锚点匹配困难的问题。
|
||||
|
||||
|
||||
|
||||
#### 帮助文档：
|
||||
- https://aias.top/guides.html
|
||||
- 1.性能优化常见问题:
|
||||
- https://aias.top/AIAS/guides/performance.html
|
||||
- 2.引擎配置（包括CPU，GPU在线自动加载，及本地配置）:
|
||||
- https://aias.top/AIAS/guides/engine_config.html
|
||||
- 3.模型加载方式（在线自动加载，及本地配置）:
|
||||
- https://aias.top/AIAS/guides/load_model.html
|
||||
- 4.Windows环境常见问题:
|
||||
- https://aias.top/AIAS/guides/windows.html
|
||||
120
6_web_app/iocr/README_EN.md
Normal file
120
6_web_app/iocr/README_EN.md
Normal file
@ -0,0 +1,120 @@
|
||||
### 目录：
|
||||
https://www.aias.top/
|
||||
|
||||
### 模型下载：
|
||||
- 链接：https://pan.baidu.com/s/1-OEOcYHjSeqbfu7XD3ASgw?pwd=f43t
|
||||
|
||||
### OCR 自定义模板识别(支持表格识别)
|
||||
|
||||
文字识别（OCR）目前在多个行业中得到了广泛应用，比如金融行业的单据识别输入，餐饮行业中的发票识别，
|
||||
交通领域的车票识别，企业中各种表单识别，以及日常工作生活中常用的身份证，驾驶证，护照识别等等。
|
||||
OCR（文字识别）是目前常用的一种AI能力。
|
||||
一般OCR的识别结果是一种按行识别的结构化输出，能够给出一行文字的检测框坐标及文字内容。
|
||||
但是我们更想要的是带有字段定义的结构化输出，由于表单还活着卡证的多样性，全都预定义好是不现实的。
|
||||
所以，设计了自定义模板的功能，能够让人设置参照锚点（通过锚点匹配定位，图片透视变换对齐），以及内容识别区
|
||||
来得到key-value形式的结构化数据。
|
||||
|
||||
当前版本包含了下面功能：
|
||||
1. 模板自定义
|
||||
2. 基于模板识别（支持旋转、倾斜的图片）
|
||||
3. 自由文本识别（用于调试）
|
||||
4. 文本转正（用于调试）
|
||||
|
||||
|
||||
|
||||
### 1. 前端部署
|
||||
|
||||
#### 1.1 直接运行：
|
||||
```bash
|
||||
npm run dev
|
||||
```
|
||||
|
||||
#### 1.2 构建dist安装包：
|
||||
```bash
|
||||
npm run build:prod
|
||||
```
|
||||
|
||||
#### 1.3 nginx部署运行(mac环境部署管理前端为例)：
|
||||
```bash
|
||||
cd /usr/local/etc/nginx/
|
||||
vi /usr/local/etc/nginx/nginx.conf
|
||||
# 编辑nginx.conf
|
||||
|
||||
server {
|
||||
listen 8080;
|
||||
server_name localhost;
|
||||
|
||||
location / {
|
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root /Users/calvin/ocr_ui/dist/;
|
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index index.html index.htm;
|
||||
}
|
||||
......
|
||||
|
||||
# 重新加载配置：
|
||||
sudo nginx -s reload
|
||||
|
||||
# 部署应用后，重启：
|
||||
cd /usr/local/Cellar/nginx/1.19.6/bin
|
||||
|
||||
# 快速停止
|
||||
sudo nginx -s stop
|
||||
|
||||
# 启动
|
||||
sudo nginx
|
||||
```
|
||||
|
||||
### 2. 后端jar部署
|
||||
#### 环境要求：
|
||||
- 系统JDK 1.8+，建议11
|
||||
|
||||
### 3. 运行程序：
|
||||
运行编译后的jar：
|
||||
```bash
|
||||
# 运行程序
|
||||
nohup java -Dfile.encoding=utf-8 -jar xxxxx.jar > log.txt 2>&1 &
|
||||
```
|
||||
|
||||
### 4. 打开浏览器
|
||||
- 输入地址： http://localhost:8089
|
||||
|
||||
#### 1. 自定义模板 - 参照锚点设置
|
||||
|
||||
|
||||
#### 2. 自定义模板 - 内容识别区设置
|
||||
|
||||
|
||||
#### 3. 基于模板文字识别
|
||||
|
||||
|
||||
#### 4. 通用文本识别
|
||||
|
||||
|
||||
#### 5. 文本转正
|
||||
|
||||
|
||||
|
||||
|
||||
#### 使用建议：
|
||||
- 1. 请先用 ocr sdk 识别文字，查看自动检测的文本框位置，及识别文字的精度
|
||||
- 2. 标注模板不能成功匹配，主要有两点原因：
|
||||
- 1）标注的文本框位置，与自动检测的文本框位置不一致，所以请参考上面建议，先运行sdk查看自动检测的效果
|
||||
- 2）另一个原因是，文字识别精度不够（可能是图片文字过于模糊，也可能是算法本身精度不够）
|
||||
|
||||
#### 待修复的Bug：
|
||||
- 1. 模板标注文本框的时候，需要从左上角向右下角拉框（代码没有自动排序，所以如果从右下角往左上角拉框会报错）
|
||||
|
||||
#### 下一步的改进功能：
|
||||
- 1. 不使用锚点匹配，而是通过文本转正对齐，将表单对齐，然后根据内容区域IoU，判断匹配度。解决锚点匹配困难的问题。
|
||||
|
||||
|
||||
|
||||
#### 帮助文档：
|
||||
- https://aias.top/guides.html
|
||||
- 1.性能优化常见问题:
|
||||
- https://aias.top/AIAS/guides/performance.html
|
||||
- 2.引擎配置（包括CPU，GPU在线自动加载，及本地配置）:
|
||||
- https://aias.top/AIAS/guides/engine_config.html
|
||||
- 3.模型加载方式（在线自动加载，及本地配置）:
|
||||
- https://aias.top/AIAS/guides/load_model.html
|
||||
- 4.Windows环境常见问题:
|
||||
- https://aias.top/AIAS/guides/windows.html
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 133 KiB |
7
6_web_app/iocr/ocr_backend/file/templates.json
Normal file
7
6_web_app/iocr/ocr_backend/file/templates.json
Normal file
@ -0,0 +1,7 @@
|
||||
[
|
||||
{
|
||||
"uid": "60b0bd28f518435f92170d64c572d90d",
|
||||
"name": "ticket",
|
||||
"imageName": "ef96a8e505eb40a3ab7883ea4660261c.jpeg"
|
||||
}
|
||||
]
|
||||
@ -0,0 +1,153 @@
|
||||
{
|
||||
"uid": "60b0bd28f518435f92170d64c572d90d",
|
||||
"name": "ticket",
|
||||
"imageName": "ef96a8e505eb40a3ab7883ea4660261c.jpeg",
|
||||
"labelData": [
|
||||
{
|
||||
"index": 0,
|
||||
"active": 0,
|
||||
"type": "anchor",
|
||||
"value": "限乘当日当次车",
|
||||
"points": [
|
||||
{
|
||||
"x": 156,
|
||||
"y": 283
|
||||
},
|
||||
{
|
||||
"x": 346,
|
||||
"y": 283
|
||||
},
|
||||
{
|
||||
"x": 346,
|
||||
"y": 323
|
||||
},
|
||||
{
|
||||
"x": 156,
|
||||
"y": 323
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 1,
|
||||
"active": 0,
|
||||
"type": "anchor",
|
||||
"value": "中国铁路祝您旅途愉快",
|
||||
"points": [
|
||||
{
|
||||
"x": 263,
|
||||
"y": 418
|
||||
},
|
||||
{
|
||||
"x": 503,
|
||||
"y": 418
|
||||
},
|
||||
{
|
||||
"x": 503,
|
||||
"y": 447
|
||||
},
|
||||
{
|
||||
"x": 263,
|
||||
"y": 447
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 2,
|
||||
"active": 0,
|
||||
"type": "anchor",
|
||||
"value": "网折",
|
||||
"points": [
|
||||
{
|
||||
"x": 385,
|
||||
"y": 250
|
||||
},
|
||||
{
|
||||
"x": 441,
|
||||
"y": 250
|
||||
},
|
||||
{
|
||||
"x": 441,
|
||||
"y": 284
|
||||
},
|
||||
{
|
||||
"x": 385,
|
||||
"y": 284
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 3,
|
||||
"active": 0,
|
||||
"type": "rectangle",
|
||||
"value": "南昌站",
|
||||
"field": "start",
|
||||
"points": [
|
||||
{
|
||||
"x": 171,
|
||||
"y": 143
|
||||
},
|
||||
{
|
||||
"x": 360,
|
||||
"y": 143
|
||||
},
|
||||
{
|
||||
"x": 360,
|
||||
"y": 190
|
||||
},
|
||||
{
|
||||
"x": 171,
|
||||
"y": 190
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 4,
|
||||
"active": 0,
|
||||
"type": "rectangle",
|
||||
"value": "九江站",
|
||||
"field": "end",
|
||||
"points": [
|
||||
{
|
||||
"x": 533,
|
||||
"y": 141
|
||||
},
|
||||
{
|
||||
"x": 724,
|
||||
"y": 141
|
||||
},
|
||||
{
|
||||
"x": 724,
|
||||
"y": 193
|
||||
},
|
||||
{
|
||||
"x": 533,
|
||||
"y": 193
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 5,
|
||||
"active": 1,
|
||||
"type": "anchor",
|
||||
"value": "二等座",
|
||||
"points": [
|
||||
{
|
||||
"x": 564,
|
||||
"y": 252
|
||||
},
|
||||
{
|
||||
"x": 678,
|
||||
"y": 252
|
||||
},
|
||||
{
|
||||
"x": 678,
|
||||
"y": 281
|
||||
},
|
||||
{
|
||||
"x": 564,
|
||||
"y": 281
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
@ -0,0 +1,153 @@
|
||||
{
|
||||
"uid": "60b0bd28f518435f92170d64c572d90d",
|
||||
"name": "ticket",
|
||||
"imageName": "ef96a8e505eb40a3ab7883ea4660261c.jpeg",
|
||||
"labelData": [
|
||||
{
|
||||
"index": 0,
|
||||
"active": 0,
|
||||
"type": "anchor",
|
||||
"value": "限乘当日当次车",
|
||||
"points": [
|
||||
{
|
||||
"x": 159,
|
||||
"y": 288
|
||||
},
|
||||
{
|
||||
"x": 346,
|
||||
"y": 288
|
||||
},
|
||||
{
|
||||
"x": 346,
|
||||
"y": 314
|
||||
},
|
||||
{
|
||||
"x": 159,
|
||||
"y": 314
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 1,
|
||||
"active": 0,
|
||||
"type": "anchor",
|
||||
"value": "中国铁路祝您旅途愉快",
|
||||
"points": [
|
||||
{
|
||||
"x": 267,
|
||||
"y": 420
|
||||
},
|
||||
{
|
||||
"x": 497,
|
||||
"y": 420
|
||||
},
|
||||
{
|
||||
"x": 497,
|
||||
"y": 444
|
||||
},
|
||||
{
|
||||
"x": 267,
|
||||
"y": 444
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 2,
|
||||
"active": 0,
|
||||
"type": "anchor",
|
||||
"value": "网折",
|
||||
"points": [
|
||||
{
|
||||
"x": 379,
|
||||
"y": 245
|
||||
},
|
||||
{
|
||||
"x": 447,
|
||||
"y": 245
|
||||
},
|
||||
{
|
||||
"x": 447,
|
||||
"y": 287
|
||||
},
|
||||
{
|
||||
"x": 379,
|
||||
"y": 287
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 3,
|
||||
"active": 0,
|
||||
"type": "rectangle",
|
||||
"value": "南昌站",
|
||||
"field": "start",
|
||||
"points": [
|
||||
{
|
||||
"x": 177,
|
||||
"y": 142
|
||||
},
|
||||
{
|
||||
"x": 359,
|
||||
"y": 144
|
||||
},
|
||||
{
|
||||
"x": 358,
|
||||
"y": 195
|
||||
},
|
||||
{
|
||||
"x": 176,
|
||||
"y": 193
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 4,
|
||||
"active": 0,
|
||||
"type": "rectangle",
|
||||
"value": "九江站",
|
||||
"field": "end",
|
||||
"points": [
|
||||
{
|
||||
"x": 537,
|
||||
"y": 141
|
||||
},
|
||||
{
|
||||
"x": 723,
|
||||
"y": 141
|
||||
},
|
||||
{
|
||||
"x": 723,
|
||||
"y": 194
|
||||
},
|
||||
{
|
||||
"x": 537,
|
||||
"y": 194
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"index": 5,
|
||||
"active": 1,
|
||||
"type": "anchor",
|
||||
"value": "二等座",
|
||||
"points": [
|
||||
{
|
||||
"x": 572,
|
||||
"y": 245
|
||||
},
|
||||
{
|
||||
"x": 663,
|
||||
"y": 247
|
||||
},
|
||||
{
|
||||
"x": 662,
|
||||
"y": 288
|
||||
},
|
||||
{
|
||||
"x": 571,
|
||||
"y": 286
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
8
6_web_app/iocr/ocr_backend/ocr_backend.iml
Normal file
8
6_web_app/iocr/ocr_backend/ocr_backend.iml
Normal file
@ -0,0 +1,8 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<module version="4">
|
||||
<component name="FacetManager">
|
||||
<facet type="Spring" name="Spring">
|
||||
<configuration />
|
||||
</facet>
|
||||
</component>
|
||||
</module>
|
||||
213
6_web_app/iocr/ocr_backend/pom.xml
Normal file
213
6_web_app/iocr/ocr_backend/pom.xml
Normal file
@ -0,0 +1,213 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
<parent>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-parent</artifactId>
|
||||
<version>2.1.9.RELEASE</version>
|
||||
</parent>
|
||||
<groupId>aias</groupId>
|
||||
<artifactId>ocr_backend</artifactId>
|
||||
<version>0.23.0</version>
|
||||
<name>ocr_backend</name>
|
||||
<description>AIAS IOCR Project</description>
|
||||
|
||||
<properties>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<maven.compiler.encoding>UTF-8</maven.compiler.encoding>
|
||||
<maven.compiler.source>1.8</maven.compiler.source>
|
||||
<maven.compiler.target>1.8</maven.compiler.target>
|
||||
<jna.version>5.13.0</jna.version>
|
||||
<fastjson.version>2.0.40</fastjson.version>
|
||||
<swagger.version>2.9.2</swagger.version>
|
||||
<djl.version>0.23.0</djl.version>
|
||||
<javacv.version>1.5.8</javacv.version>
|
||||
<javacv.ffmpeg.version>5.1.2-1.5.8</javacv.ffmpeg.version>
|
||||
<javacpp.platform.macosx-x86_64>macosx-x86_64</javacpp.platform.macosx-x86_64>
|
||||
<javacpp.platform.linux-x86>linux-x86</javacpp.platform.linux-x86>
|
||||
<javacpp.platform.linux-x86_64>linux-x86_64</javacpp.platform.linux-x86_64>
|
||||
<javacpp.platform.windows-x86>windows-x86</javacpp.platform.windows-x86>
|
||||
<javacpp.platform.windows-x86_64>windows-x86_64</javacpp.platform.windows-x86_64>
|
||||
</properties>
|
||||
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-web</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-aop</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-test</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.data</groupId>
|
||||
<artifactId>spring-data-commons</artifactId>
|
||||
<version>2.1.2.RELEASE</version>
|
||||
</dependency>
|
||||
<!-- apache commons -->
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.8.1</version>
|
||||
</dependency>
|
||||
<!-- Gson -->
|
||||
<dependency>
|
||||
<groupId>com.google.code.gson</groupId>
|
||||
<artifactId>gson</artifactId>
|
||||
<version>2.8.5</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.logging.log4j</groupId>
|
||||
<artifactId>log4j-slf4j-impl</artifactId>
|
||||
<version>2.15.0</version>
|
||||
</dependency>
|
||||
<!-- DJL -->
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>api</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>basicdataset</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>model-zoo</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>net.java.dev.jna</groupId>
|
||||
<artifactId>jna</artifactId>
|
||||
<version>${jna.version}</version> <!-- overrides default spring boot version to comply with DJL -->
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>ai.djl.pytorch</groupId>
|
||||
<artifactId>pytorch-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- ONNX -->
|
||||
<dependency>
|
||||
<groupId>ai.djl.onnxruntime</groupId>
|
||||
<artifactId>onnxruntime-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- java cv -->
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacv-platform</artifactId>
|
||||
<version>1.5.7</version>
|
||||
</dependency>
|
||||
|
||||
<!--lombok-->
|
||||
<dependency>
|
||||
<groupId>org.projectlombok</groupId>
|
||||
<artifactId>lombok</artifactId>
|
||||
<version>1.18.24</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>com.google.http-client</groupId>
|
||||
<artifactId>google-http-client</artifactId>
|
||||
<version>1.19.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-cli</groupId>
|
||||
<artifactId>commons-cli</artifactId>
|
||||
<version>1.4</version>
|
||||
</dependency>
|
||||
|
||||
<!-- fastjson -->
|
||||
<dependency>
|
||||
<groupId>com.alibaba</groupId>
|
||||
<artifactId>fastjson</artifactId>
|
||||
<version>${fastjson.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>com.github.xiaoymin</groupId>
|
||||
<artifactId>knife4j-spring-boot-starter</artifactId>
|
||||
<version>2.0.2</version>
|
||||
</dependency>
|
||||
|
||||
<!-- Swagger UI 相关 -->
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger2</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
<exclusions>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
</exclusion>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
</exclusion>
|
||||
</exclusions>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger-ui</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.12.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-collections</groupId>
|
||||
<artifactId>commons-collections</artifactId>
|
||||
<version>3.2.2</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.poi</groupId>
|
||||
<artifactId>poi</artifactId>
|
||||
<version>4.0.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>dom4j</groupId>
|
||||
<artifactId>dom4j</artifactId>
|
||||
<version>1.6.1</version>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-maven-plugin</artifactId>
|
||||
<configuration>
|
||||
<mainClass>top.aias.iocr.MainApplication</mainClass>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
|
||||
</project>
|
||||
246
6_web_app/iocr/ocr_backend/pom_linux.xml
Normal file
246
6_web_app/iocr/ocr_backend/pom_linux.xml
Normal file
@ -0,0 +1,246 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
<parent>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-parent</artifactId>
|
||||
<version>2.1.9.RELEASE</version>
|
||||
</parent>
|
||||
<groupId>aias</groupId>
|
||||
<artifactId>ocr_backend</artifactId>
|
||||
<version>0.23.0</version>
|
||||
<name>ocr_backend</name>
|
||||
<description>AIAS IOCR Project</description>
|
||||
|
||||
<properties>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<maven.compiler.encoding>UTF-8</maven.compiler.encoding>
|
||||
<maven.compiler.source>1.8</maven.compiler.source>
|
||||
<maven.compiler.target>1.8</maven.compiler.target>
|
||||
<jna.version>5.13.0</jna.version>
|
||||
<fastjson.version>2.0.40</fastjson.version>
|
||||
<swagger.version>2.9.2</swagger.version>
|
||||
<djl.version>0.23.0</djl.version>
|
||||
<javacv.version>1.5.8</javacv.version>
|
||||
<javacv.ffmpeg.version>5.1.2-1.5.8</javacv.ffmpeg.version>
|
||||
<javacpp.platform.macosx-x86_64>macosx-x86_64</javacpp.platform.macosx-x86_64>
|
||||
<javacpp.platform.linux-x86>linux-x86</javacpp.platform.linux-x86>
|
||||
<javacpp.platform.linux-x86_64>linux-x86_64</javacpp.platform.linux-x86_64>
|
||||
<javacpp.platform.windows-x86>windows-x86</javacpp.platform.windows-x86>
|
||||
<javacpp.platform.windows-x86_64>windows-x86_64</javacpp.platform.windows-x86_64>
|
||||
</properties>
|
||||
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-web</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-aop</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-test</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.data</groupId>
|
||||
<artifactId>spring-data-commons</artifactId>
|
||||
<version>2.1.2.RELEASE</version>
|
||||
</dependency>
|
||||
<!-- apache commons -->
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.8.1</version>
|
||||
</dependency>
|
||||
<!-- Gson -->
|
||||
<dependency>
|
||||
<groupId>com.google.code.gson</groupId>
|
||||
<artifactId>gson</artifactId>
|
||||
<version>2.8.5</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.logging.log4j</groupId>
|
||||
<artifactId>log4j-slf4j-impl</artifactId>
|
||||
<version>2.15.0</version>
|
||||
</dependency>
|
||||
<!-- DJL -->
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>api</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>basicdataset</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>model-zoo</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>net.java.dev.jna</groupId>
|
||||
<artifactId>jna</artifactId>
|
||||
<version>${jna.version}</version> <!-- overrides default spring boot version to comply with DJL -->
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>ai.djl.pytorch</groupId>
|
||||
<artifactId>pytorch-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- ONNX -->
|
||||
<dependency>
|
||||
<groupId>ai.djl.onnxruntime</groupId>
|
||||
<artifactId>onnxruntime-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- java cv -->
|
||||
<!-- <dependency>-->
|
||||
<!-- <groupId>org.bytedeco</groupId>-->
|
||||
<!-- <artifactId>javacv-platform</artifactId>-->
|
||||
<!-- <version>1.5.7</version>-->
|
||||
<!-- </dependency>-->
|
||||
<!--javacv截取视频帧-->
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacv</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!--Linux平台-->
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacpp</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
<classifier>${javacpp.platform.linux-x86}</classifier>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>ffmpeg</artifactId>
|
||||
<version>${javacv.ffmpeg.version}</version>
|
||||
<classifier>${javacpp.platform.linux-x86}</classifier>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacpp</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
<classifier>${javacpp.platform.linux-x86_64}</classifier>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>ffmpeg</artifactId>
|
||||
<version>${javacv.ffmpeg.version}</version>
|
||||
<classifier>${javacpp.platform.linux-x86_64}</classifier>
|
||||
</dependency>
|
||||
|
||||
<!--lombok-->
|
||||
<dependency>
|
||||
<groupId>org.projectlombok</groupId>
|
||||
<artifactId>lombok</artifactId>
|
||||
<version>1.18.24</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>com.google.http-client</groupId>
|
||||
<artifactId>google-http-client</artifactId>
|
||||
<version>1.19.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-cli</groupId>
|
||||
<artifactId>commons-cli</artifactId>
|
||||
<version>1.4</version>
|
||||
</dependency>
|
||||
|
||||
<!-- fastjson -->
|
||||
<dependency>
|
||||
<groupId>com.alibaba</groupId>
|
||||
<artifactId>fastjson</artifactId>
|
||||
<version>${fastjson.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>com.github.xiaoymin</groupId>
|
||||
<artifactId>knife4j-spring-boot-starter</artifactId>
|
||||
<version>2.0.2</version>
|
||||
</dependency>
|
||||
|
||||
<!-- Swagger UI 相关 -->
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger2</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
<exclusions>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
</exclusion>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
</exclusion>
|
||||
</exclusions>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger-ui</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.12.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-collections</groupId>
|
||||
<artifactId>commons-collections</artifactId>
|
||||
<version>3.2.2</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.poi</groupId>
|
||||
<artifactId>poi</artifactId>
|
||||
<version>4.0.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>dom4j</groupId>
|
||||
<artifactId>dom4j</artifactId>
|
||||
<version>1.6.1</version>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-maven-plugin</artifactId>
|
||||
<configuration>
|
||||
<mainClass>top.aias.iocr.MainApplication</mainClass>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
|
||||
</project>
|
||||
233
6_web_app/iocr/ocr_backend/pom_mac.xml
Normal file
233
6_web_app/iocr/ocr_backend/pom_mac.xml
Normal file
@ -0,0 +1,233 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
<parent>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-parent</artifactId>
|
||||
<version>2.1.9.RELEASE</version>
|
||||
</parent>
|
||||
<groupId>aias</groupId>
|
||||
<artifactId>ocr_backend</artifactId>
|
||||
<version>0.23.0</version>
|
||||
<name>ocr_backend</name>
|
||||
<description>AIAS IOCR Project</description>
|
||||
|
||||
<properties>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<maven.compiler.encoding>UTF-8</maven.compiler.encoding>
|
||||
<maven.compiler.source>1.8</maven.compiler.source>
|
||||
<maven.compiler.target>1.8</maven.compiler.target>
|
||||
<jna.version>5.13.0</jna.version>
|
||||
<fastjson.version>2.0.40</fastjson.version>
|
||||
<swagger.version>2.9.2</swagger.version>
|
||||
<djl.version>0.23.0</djl.version>
|
||||
<javacv.version>1.5.8</javacv.version>
|
||||
<javacv.ffmpeg.version>5.1.2-1.5.8</javacv.ffmpeg.version>
|
||||
<javacpp.platform.macosx-x86_64>macosx-x86_64</javacpp.platform.macosx-x86_64>
|
||||
<javacpp.platform.linux-x86>linux-x86</javacpp.platform.linux-x86>
|
||||
<javacpp.platform.linux-x86_64>linux-x86_64</javacpp.platform.linux-x86_64>
|
||||
<javacpp.platform.windows-x86>windows-x86</javacpp.platform.windows-x86>
|
||||
<javacpp.platform.windows-x86_64>windows-x86_64</javacpp.platform.windows-x86_64>
|
||||
</properties>
|
||||
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-web</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-aop</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-test</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.data</groupId>
|
||||
<artifactId>spring-data-commons</artifactId>
|
||||
<version>2.1.2.RELEASE</version>
|
||||
</dependency>
|
||||
<!-- apache commons -->
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.8.1</version>
|
||||
</dependency>
|
||||
<!-- Gson -->
|
||||
<dependency>
|
||||
<groupId>com.google.code.gson</groupId>
|
||||
<artifactId>gson</artifactId>
|
||||
<version>2.8.5</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.logging.log4j</groupId>
|
||||
<artifactId>log4j-slf4j-impl</artifactId>
|
||||
<version>2.15.0</version>
|
||||
</dependency>
|
||||
<!-- DJL -->
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>api</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>basicdataset</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>model-zoo</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>net.java.dev.jna</groupId>
|
||||
<artifactId>jna</artifactId>
|
||||
<version>${jna.version}</version> <!-- overrides default spring boot version to comply with DJL -->
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>ai.djl.pytorch</groupId>
|
||||
<artifactId>pytorch-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- ONNX -->
|
||||
<dependency>
|
||||
<groupId>ai.djl.onnxruntime</groupId>
|
||||
<artifactId>onnxruntime-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- java cv -->
|
||||
<!-- <dependency>-->
|
||||
<!-- <groupId>org.bytedeco</groupId>-->
|
||||
<!-- <artifactId>javacv-platform</artifactId>-->
|
||||
<!-- <version>1.5.7</version>-->
|
||||
<!-- </dependency>-->
|
||||
<!--javacv截取视频帧-->
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacv</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!--MacOS平台-->
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacpp</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
<classifier>${javacpp.platform.macosx-x86_64}</classifier>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>ffmpeg</artifactId>
|
||||
<version>${javacv.ffmpeg.version}</version>
|
||||
<classifier>${javacpp.platform.macosx-x86_64}</classifier>
|
||||
</dependency>
|
||||
|
||||
<!--lombok-->
|
||||
<dependency>
|
||||
<groupId>org.projectlombok</groupId>
|
||||
<artifactId>lombok</artifactId>
|
||||
<version>1.18.24</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>com.google.http-client</groupId>
|
||||
<artifactId>google-http-client</artifactId>
|
||||
<version>1.19.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-cli</groupId>
|
||||
<artifactId>commons-cli</artifactId>
|
||||
<version>1.4</version>
|
||||
</dependency>
|
||||
|
||||
<!-- fastjson -->
|
||||
<dependency>
|
||||
<groupId>com.alibaba</groupId>
|
||||
<artifactId>fastjson</artifactId>
|
||||
<version>${fastjson.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>com.github.xiaoymin</groupId>
|
||||
<artifactId>knife4j-spring-boot-starter</artifactId>
|
||||
<version>2.0.2</version>
|
||||
</dependency>
|
||||
|
||||
<!-- Swagger UI 相关 -->
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger2</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
<exclusions>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
</exclusion>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
</exclusion>
|
||||
</exclusions>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger-ui</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.12.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-collections</groupId>
|
||||
<artifactId>commons-collections</artifactId>
|
||||
<version>3.2.2</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.poi</groupId>
|
||||
<artifactId>poi</artifactId>
|
||||
<version>4.0.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>dom4j</groupId>
|
||||
<artifactId>dom4j</artifactId>
|
||||
<version>1.6.1</version>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-maven-plugin</artifactId>
|
||||
<configuration>
|
||||
<mainClass>top.aias.iocr.MainApplication</mainClass>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
|
||||
</project>
|
||||
246
6_web_app/iocr/ocr_backend/pom_win.xml
Normal file
246
6_web_app/iocr/ocr_backend/pom_win.xml
Normal file
@ -0,0 +1,246 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
<parent>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-parent</artifactId>
|
||||
<version>2.1.9.RELEASE</version>
|
||||
</parent>
|
||||
<groupId>aias</groupId>
|
||||
<artifactId>ocr_backend</artifactId>
|
||||
<version>0.23.0</version>
|
||||
<name>ocr_backend</name>
|
||||
<description>AIAS IOCR Project</description>
|
||||
|
||||
<properties>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<maven.compiler.encoding>UTF-8</maven.compiler.encoding>
|
||||
<maven.compiler.source>1.8</maven.compiler.source>
|
||||
<maven.compiler.target>1.8</maven.compiler.target>
|
||||
<jna.version>5.13.0</jna.version>
|
||||
<fastjson.version>2.0.40</fastjson.version>
|
||||
<swagger.version>2.9.2</swagger.version>
|
||||
<djl.version>0.23.0</djl.version>
|
||||
<javacv.version>1.5.8</javacv.version>
|
||||
<javacv.ffmpeg.version>5.1.2-1.5.8</javacv.ffmpeg.version>
|
||||
<javacpp.platform.macosx-x86_64>macosx-x86_64</javacpp.platform.macosx-x86_64>
|
||||
<javacpp.platform.linux-x86>linux-x86</javacpp.platform.linux-x86>
|
||||
<javacpp.platform.linux-x86_64>linux-x86_64</javacpp.platform.linux-x86_64>
|
||||
<javacpp.platform.windows-x86>windows-x86</javacpp.platform.windows-x86>
|
||||
<javacpp.platform.windows-x86_64>windows-x86_64</javacpp.platform.windows-x86_64>
|
||||
</properties>
|
||||
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-web</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-aop</artifactId>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-starter-test</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.springframework.data</groupId>
|
||||
<artifactId>spring-data-commons</artifactId>
|
||||
<version>2.1.2.RELEASE</version>
|
||||
</dependency>
|
||||
<!-- apache commons -->
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.8.1</version>
|
||||
</dependency>
|
||||
<!-- Gson -->
|
||||
<dependency>
|
||||
<groupId>com.google.code.gson</groupId>
|
||||
<artifactId>gson</artifactId>
|
||||
<version>2.8.5</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.logging.log4j</groupId>
|
||||
<artifactId>log4j-slf4j-impl</artifactId>
|
||||
<version>2.15.0</version>
|
||||
</dependency>
|
||||
<!-- DJL -->
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>api</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>basicdataset</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>ai.djl</groupId>
|
||||
<artifactId>model-zoo</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>net.java.dev.jna</groupId>
|
||||
<artifactId>jna</artifactId>
|
||||
<version>${jna.version}</version> <!-- overrides default spring boot version to comply with DJL -->
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>ai.djl.pytorch</groupId>
|
||||
<artifactId>pytorch-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- ONNX -->
|
||||
<dependency>
|
||||
<groupId>ai.djl.onnxruntime</groupId>
|
||||
<artifactId>onnxruntime-engine</artifactId>
|
||||
<version>${djl.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!-- java cv -->
|
||||
<!-- <dependency>-->
|
||||
<!-- <groupId>org.bytedeco</groupId>-->
|
||||
<!-- <artifactId>javacv-platform</artifactId>-->
|
||||
<!-- <version>1.5.7</version>-->
|
||||
<!-- </dependency>-->
|
||||
<!--javacv截取视频帧-->
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacv</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
</dependency>
|
||||
|
||||
<!--Windows平台-->
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacpp</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
<classifier>${javacpp.platform.windows-x86}</classifier>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>ffmpeg</artifactId>
|
||||
<version>${javacv.ffmpeg.version}</version>
|
||||
<classifier>${javacpp.platform.windows-x86}</classifier>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>javacpp</artifactId>
|
||||
<version>${javacv.version}</version>
|
||||
<classifier>${javacpp.platform.windows-x86_64}</classifier>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.bytedeco</groupId>
|
||||
<artifactId>ffmpeg</artifactId>
|
||||
<version>${javacv.ffmpeg.version}</version>
|
||||
<classifier>${javacpp.platform.windows-x86_64}</classifier>
|
||||
</dependency>
|
||||
|
||||
<!--lombok-->
|
||||
<dependency>
|
||||
<groupId>org.projectlombok</groupId>
|
||||
<artifactId>lombok</artifactId>
|
||||
<version>1.18.24</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>com.google.http-client</groupId>
|
||||
<artifactId>google-http-client</artifactId>
|
||||
<version>1.19.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-cli</groupId>
|
||||
<artifactId>commons-cli</artifactId>
|
||||
<version>1.4</version>
|
||||
</dependency>
|
||||
|
||||
<!-- fastjson -->
|
||||
<dependency>
|
||||
<groupId>com.alibaba</groupId>
|
||||
<artifactId>fastjson</artifactId>
|
||||
<version>${fastjson.version}</version>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>com.github.xiaoymin</groupId>
|
||||
<artifactId>knife4j-spring-boot-starter</artifactId>
|
||||
<version>2.0.2</version>
|
||||
</dependency>
|
||||
|
||||
<!-- Swagger UI 相关 -->
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger2</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
<exclusions>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
</exclusion>
|
||||
<exclusion>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
</exclusion>
|
||||
</exclusions>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.springfox</groupId>
|
||||
<artifactId>springfox-swagger-ui</artifactId>
|
||||
<version>${swagger.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-annotations</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>io.swagger</groupId>
|
||||
<artifactId>swagger-models</artifactId>
|
||||
<version>1.5.21</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.12.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>commons-collections</groupId>
|
||||
<artifactId>commons-collections</artifactId>
|
||||
<version>3.2.2</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.poi</groupId>
|
||||
<artifactId>poi</artifactId>
|
||||
<version>4.0.0</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>dom4j</groupId>
|
||||
<artifactId>dom4j</artifactId>
|
||||
<version>1.6.1</version>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.springframework.boot</groupId>
|
||||
<artifactId>spring-boot-maven-plugin</artifactId>
|
||||
<configuration>
|
||||
<mainClass>top.aias.iocr.MainApplication</mainClass>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
|
||||
</project>
|
||||
@ -0,0 +1,3 @@
|
||||
Manifest-Version: 1.0
|
||||
Main-Class: top.aias.iocr.MainApplication
|
||||
|
||||
@ -0,0 +1,19 @@
|
||||
package top.aias.iocr;
|
||||
|
||||
import org.springframework.boot.SpringApplication;
|
||||
import org.springframework.boot.autoconfigure.SpringBootApplication;
|
||||
|
||||
/**
|
||||
* 入口主程序
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@SpringBootApplication
|
||||
public class MainApplication {
|
||||
|
||||
public static void main(String[] args) {
|
||||
SpringApplication.run(MainApplication.class, args);
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,43 @@
|
||||
package top.aias.iocr.bean;
|
||||
/**
|
||||
* excel 单元
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class CrossRangeCellMeta {
|
||||
public CrossRangeCellMeta(int firstRowIndex, int firstColIndex, int rowSpan, int colSpan) {
|
||||
super();
|
||||
this.firstRowIndex = firstRowIndex;
|
||||
this.firstColIndex = firstColIndex;
|
||||
this.rowSpan = rowSpan;
|
||||
this.colSpan = colSpan;
|
||||
}
|
||||
|
||||
private int firstRowIndex;
|
||||
private int firstColIndex;
|
||||
private int rowSpan;// 跨越行数
|
||||
private int colSpan;// 跨越列数
|
||||
|
||||
public int getFirstRow() {
|
||||
return firstRowIndex;
|
||||
}
|
||||
|
||||
public int getLastRow() {
|
||||
return firstRowIndex + rowSpan - 1;
|
||||
}
|
||||
|
||||
public int getFirstCol() {
|
||||
return firstColIndex;
|
||||
}
|
||||
|
||||
public int getLastCol() {
|
||||
return firstColIndex + colSpan - 1;
|
||||
}
|
||||
|
||||
public int getColSpan(){
|
||||
return colSpan;
|
||||
}
|
||||
}
|
||||
|
||||
@ -0,0 +1,15 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import lombok.Data;
|
||||
import java.util.List;
|
||||
/**
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class DataBean {
|
||||
private String value;
|
||||
private List<Point> points;
|
||||
}
|
||||
@ -0,0 +1,20 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import lombok.Data;
|
||||
|
||||
import java.util.List;
|
||||
/**
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class LabelBean {
|
||||
private int index;
|
||||
private int active;
|
||||
private String type;
|
||||
private String value;
|
||||
private String field;
|
||||
private List<Point> points;
|
||||
private ai.djl.modality.cv.output.Point centerPoint;
|
||||
}
|
||||
@ -0,0 +1,13 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import lombok.Data;
|
||||
/**
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class LabelDTO {
|
||||
private String uid;
|
||||
private LabelBean labelData;
|
||||
}
|
||||
@ -0,0 +1,21 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import lombok.Data;
|
||||
/**
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class Point {
|
||||
private int x;
|
||||
private int y;
|
||||
|
||||
public Point() {
|
||||
}
|
||||
|
||||
public Point(int x, int y) {
|
||||
this.x = x;
|
||||
this.y = y;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,16 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import lombok.Data;
|
||||
/**
|
||||
* 透视变换对象
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class ProjBean {
|
||||
private Image image;
|
||||
private org.opencv.core.Mat warpMat;
|
||||
}
|
||||
@ -0,0 +1,43 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import lombok.Data;
|
||||
|
||||
import java.io.Serializable;
|
||||
import java.util.HashMap;
|
||||
import java.util.Map;
|
||||
/**
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class ResultBean<T> implements Serializable {
|
||||
private static final long serialVersionUID = 1L;
|
||||
private int code;
|
||||
private String value;
|
||||
private Map<String, Object> data = new HashMap<String, Object>();
|
||||
|
||||
public static ResultBean success() {
|
||||
ResultBean rb = new ResultBean();
|
||||
rb.setCode(0);
|
||||
rb.setValue("Success");
|
||||
return rb;
|
||||
}
|
||||
|
||||
public static ResultBean failure() {
|
||||
ResultBean msg = new ResultBean();
|
||||
msg.setCode(-1);
|
||||
msg.setValue("Failure");
|
||||
return msg;
|
||||
}
|
||||
|
||||
public ResultBean() {
|
||||
|
||||
}
|
||||
|
||||
public ResultBean add(String key, Object value) {
|
||||
this.getData().put(key, value);
|
||||
return this;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,50 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import ai.djl.ndarray.NDArray;
|
||||
/**
|
||||
* 旋转检测框
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class RotatedBox implements Comparable<RotatedBox> {
|
||||
private NDArray box;
|
||||
private String text;
|
||||
|
||||
public RotatedBox(NDArray box, String text) {
|
||||
this.box = box;
|
||||
this.text = text;
|
||||
}
|
||||
|
||||
/**
|
||||
* 将左上角 Y 坐标升序排序
|
||||
*
|
||||
* @param o
|
||||
* @return
|
||||
*/
|
||||
@Override
|
||||
public int compareTo(RotatedBox o) {
|
||||
NDArray lowBox = this.getBox();
|
||||
NDArray highBox = o.getBox();
|
||||
float lowY = lowBox.toFloatArray()[1];
|
||||
float highY = highBox.toFloatArray()[1];
|
||||
return (lowY < highY) ? -1 : 1;
|
||||
}
|
||||
|
||||
public NDArray getBox() {
|
||||
return box;
|
||||
}
|
||||
|
||||
public void setBox(NDArray box) {
|
||||
this.box = box;
|
||||
}
|
||||
|
||||
public String getText() {
|
||||
return text;
|
||||
}
|
||||
|
||||
public void setText(String text) {
|
||||
this.text = text;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,23 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import ai.djl.modality.cv.output.BoundingBox;
|
||||
import lombok.Data;
|
||||
|
||||
import java.util.List;
|
||||
/**
|
||||
* 表格检测结果
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class TableResult {
|
||||
private List<String> structure_str_list;
|
||||
private List<BoundingBox> boxes;
|
||||
|
||||
public TableResult(List<String> structure_str_list, List<BoundingBox> boxes) {
|
||||
this.structure_str_list = structure_str_list;
|
||||
this.boxes = boxes;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,19 @@
|
||||
package top.aias.iocr.bean;
|
||||
|
||||
import lombok.Data;
|
||||
|
||||
import java.util.List;
|
||||
/**
|
||||
* 模板对象
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
public class TemplateBean {
|
||||
private String uid;
|
||||
private String name;
|
||||
private String imageName;
|
||||
List<LabelBean> labelData;
|
||||
}
|
||||
@ -0,0 +1,78 @@
|
||||
package top.aias.iocr.configuration;
|
||||
|
||||
import com.alibaba.fastjson.serializer.SerializerFeature;
|
||||
import com.alibaba.fastjson.support.config.FastJsonConfig;
|
||||
import com.alibaba.fastjson.support.spring.FastJsonHttpMessageConverter;
|
||||
import org.springframework.context.annotation.Bean;
|
||||
import org.springframework.context.annotation.Configuration;
|
||||
import org.springframework.http.MediaType;
|
||||
import org.springframework.http.converter.HttpMessageConverter;
|
||||
import org.springframework.web.cors.CorsConfiguration;
|
||||
import org.springframework.web.cors.UrlBasedCorsConfigurationSource;
|
||||
import org.springframework.web.filter.CorsFilter;
|
||||
import org.springframework.web.servlet.config.annotation.EnableWebMvc;
|
||||
import org.springframework.web.servlet.config.annotation.ResourceHandlerRegistry;
|
||||
import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;
|
||||
|
||||
import java.nio.charset.StandardCharsets;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 配置类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Configuration
|
||||
@EnableWebMvc
|
||||
public class ConfigAdapter implements WebMvcConfigurer {
|
||||
|
||||
// file configuration
|
||||
private final FileProperties properties;
|
||||
|
||||
public ConfigAdapter(FileProperties properties) {
|
||||
this.properties = properties;
|
||||
}
|
||||
|
||||
@Bean
|
||||
public CorsFilter corsFilter() {
|
||||
UrlBasedCorsConfigurationSource source = new UrlBasedCorsConfigurationSource();
|
||||
CorsConfiguration config = new CorsConfiguration();
|
||||
config.setAllowCredentials(true);
|
||||
config.addAllowedOrigin("*");
|
||||
config.addAllowedHeader("*");
|
||||
config.addAllowedMethod("*");
|
||||
source.registerCorsConfiguration("/**", config);
|
||||
return new CorsFilter(source);
|
||||
}
|
||||
|
||||
@Override
|
||||
public void addResourceHandlers(ResourceHandlerRegistry registry) {
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String pathUtl = "file:" + path.getPath().replace("\\", "/");
|
||||
registry.addResourceHandler("/file/**").addResourceLocations(pathUtl).setCachePeriod(0);
|
||||
registry.addResourceHandler("/file/tables/**").addResourceLocations(pathUtl + "tables/").setCachePeriod(0);
|
||||
registry.addResourceHandler("/file/images/**").addResourceLocations(pathUtl + "images/").setCachePeriod(0);
|
||||
registry.addResourceHandler("/**").addResourceLocations("classpath:/META-INF/resources/").setCachePeriod(0);
|
||||
}
|
||||
|
||||
@Override
|
||||
public void configureMessageConverters(List<HttpMessageConverter<?>> converters) {
|
||||
// 使用 fastjson 序列化，会导致 @JsonIgnore 失效，可以使用 @JSONField(serialize = false) 替换
|
||||
// Use fastjson serialization, which will cause @JsonIgnore to be invalid, can be replaced with @JSONField (serialize = false)
|
||||
FastJsonHttpMessageConverter fastJsonHttpMessageConverter = new FastJsonHttpMessageConverter();
|
||||
List<MediaType> supportMediaTypeList = new ArrayList<>();
|
||||
supportMediaTypeList.add(MediaType.APPLICATION_JSON_UTF8);
|
||||
supportMediaTypeList.add(MediaType.TEXT_HTML);
|
||||
FastJsonConfig config = new FastJsonConfig();
|
||||
config.setDateFormat("yyyy-MM-dd HH:mm:ss");
|
||||
config.setSerializerFeatures(SerializerFeature.DisableCircularReferenceDetect);
|
||||
fastJsonHttpMessageConverter.setFastJsonConfig(config);
|
||||
fastJsonHttpMessageConverter.setSupportedMediaTypes(supportMediaTypeList);
|
||||
fastJsonHttpMessageConverter.setDefaultCharset(StandardCharsets.UTF_8);
|
||||
|
||||
converters.add(fastJsonHttpMessageConverter);
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,46 @@
|
||||
package top.aias.iocr.configuration;
|
||||
|
||||
import lombok.Data;
|
||||
import top.aias.iocr.utils.Constants;
|
||||
import org.springframework.boot.context.properties.ConfigurationProperties;
|
||||
import org.springframework.context.annotation.Configuration;
|
||||
|
||||
/**
|
||||
* 文件配置
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Data
|
||||
@Configuration
|
||||
@ConfigurationProperties(prefix = "file")
|
||||
public class FileProperties {
|
||||
|
||||
/**
|
||||
* File size limitation
|
||||
*/
|
||||
private Long maxSize;
|
||||
|
||||
private ElPath mac;
|
||||
|
||||
private ElPath linux;
|
||||
|
||||
private ElPath windows;
|
||||
|
||||
public ElPath getPath() {
|
||||
String os = System.getProperty("os.name");
|
||||
if (os.toLowerCase().startsWith(Constants.WIN)) {
|
||||
return windows;
|
||||
} else if (os.toLowerCase().startsWith(Constants.MAC)) {
|
||||
return mac;
|
||||
}
|
||||
return linux;
|
||||
}
|
||||
|
||||
@Data
|
||||
public static class ElPath {
|
||||
|
||||
private String path;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,46 @@
|
||||
package top.aias.iocr.configuration;
|
||||
|
||||
import ai.djl.MalformedModelException;
|
||||
import ai.djl.repository.zoo.ModelNotFoundException;
|
||||
import top.aias.iocr.model.MlsdSquareModel;
|
||||
import top.aias.iocr.model.RecognitionModel;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
import org.springframework.context.annotation.Bean;
|
||||
import org.springframework.context.annotation.Configuration;
|
||||
|
||||
import java.io.IOException;
|
||||
|
||||
/**
|
||||
* 模型配置
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Configuration
|
||||
public class ModelConfiguration {
|
||||
// ocr model
|
||||
@Value("${model.ocrv4.det}")
|
||||
private String ocrDet;
|
||||
@Value("${model.ocrv4.rec}")
|
||||
private String ocrRec;
|
||||
@Value("${model.mlsd.model}")
|
||||
private String mlsd;
|
||||
@Value("${model.poolSize}")
|
||||
private int poolSize;
|
||||
|
||||
|
||||
@Bean
|
||||
public RecognitionModel recognitionModel() throws IOException, ModelNotFoundException, MalformedModelException {
|
||||
RecognitionModel recognitionModel = new RecognitionModel();
|
||||
recognitionModel.init(ocrDet, ocrRec, poolSize);
|
||||
return recognitionModel;
|
||||
}
|
||||
|
||||
@Bean
|
||||
public MlsdSquareModel mlsdSquareModel() throws IOException, ModelNotFoundException, MalformedModelException {
|
||||
MlsdSquareModel mlsdSquareModel = new MlsdSquareModel();
|
||||
mlsdSquareModel.init(mlsd, poolSize);
|
||||
return mlsdSquareModel;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,112 @@
|
||||
/*
|
||||
* Copyright 2019-2020 Zheng Jie
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
package top.aias.iocr.configuration;
|
||||
|
||||
import com.fasterxml.classmate.TypeResolver;
|
||||
import com.google.common.base.Predicates;
|
||||
import io.swagger.annotations.ApiModel;
|
||||
import io.swagger.annotations.ApiModelProperty;
|
||||
import lombok.Data;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
import org.springframework.context.annotation.Bean;
|
||||
import org.springframework.context.annotation.Configuration;
|
||||
import org.springframework.core.Ordered;
|
||||
import org.springframework.data.domain.Pageable;
|
||||
import springfox.documentation.builders.ApiInfoBuilder;
|
||||
import springfox.documentation.builders.ParameterBuilder;
|
||||
import springfox.documentation.builders.PathSelectors;
|
||||
import springfox.documentation.schema.AlternateTypeRule;
|
||||
import springfox.documentation.schema.AlternateTypeRuleConvention;
|
||||
import springfox.documentation.service.ApiInfo;
|
||||
import springfox.documentation.spi.DocumentationType;
|
||||
import springfox.documentation.spring.web.plugins.Docket;
|
||||
import springfox.documentation.swagger2.annotations.EnableSwagger2;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import static com.google.common.collect.Lists.newArrayList;
|
||||
import static springfox.documentation.schema.AlternateTypeRules.newRule;
|
||||
|
||||
/**
|
||||
* api doc.html
|
||||
* @author Calvin
|
||||
* @date Oct 19, 2021
|
||||
*/
|
||||
@Configuration
|
||||
@EnableSwagger2
|
||||
public class SwaggerConfig {
|
||||
|
||||
|
||||
@Value("${swagger.enabled}")
|
||||
private Boolean enabled;
|
||||
|
||||
@Bean
|
||||
@SuppressWarnings("all")
|
||||
public Docket createRestApi() {
|
||||
ParameterBuilder ticketPar = new ParameterBuilder();
|
||||
return new Docket(DocumentationType.SWAGGER_2)
|
||||
.enable(enabled)
|
||||
.apiInfo(apiInfo())
|
||||
.select()
|
||||
.paths(Predicates.not(PathSelectors.regex("/error.*")))
|
||||
.build();
|
||||
}
|
||||
|
||||
private ApiInfo apiInfo() {
|
||||
return new ApiInfoBuilder()
|
||||
.description("")
|
||||
.title("API Doc")
|
||||
.version("1.0")
|
||||
.build();
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
/**
|
||||
* 将Pageable转换展示在swagger中
|
||||
* Convert Pageable for display in Swagger
|
||||
*/
|
||||
@Configuration
|
||||
class SwaggerDataConfig {
|
||||
|
||||
@Bean
|
||||
public AlternateTypeRuleConvention pageableConvention(final TypeResolver resolver) {
|
||||
return new AlternateTypeRuleConvention() {
|
||||
@Override
|
||||
public int getOrder() {
|
||||
return Ordered.HIGHEST_PRECEDENCE;
|
||||
}
|
||||
|
||||
@Override
|
||||
public List<AlternateTypeRule> rules() {
|
||||
return newArrayList(newRule(resolver.resolve(Pageable.class), resolver.resolve(Page.class)));
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
@ApiModel
|
||||
@Data
|
||||
private static class Page {
|
||||
@ApiModelProperty("Page number (0..N)")
|
||||
private Integer page;
|
||||
|
||||
@ApiModelProperty("Number of items per page")
|
||||
private Integer size;
|
||||
|
||||
@ApiModelProperty("Sort criteria in the following format: property[,asc|desc]. Default sort order is ascending. Multiple sort conditions are supported, such as id,asc")
|
||||
private List<String> sort;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,151 @@
|
||||
package top.aias.iocr.controller;
|
||||
|
||||
import ai.djl.Device;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.opencv.OpenCVImageFactory;
|
||||
import io.swagger.annotations.Api;
|
||||
import io.swagger.annotations.ApiOperation;
|
||||
import top.aias.iocr.bean.DataBean;
|
||||
import top.aias.iocr.bean.Point;
|
||||
import top.aias.iocr.bean.ResultBean;
|
||||
import top.aias.iocr.bean.RotatedBox;
|
||||
import top.aias.iocr.service.InferService;
|
||||
import top.aias.iocr.utils.ImageUtils;
|
||||
import top.aias.iocr.utils.OpenCVUtils;
|
||||
import org.opencv.core.Mat;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.web.multipart.MultipartFile;
|
||||
|
||||
import java.awt.image.BufferedImage;
|
||||
import java.io.InputStream;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 文字识别
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Api(tags = "通用文字识别 -General Text Recognition")
|
||||
@RestController
|
||||
@RequestMapping("/inference")
|
||||
public class InferController {
|
||||
private Logger logger = LoggerFactory.getLogger(InferController.class);
|
||||
|
||||
@Autowired
|
||||
private InferService inferService;
|
||||
|
||||
@Value("${server.baseUri}")
|
||||
private String baseUri;
|
||||
|
||||
@ApiOperation(value = "通用文字识别-URL -General Text Recognition-URL")
|
||||
@GetMapping(value = "/generalInfoForImageUrl", produces = "application/json;charset=utf-8")
|
||||
public ResultBean generalInfoForImageUrl(@RequestParam(value = "url") String url) {
|
||||
try(NDManager manager = NDManager.newBaseManager(Device.cpu(), "PyTorch")) {
|
||||
Image image = OpenCVImageFactory.getInstance().fromUrl(url);
|
||||
List<RotatedBox> detections = inferService.getGeneralInfo(manager, image);
|
||||
List<DataBean> dataList = this.getDataList(detections);
|
||||
|
||||
// 转 BufferedImage 解决 Imgproc.putText 中文乱码问题
|
||||
Mat wrappedImage = (Mat) image.getWrappedImage();
|
||||
BufferedImage bufferedImage = OpenCVUtils.mat2Image(wrappedImage);
|
||||
for (RotatedBox result : detections) {
|
||||
ImageUtils.drawImageRectWithText(bufferedImage, result.getBox(), result.getText());
|
||||
}
|
||||
String base64Img = ImageUtils.toBase64(bufferedImage, "jpg");
|
||||
|
||||
return ResultBean.success().add("result", dataList).add("base64Img", "data:imageName/jpeg;base64," + base64Img);
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
e.printStackTrace();
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "通用文字识别-图片 -General Text Recognition-Image")
|
||||
@PostMapping(value = "/generalInfoForImageFile", produces = "application/json;charset=utf-8")
|
||||
public ResultBean generalInfoForImageFile(@RequestParam(value = "imageFile") MultipartFile imageFile) {
|
||||
try (InputStream inputStream = imageFile.getInputStream();
|
||||
NDManager manager = NDManager.newBaseManager(Device.cpu(), "PyTorch")) {
|
||||
// String base64Img = Base64.encodeBase64String(imageFile.getBytes());
|
||||
Image image = OpenCVImageFactory.getInstance().fromInputStream(inputStream);
|
||||
List<RotatedBox> detections = inferService.getGeneralInfo(manager, image);
|
||||
List<DataBean> dataList = this.getDataList(detections);
|
||||
|
||||
// 转 BufferedImage 解决 Imgproc.putText 中文乱码问题
|
||||
Mat wrappedImage = (Mat) image.getWrappedImage();
|
||||
BufferedImage bufferedImage = OpenCVUtils.mat2Image(wrappedImage);
|
||||
for (RotatedBox result : detections) {
|
||||
ImageUtils.drawImageRectWithText(bufferedImage, result.getBox(), result.getText());
|
||||
}
|
||||
String base64Img = ImageUtils.toBase64(bufferedImage, "jpg");
|
||||
|
||||
return ResultBean.success().add("result", dataList).add("base64Img", "data:imageName/jpeg;base64," + base64Img);
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
e.printStackTrace();
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
// @ApiOperation(value = "转正对齐-URL")
|
||||
// @GetMapping(value = "/mlsdForImageUrl", produces = "application/json;charset=utf-8")
|
||||
// public ResultBean mlsdForImageUrl(@RequestParam(value = "url") String url) throws IOException {
|
||||
// try {
|
||||
// Image image = OpenCVImageFactory.getInstance().fromUrl(url);
|
||||
// Image warpImg = inferService.getWarpImg(image);
|
||||
// BufferedImage buffImage = OpenCVUtils.mat2Image((Mat) warpImg.getWrappedImage());
|
||||
// String base64Img = ImageUtils.toBase64(buffImage,"jpg");
|
||||
// return ResultBean.success().add("base64Img", "data:imageName/jpeg;base64," + base64Img);
|
||||
// } catch (Exception e) {
|
||||
// logger.error(e.getMessage());
|
||||
// e.printStackTrace();
|
||||
// return ResultBean.failure().add("message", e.getMessage());
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// @ApiOperation(value = "转正对齐-图片")
|
||||
// @PostMapping(value = "/mlsdForImageFile", produces = "application/json;charset=utf-8")
|
||||
// public ResultBean mlsdForImageFile(@RequestParam(value = "imageFile") MultipartFile imageFile) {
|
||||
// try (InputStream inputStream = imageFile.getInputStream()) {
|
||||
// Image image = OpenCVImageFactory.getInstance().fromInputStream(inputStream);
|
||||
// Image warpImg = inferService.getWarpImg(image);
|
||||
// BufferedImage buffImage = OpenCVUtils.mat2Image((Mat) warpImg.getWrappedImage());
|
||||
//
|
||||
// String orgBase64Img = Base64.encodeBase64String(imageFile.getBytes());
|
||||
// String base64Img = ImageUtils.toBase64(buffImage,"jpg");
|
||||
// return ResultBean.success().add("orgBase64Img", "data:imageName/jpeg;base64," + orgBase64Img).add("base64Img", "data:imageName/jpeg;base64," + base64Img);
|
||||
// } catch (Exception e) {
|
||||
// logger.error(e.getMessage());
|
||||
// e.printStackTrace();
|
||||
// return ResultBean.failure().add("message", e.getMessage());
|
||||
// }
|
||||
// }
|
||||
|
||||
private List<DataBean> getDataList(List<RotatedBox> detections){
|
||||
List<DataBean> dataList = new ArrayList<>();
|
||||
|
||||
for (RotatedBox rotatedBox : detections) {
|
||||
DataBean dataBean = new DataBean();
|
||||
List<Point> points = new ArrayList<>();
|
||||
dataBean.setValue(rotatedBox.getText());
|
||||
|
||||
float[] pointsArr = rotatedBox.getBox().toFloatArray();
|
||||
for (int i = 0; i < 4; i++) {
|
||||
Point point = new Point((int) pointsArr[2 * i], (int) pointsArr[2 * i + 1]);
|
||||
points.add(point);
|
||||
}
|
||||
|
||||
dataBean.setPoints(points);
|
||||
dataList.add(dataBean);
|
||||
}
|
||||
return dataList;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,215 @@
|
||||
package top.aias.iocr.controller;
|
||||
|
||||
import ai.djl.Device;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.opencv.OpenCVImageFactory;
|
||||
import io.swagger.annotations.Api;
|
||||
import io.swagger.annotations.ApiOperation;
|
||||
import org.apache.commons.codec.binary.Base64;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.context.annotation.Configuration;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.web.multipart.MultipartFile;
|
||||
import top.aias.iocr.bean.*;
|
||||
import top.aias.iocr.configuration.FileProperties;
|
||||
import top.aias.iocr.service.InferService;
|
||||
import top.aias.iocr.service.TemplateService;
|
||||
import top.aias.iocr.utils.FileUtils;
|
||||
import top.aias.iocr.utils.UUIDUtils;
|
||||
|
||||
import java.io.InputStream;
|
||||
import java.nio.file.Path;
|
||||
import java.nio.file.Paths;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
/**
|
||||
* 自定义模版文字识别
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Api(tags = "自定义模版文字识别 - Custom Template Text Recognition")
|
||||
@RestController
|
||||
@Configuration
|
||||
@RequestMapping("/template")
|
||||
public class TemplateController {
|
||||
private Logger logger = LoggerFactory.getLogger(TemplateController.class);
|
||||
|
||||
@Autowired
|
||||
private TemplateService ocrTemplateService;
|
||||
@Autowired
|
||||
private InferService inferService;
|
||||
|
||||
/**
|
||||
* 文件配置
|
||||
* File Configuration
|
||||
*/
|
||||
@Autowired
|
||||
private FileProperties properties;
|
||||
|
||||
@ApiOperation(value = "获取模版信息 Get Template Information")
|
||||
@GetMapping(value = "/getTemplate", produces = "application/json;charset=utf-8")
|
||||
public ResultBean getTemplate(@RequestParam(value = "uid") String uid) {
|
||||
try {
|
||||
TemplateBean templateBean = ocrTemplateService.getTemplate(uid);
|
||||
return ResultBean.success().add("result", templateBean);
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "获取模版列表 Get Template List")
|
||||
@GetMapping(value = "/getTemplates", produces = "application/json;charset=utf-8")
|
||||
public ResultBean getTemplatesList() {
|
||||
try {
|
||||
return ResultBean.success().add("result", ocrTemplateService.getTemplateList());
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "更新模板信息 Update Template Information")
|
||||
@PostMapping(value = "/updateTemplate", consumes = "application/json;charset=utf-8")
|
||||
public ResultBean updateTemplate(@RequestBody TemplateBean templateBean) {
|
||||
try (NDManager manager = NDManager.newBaseManager(Device.cpu(), "PyTorch")) {
|
||||
|
||||
// 检测锚点框的数量
|
||||
List<LabelBean> anchorlabels = ocrTemplateService.getLabelDataByType(templateBean.getLabelData(), "anchor");
|
||||
if(anchorlabels.size() < 4){
|
||||
return ResultBean.failure().add("message", "锚点参考框至少需要4个，不能小于4个。");
|
||||
}
|
||||
|
||||
// 更新手工标注的模板信息
|
||||
ocrTemplateService.updateTemplate(templateBean);
|
||||
|
||||
// 新建或者更新手工标注的模板信息
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String imagePath = path.getPath().replace("\\", "/") + "images/" + templateBean.getImageName();
|
||||
Path imageFile = Paths.get(imagePath);
|
||||
Image templateImg = OpenCVImageFactory.getInstance().fromFile(imageFile);
|
||||
List<RotatedBox> detections = inferService.getGeneralInfo(manager, templateImg);
|
||||
// 将手工标注的参考框坐标替换为对应自动检测框的坐标，手工标注的会有几个像素的偏移，影响透视变换的效果
|
||||
List<LabelBean> updatedLabelData = ocrTemplateService.getImageInfo(templateBean, detections);
|
||||
|
||||
String templatePath = path.getPath().replace("\\", "/") + "templates/recinfo/";
|
||||
FileUtils.checkAndCreatePath(templatePath);
|
||||
templateBean.setLabelData(updatedLabelData);
|
||||
ocrTemplateService.updateTemplateRecInfo(templateBean);
|
||||
return ResultBean.success();
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "删除模板 Remove Template")
|
||||
@PostMapping(value = "/removeTemplate", produces = "application/json;charset=utf-8")
|
||||
public ResultBean removeTemplate(@RequestParam(value = "uid") String uid) {
|
||||
try {
|
||||
ocrTemplateService.removeTemplate(uid);
|
||||
return ResultBean.success();
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "识别标注字段 Recognize Label Fields")
|
||||
@PostMapping(value = "/getLabelData", produces = "application/json;charset=utf-8")
|
||||
public ResultBean getLabelData(@RequestBody LabelDTO labelDTO) {
|
||||
try {
|
||||
String result = ocrTemplateService.getLabelData(labelDTO.getUid(), labelDTO.getLabelData());
|
||||
logger.info("LabelData: " + result);
|
||||
return ResultBean.success().add("result", result);
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
e.printStackTrace();
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "创建模板 Create Template")
|
||||
@PostMapping(value = "/addTemplate")
|
||||
public ResultBean addTemplate(@RequestParam(value = "name") String name, @RequestParam(value = "imageFile") MultipartFile imageFile) {
|
||||
try {
|
||||
// 要上传的目标文件存放路径
|
||||
// Target file storage path to be uploaded
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String imagePath = path.getPath().replace("\\", "/") + "images/";
|
||||
FileUtils.checkAndCreatePath(imagePath);
|
||||
String templatePath = path.getPath().replace("\\", "/") + "templates/";
|
||||
FileUtils.checkAndCreatePath(templatePath);
|
||||
|
||||
TemplateBean templateBean = new TemplateBean();
|
||||
String uid = UUIDUtils.getUUID();
|
||||
templateBean.setUid(uid);
|
||||
//image/jpg' || 'image/jpeg' || 'image/png'
|
||||
String suffix = FileUtils.getSuffix(imageFile.getOriginalFilename());
|
||||
if (!suffix.equalsIgnoreCase(".jpg") &&
|
||||
!suffix.equalsIgnoreCase(".jpeg") &&
|
||||
!suffix.equalsIgnoreCase(".png") &&
|
||||
!suffix.equalsIgnoreCase(".bmp")) {
|
||||
return ResultBean.failure().add("errors", "图片格式应为: jpg, jpeg, png 或者 bmp!");
|
||||
}
|
||||
String imageName = FileUtils.getFileName(imageFile.getOriginalFilename());
|
||||
templateBean.setImageName(imageName);
|
||||
templateBean.setName(name);
|
||||
|
||||
logger.info("Template name:" + name);
|
||||
|
||||
if (FileUtils.upload(imageFile, imagePath, imageName)) {
|
||||
ocrTemplateService.addTemplate(templateBean);
|
||||
return ResultBean.success().add("result", templateBean);
|
||||
} else {
|
||||
return ResultBean.failure();
|
||||
}
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
e.printStackTrace();
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "模版文字识别-URL Template Text Recognition-URL")
|
||||
@GetMapping(value = "/infoForImageUrl", produces = "application/json;charset=utf-8")
|
||||
public ResultBean infoForImageUrl(@RequestParam(value = "uid") String uid, @RequestParam(value = "url") String url) {
|
||||
try {
|
||||
// TemplateBean templateBean = ocrTemplateService.getTemplate(uid);
|
||||
TemplateBean templateBean = ocrTemplateService.getTemplateRecInfo(uid);
|
||||
Image image = OpenCVImageFactory.getInstance().fromUrl(url);
|
||||
Map<String, String> hashMap = ocrTemplateService.getImageInfo(templateBean, image);
|
||||
|
||||
return ResultBean.success().add("result", hashMap);
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
e.printStackTrace();
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
@ApiOperation(value = "模版文字识别-图片 - Template Text Recognition-Image")
|
||||
@PostMapping(value = "/infoForImageFile", produces = "application/json;charset=utf-8")
|
||||
public ResultBean infoForImageFile(@RequestParam(value = "uid") String uid, @RequestParam(value = "imageFile") MultipartFile imageFile) {
|
||||
try (InputStream inputStream = imageFile.getInputStream()) {
|
||||
String base64Img = Base64.encodeBase64String(imageFile.getBytes());
|
||||
// TemplateBean templateBean = ocrTemplateService.getTemplate(uid);
|
||||
TemplateBean templateBean = ocrTemplateService.getTemplateRecInfo(uid);
|
||||
Image image = OpenCVImageFactory.getInstance().fromInputStream(inputStream);
|
||||
Map<String, String> hashMap = ocrTemplateService.getImageInfo(templateBean, image);
|
||||
|
||||
return ResultBean.success().add("result", hashMap)
|
||||
.add("base64Img", "data:imageName/jpeg;base64," + base64Img);
|
||||
} catch (Exception e) {
|
||||
logger.error(e.getMessage());
|
||||
e.printStackTrace();
|
||||
return ResultBean.failure().add("message", e.getMessage());
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,815 @@
|
||||
package top.aias.iocr.model;
|
||||
|
||||
import ai.djl.Device;
|
||||
import ai.djl.MalformedModelException;
|
||||
import ai.djl.inference.Predictor;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.ImageFactory;
|
||||
import ai.djl.modality.cv.util.NDImageUtils;
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDArrays;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.ndarray.index.NDIndex;
|
||||
import ai.djl.ndarray.types.DataType;
|
||||
import ai.djl.ndarray.types.Shape;
|
||||
import ai.djl.repository.zoo.Criteria;
|
||||
import ai.djl.repository.zoo.ModelNotFoundException;
|
||||
import ai.djl.repository.zoo.ModelZoo;
|
||||
import ai.djl.repository.zoo.ZooModel;
|
||||
import ai.djl.training.util.ProgressBar;
|
||||
import ai.djl.translate.Batchifier;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import ai.djl.translate.Translator;
|
||||
import ai.djl.translate.TranslatorContext;
|
||||
import top.aias.iocr.model.pool.MlsdPool;
|
||||
import top.aias.iocr.utils.NDArrayUtils;
|
||||
import top.aias.iocr.utils.OpenCVUtils;
|
||||
import org.opencv.core.Mat;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.nio.file.Paths;
|
||||
import java.util.ArrayList;
|
||||
|
||||
/**
|
||||
* 图像转正模型
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public final class MlsdSquareModel implements AutoCloseable {
|
||||
private ZooModel<Image, Image> model;
|
||||
private MlsdPool mlsdPool;
|
||||
|
||||
private float thr_v = 0.1f;
|
||||
private float thr_d = 0.1f;
|
||||
private int detect_resolution = 512;
|
||||
|
||||
public void init(String modelUri, int poolSize) throws MalformedModelException, ModelNotFoundException, IOException {
|
||||
this.model = ModelZoo.loadModel(onnxCriteria(modelUri));
|
||||
this.mlsdPool = new MlsdPool(poolSize, model);
|
||||
}
|
||||
|
||||
public void close() {
|
||||
this.model.close();
|
||||
this.mlsdPool.close();
|
||||
}
|
||||
|
||||
// 多线程环境，每个线程一个predictor，共享一个model, 资源池（CPU Core 核心数）达到上限则等待
|
||||
public Image predict(Image image) throws TranslateException {
|
||||
Predictor<Image, Image> predictor = mlsdPool.getPredictor();
|
||||
Image cropImg = predictor.predict(image);
|
||||
// 释放资源
|
||||
mlsdPool.releasePredictor(predictor);
|
||||
|
||||
return cropImg;
|
||||
}
|
||||
|
||||
private Criteria<Image, Image> onnxCriteria(String modelUri) {
|
||||
|
||||
Criteria<Image, Image> criteria =
|
||||
Criteria.builder()
|
||||
.optEngine("OnnxRuntime")
|
||||
.setTypes(Image.class, Image.class)
|
||||
.optModelName("mlsd_traced_model")
|
||||
.optModelPath(Paths.get(modelUri))
|
||||
.optDevice(Device.cpu())
|
||||
// .optDevice(Device.gpu())
|
||||
.optTranslator(new FeatureTranslator())
|
||||
.optProgress(new ProgressBar())
|
||||
.build();
|
||||
|
||||
return criteria;
|
||||
}
|
||||
|
||||
private final class FeatureTranslator implements Translator<Image, Image> {
|
||||
protected Batchifier batchifier = Batchifier.STACK;
|
||||
private int topk_n = 200;
|
||||
private int ksize = 3;
|
||||
private float score = 0.06f;
|
||||
private float outside_ratio = 0.28f;
|
||||
private float inside_ratio = 0.45f;
|
||||
private float w_overlap = 0.0f;
|
||||
private float w_degree = 1.95f;
|
||||
private float w_length = 0.0f;
|
||||
private float w_area = 1.86f;
|
||||
private float w_center = 0.1f;
|
||||
private NDArray imgArray;
|
||||
private int original_shape[] = new int[2];
|
||||
private int input_shape[] = new int[2];
|
||||
|
||||
FeatureTranslator() {
|
||||
}
|
||||
|
||||
@Override
|
||||
public NDList processInput(TranslatorContext ctx, Image input) {
|
||||
try (NDManager manager = NDManager.newBaseManager(ctx.getNDManager().getDevice(), "PyTorch")) {
|
||||
original_shape[1] = input.getWidth(); // w - input_shape[1]
|
||||
original_shape[0] = input.getHeight(); // h - input_shape[0]
|
||||
|
||||
NDArray array = input.toNDArray(ctx.getNDManager(), Image.Flag.COLOR);
|
||||
|
||||
array = array.toType(DataType.UINT8, false);
|
||||
|
||||
imgArray = array;
|
||||
|
||||
// NDArray padding_im = ctx.getNDManager().zeros(new Shape(array.getShape().get(0) + 200, array.getShape().get(1) + 200, array.getShape().get(2)), DataType.FLOAT32);
|
||||
// padding_im.set(new NDIndex("100:" + (original_shape[0] + 100) + ",100:"+ (original_shape[1]+ 100) + ",:" ), imgArray);
|
||||
|
||||
// h : input_shape[0], w : input_shape[1]
|
||||
input_shape = resize64(original_shape[0], original_shape[1], detect_resolution);
|
||||
|
||||
array = NDImageUtils.resize(array, input_shape[1], input_shape[0], Image.Interpolation.AREA);
|
||||
|
||||
NDArray ones = manager.ones(new Shape(array.getShape().get(0), array.getShape().get(1), 1), DataType.UINT8);
|
||||
|
||||
array = array.concat(ones, -1);
|
||||
|
||||
array = array.transpose(2, 0, 1); // HWC -> CHW RGB
|
||||
|
||||
array = array.toType(DataType.FLOAT32, false);
|
||||
|
||||
array = array.div(127.5f).sub(1.0f);
|
||||
|
||||
array = array.flip(0);
|
||||
|
||||
return new NDList(array);
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public Image processOutput(TranslatorContext ctx, NDList list) {
|
||||
try (NDManager manager = NDManager.newBaseManager(ctx.getNDManager().getDevice(), "PyTorch")) {
|
||||
|
||||
NDArray tpMap = list.singletonOrThrow();
|
||||
|
||||
// deccode_output_score_and_ptss(tpMap, topk_n = 200, ksize = 3) start
|
||||
int width = (int) (tpMap.getShape().get(2));
|
||||
|
||||
NDArray displacement = tpMap.get("1:5, :, :");
|
||||
|
||||
NDArray center = tpMap.get("0, :, :");
|
||||
|
||||
// Sigmoid 函数，即f(x)=1/(1+e-x)
|
||||
NDArray heat = NDArrayUtils.Sigmoid(center);
|
||||
|
||||
NDArray hmax = NDArrayUtils.maxPool(manager, heat, ksize, 1, (ksize - 1) / 2);
|
||||
|
||||
NDArray keep = hmax.eq(heat);
|
||||
keep = keep.toType(DataType.FLOAT32, false);
|
||||
|
||||
heat = heat.mul(keep);
|
||||
heat = heat.reshape(-1);
|
||||
|
||||
NDArray indices = heat.argSort(-1, false).get("0:200");
|
||||
NDArray pts_score = heat.get(indices);
|
||||
indices = indices.toType(DataType.FLOAT32, true);
|
||||
NDArray yy = indices.div(width).floor().expandDims(-1);
|
||||
NDArray xx = indices.mod(width).expandDims(-1);
|
||||
NDArray pts = yy.concat(xx, -1);
|
||||
|
||||
NDArray vmap = displacement.transpose(1, 2, 0);
|
||||
// deccode_output_score_and_ptss end
|
||||
|
||||
NDArray start = vmap.get(":, :, :2");
|
||||
NDArray end = vmap.get(":, :, 2:");
|
||||
|
||||
NDArray dist_map = start.sub(end).pow(2).sum(new int[]{-1}).sqrt();
|
||||
|
||||
ArrayList<float[]> junc_list = new ArrayList<>();
|
||||
ArrayList<float[]> segments_list = new ArrayList<>();
|
||||
|
||||
for (int i = 0; i < pts_score.size(); i++) {
|
||||
center = pts.get(i);
|
||||
int y = (int) center.getFloat(0);
|
||||
int x = (int) center.getFloat(1);
|
||||
float score = pts_score.getFloat(i);
|
||||
float distance = dist_map.getFloat(y, x);
|
||||
|
||||
if (score > this.score && distance > 20.0f) {
|
||||
float[] junc = new float[2];
|
||||
junc[0] = x;
|
||||
junc[1] = y;
|
||||
junc_list.add(junc);
|
||||
|
||||
NDArray array = vmap.get(y + "," + x + ",:"); // y, x, :
|
||||
float disp_x_start = array.getFloat(0);
|
||||
float disp_y_start = array.getFloat(1);
|
||||
float disp_x_end = array.getFloat(2);
|
||||
float disp_y_end = array.getFloat(3);
|
||||
|
||||
float x_start = x + disp_x_start;
|
||||
float y_start = y + disp_y_start;
|
||||
float x_end = x + disp_x_end;
|
||||
float y_end = y + disp_y_end;
|
||||
|
||||
float[] segment = new float[4];
|
||||
segment[0] = x_start;
|
||||
segment[1] = y_start;
|
||||
segment[2] = x_end;
|
||||
segment[3] = y_end;
|
||||
|
||||
segments_list.add(segment);
|
||||
}
|
||||
}
|
||||
|
||||
float[][] segmentsArr = new float[segments_list.size()][4];
|
||||
for (int i = 0; i < segments_list.size(); i++) {
|
||||
float[] item = segments_list.get(i);
|
||||
segmentsArr[i][0] = item[0];
|
||||
segmentsArr[i][1] = item[1];
|
||||
segmentsArr[i][2] = item[2];
|
||||
segmentsArr[i][3] = item[3];
|
||||
}
|
||||
|
||||
NDArray segments = manager.create(segmentsArr).toType(DataType.FLOAT32, false);
|
||||
|
||||
// ####### post processing for squares
|
||||
// 1. get unique lines
|
||||
start = segments.get(":, :2");
|
||||
end = segments.get(":, 2:");
|
||||
NDArray diff = start.sub(end);
|
||||
|
||||
NDArray a = diff.get(":, 1");
|
||||
NDArray b = diff.get(":, 0").neg();
|
||||
NDArray c = a.mul(start.get(":, 0")).add(b.mul(start.get(":, 1")));
|
||||
NDArray d = c.abs().div(a.square().add(b.square().add(Math.exp(-10))).sqrt());
|
||||
|
||||
NDArray theta = NDArrayUtils.arctan2(diff.get(":, 0"), diff.get(":, 1"));
|
||||
NDArray index = theta.lt(0.0f);
|
||||
index = index.toType(DataType.INT32, false).mul(180);
|
||||
theta = theta.add(index);
|
||||
|
||||
NDArray hough = d.expandDims(1).concat(theta.expandDims(1), -1);
|
||||
|
||||
int d_quant = 1;
|
||||
int theta_quant = 2;
|
||||
hough.get(":, 0").divi(d_quant);
|
||||
hough.get(":, 1").divi(theta_quant);
|
||||
hough = hough.floor();
|
||||
float[][] houghArr = NDArrayUtils.floatNDArrayToArray(hough);
|
||||
|
||||
NDList ndList = hough.unique(0, true, false, true);
|
||||
// 唯一的元素列表
|
||||
NDArray yx_indices = ndList.get(0).toType(DataType.INT32, false);
|
||||
int[][] yx_indicesArr = NDArrayUtils.intNDArrayToArray(yx_indices);
|
||||
int[] inds = new int[yx_indicesArr.length];
|
||||
// 唯一的元素,对应的数量
|
||||
NDArray counts = ndList.get(2);
|
||||
long[] countsArr = counts.toLongArray();
|
||||
|
||||
for (int i = 0; i < yx_indicesArr.length; i++) {
|
||||
for (int j = 0; j < houghArr.length; j++) {
|
||||
if (yx_indicesArr[i][0] == houghArr[j][0] && yx_indicesArr[i][1] == houghArr[j][1]) {
|
||||
inds[i] = j;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
NDArray acc_map = manager.zeros(new Shape(512 / d_quant + 1, 360 / theta_quant + 1), DataType.FLOAT32);
|
||||
NDArray idx_map = manager.zeros(new Shape(512 / d_quant + 1, 360 / theta_quant + 1), DataType.INT32).sub(1);
|
||||
|
||||
for (int i = 0; i < yx_indicesArr.length; i++) {
|
||||
acc_map.set(new NDIndex(yx_indicesArr[i][0], yx_indicesArr[i][1]), countsArr[i]);
|
||||
idx_map.set(new NDIndex(yx_indicesArr[i][0], yx_indicesArr[i][1]), inds[i]);
|
||||
}
|
||||
|
||||
float[][] acc_map_np = NDArrayUtils.floatNDArrayToArray(acc_map);
|
||||
|
||||
NDArray max_acc_map = NDArrayUtils.maxPool(manager, acc_map, 5, 1, 2);
|
||||
|
||||
|
||||
keep = acc_map.eq(max_acc_map);
|
||||
keep = keep.toType(DataType.FLOAT32, false);
|
||||
acc_map = acc_map.mul(keep);
|
||||
NDArray flatten_acc_map = acc_map.flatten();
|
||||
|
||||
indices = flatten_acc_map.argSort(-1, false).get("0:200");
|
||||
|
||||
NDArray scores = flatten_acc_map.get(indices);
|
||||
int cols = (int) (acc_map.getShape().get(1));
|
||||
yy = indices.div(cols).floor().expandDims(-1);
|
||||
xx = indices.mod(cols).expandDims(-1);
|
||||
NDArray yx = yy.concat(xx, -1);
|
||||
float[][] yx_arr = NDArrayUtils.floatNDArrayToArray(yx);
|
||||
float[] topk_values = scores.toFloatArray();
|
||||
int[][] idx_map_arr = NDArrayUtils.intNDArrayToArray(idx_map);
|
||||
|
||||
int[] indices_arr = new int[yx_arr.length];
|
||||
for (int i = 0; i < yx_arr.length; i++) {
|
||||
indices_arr[i] = idx_map_arr[(int) yx_arr[i][0]][(int) yx_arr[i][1]];
|
||||
}
|
||||
|
||||
int basis = 5 / 2;
|
||||
NDArray merged_segments = manager.zeros(new Shape(0, 4), DataType.FLOAT32);
|
||||
for (int i = 0; i < yx_arr.length; i++) {
|
||||
float[] yx_pt = yx_arr[i];
|
||||
float y = yx_pt[0];
|
||||
float x = yx_pt[1];
|
||||
int max_indice = indices_arr[i];
|
||||
float value = topk_values[i];
|
||||
if (max_indice == -1 || value == 0) {
|
||||
continue;
|
||||
}
|
||||
|
||||
NDList segment_list = new NDList();
|
||||
for (int y_offset = -basis; y_offset < basis + 1; y_offset++) {
|
||||
for (int x_offset = -basis; x_offset < basis + 1; x_offset++) {
|
||||
if (y + y_offset < 0 || x + x_offset < 0) {
|
||||
continue;
|
||||
}
|
||||
int indice = idx_map_arr[(int) (y + y_offset)][(int) (x + x_offset)];
|
||||
int cnt = (int) acc_map_np[(int) (y + y_offset)][(int) (x + x_offset)];
|
||||
if (indice != -1) {
|
||||
segment_list.add(segments.get(indice));
|
||||
}
|
||||
if (cnt > 1) {
|
||||
int check_cnt = 1;
|
||||
NDArray current_hough = hough.get(indice);
|
||||
for (int new_indice = 0; new_indice < hough.size(0); new_indice++) {
|
||||
NDArray new_hough = hough.get(new_indice);
|
||||
if (current_hough.eq(new_hough).all().toBooleanArray()[0] && indice != new_indice) {
|
||||
segment_list.add(segments.get(new_indice));
|
||||
check_cnt += 1;
|
||||
if (check_cnt == cnt)
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
NDArray group_segments = NDArrays.concat(segment_list).reshape(-1, 2);
|
||||
NDArray sorted_group_segments = group_segments.sort(0);
|
||||
|
||||
float[] min = sorted_group_segments.get("0, :").toFloatArray();
|
||||
float[] max = sorted_group_segments.get("-1, :").toFloatArray();
|
||||
float x_min = min[0];
|
||||
float y_min = min[1];
|
||||
float x_max = max[0];
|
||||
float y_max = max[1];
|
||||
|
||||
float deg = theta.get(max_indice).toFloatArray()[0];
|
||||
if (deg >= 90) {
|
||||
merged_segments = merged_segments.concat(manager.create(new float[]{x_min, y_max, x_max, y_min}).reshape(1, 4));
|
||||
} else {
|
||||
merged_segments = merged_segments.concat(manager.create(new float[]{x_min, y_min, x_max, y_max}).reshape(1, 4));
|
||||
}
|
||||
}
|
||||
|
||||
// 2. get intersections
|
||||
NDArray new_segments = merged_segments;
|
||||
|
||||
start = new_segments.get(":, :2"); // (x1, y1)
|
||||
end = new_segments.get(":, 2:"); // (x2, y2)
|
||||
NDArray new_centers = start.add(end).div(2.0f);
|
||||
diff = start.sub(end);
|
||||
NDArray dist_segments = diff.square().sum(new int[]{-1}).sqrt();
|
||||
|
||||
// ax + by = c
|
||||
a = diff.get(":, 1");
|
||||
b = diff.get(":, 0").neg();
|
||||
c = a.mul(start.get(":, 0")).add(b.mul(start.get(":, 1")));
|
||||
|
||||
NDArray pre_det = a.expandDims(1).mul(b.expandDims(0));
|
||||
NDArray det = pre_det.sub(pre_det.transpose());
|
||||
NDArray pre_inter_y = a.expandDims(1).mul(c.expandDims(0));
|
||||
NDArray inter_y = pre_inter_y.sub(pre_inter_y.transpose()).div(det.add(Math.exp(-10)));
|
||||
NDArray pre_inter_x = c.expandDims(1).mul(b.expandDims(0));
|
||||
NDArray inter_x = pre_inter_x.sub(pre_inter_x.transpose()).div(det.add(Math.exp(-10)));
|
||||
NDArray inter_pts = inter_x.expandDims(2).concat(inter_y.expandDims(2), -1).toType(DataType.INT32, false);
|
||||
|
||||
// 3. get corner information
|
||||
// 3.1 get distance
|
||||
NDArray dist_inter_to_segment1_start = inter_pts.sub(start.expandDims(1)).square().sum(new int[]{-1}, true).sqrt();
|
||||
NDArray dist_inter_to_segment1_end = inter_pts.sub(end.expandDims(1)).square().sum(new int[]{-1}, true).sqrt();
|
||||
NDArray dist_inter_to_segment2_start = inter_pts.sub(start.expandDims(0)).square().sum(new int[]{-1}, true).sqrt();
|
||||
NDArray dist_inter_to_segment2_end = inter_pts.sub(end.expandDims(0)).square().sum(new int[]{-1}, true).sqrt();
|
||||
|
||||
// sort ascending
|
||||
NDArray dist_inter_to_segment1 = dist_inter_to_segment1_start.concat(dist_inter_to_segment1_end, -1).sort(-1);
|
||||
NDArray dist_inter_to_segment2 = dist_inter_to_segment2_start.concat(dist_inter_to_segment2_end, -1).sort(-1);
|
||||
|
||||
// 3.2 get degree
|
||||
NDArray inter_to_start = new_centers.expandDims(1).sub(inter_pts);
|
||||
NDArray deg_inter_to_start = NDArrayUtils.arctan2(inter_to_start.get(":, :, 1"), inter_to_start.get(":, :, 0"));
|
||||
index = deg_inter_to_start.lt(0.0f);
|
||||
index = index.toType(DataType.INT32, false).mul(360);
|
||||
deg_inter_to_start = deg_inter_to_start.add(index);
|
||||
|
||||
NDArray inter_to_end = new_centers.expandDims(0).sub(inter_pts);
|
||||
|
||||
// np.arctan2和np.arctan都是计算反正切值的NumPy函数，但它们的参数和返回值不同。一般来说，np.arctan2的参数为(y, x)，
|
||||
NDArray deg_inter_to_end = NDArrayUtils.arctan2(inter_to_end.get(":, :, 1"), inter_to_end.get(":, :, 0"));
|
||||
index = deg_inter_to_end.lt(0.0f);
|
||||
index = index.toType(DataType.INT32, false).mul(360);
|
||||
deg_inter_to_end = deg_inter_to_end.add(index);
|
||||
|
||||
// rename variables
|
||||
NDArray deg1_map = deg_inter_to_start;
|
||||
NDArray deg2_map = deg_inter_to_end;
|
||||
|
||||
// sort deg ascending
|
||||
NDArray deg_sort = deg1_map.expandDims(2).concat(deg2_map.expandDims(2), -1).sort(-1);
|
||||
NDArray deg_diff_map = deg1_map.sub(deg2_map).abs();
|
||||
// we only consider the smallest degree of intersect
|
||||
// deg_diff_map[deg_diff_map > 180] = 360 - deg_diff_map[deg_diff_map > 180]
|
||||
// x -> 360- x => x + 360 - 2x = 360 - x
|
||||
index = deg_diff_map.gt(180);
|
||||
NDArray val1 = index.toType(DataType.INT32, false).mul(360);
|
||||
NDArray val2 = index.toType(DataType.INT32, false).mul(deg_diff_map).neg().mul(2);
|
||||
|
||||
deg_diff_map = deg_diff_map.add(val1).add(val2);
|
||||
|
||||
// define available degree range
|
||||
int[] deg_range = new int[]{60, 120};
|
||||
ArrayList<ArrayList<int[]>> corner_dict = new ArrayList<>();
|
||||
ArrayList<int[]> blueList = new ArrayList<>();
|
||||
ArrayList<int[]> greenList = new ArrayList<>();
|
||||
ArrayList<int[]> blackList = new ArrayList<>();
|
||||
ArrayList<int[]> cyanList = new ArrayList<>();
|
||||
ArrayList<int[]> redList = new ArrayList<>();
|
||||
|
||||
corner_dict.add(blueList);
|
||||
corner_dict.add(greenList);
|
||||
corner_dict.add(blackList);
|
||||
corner_dict.add(cyanList);
|
||||
corner_dict.add(redList);
|
||||
|
||||
NDArray inter_points = manager.zeros(new Shape(0, 2));
|
||||
|
||||
float[] dist_segments_arr = dist_segments.toFloatArray();
|
||||
for (int i = 0; i < inter_pts.getShape().get(0); i++) {
|
||||
for (int j = i + 1; j < inter_pts.getShape().get(1); j++) {
|
||||
// i, j > line index, always i < j
|
||||
int[] point1 = inter_pts.get(i + "," + j + ",:").toIntArray();
|
||||
int x = point1[0];
|
||||
int y = point1[1];
|
||||
float[] point2 = deg_sort.get(i + "," + j + ",:").toFloatArray();
|
||||
float deg1 = point2[0];
|
||||
float deg2 = point2[1];
|
||||
float deg_diff = deg_diff_map.getFloat(i, j);
|
||||
boolean check_degree = false;
|
||||
if (deg_diff > deg_range[0] && deg_diff < deg_range[1]) {
|
||||
check_degree = true;
|
||||
}
|
||||
boolean check_distance = false;
|
||||
|
||||
if (((dist_inter_to_segment1.getFloat(i, j, 1) >= dist_segments_arr[i] &&
|
||||
dist_inter_to_segment1.getFloat(i, j, 0) <= dist_segments_arr[i] * this.outside_ratio) ||
|
||||
(dist_inter_to_segment1.getFloat(i, j, 1) <= dist_segments_arr[i] &&
|
||||
dist_inter_to_segment1.getFloat(i, j, 0) <= dist_segments_arr[i] * this.inside_ratio)) &&
|
||||
((dist_inter_to_segment2.getFloat(i, j, 1) >= dist_segments_arr[j] &&
|
||||
dist_inter_to_segment2.getFloat(i, j, 0) <= dist_segments_arr[j] * this.outside_ratio) ||
|
||||
(dist_inter_to_segment2.getFloat(i, j, 1) <= dist_segments_arr[j] &&
|
||||
dist_inter_to_segment2.getFloat(i, j, 0) <= dist_segments_arr[j] * this.inside_ratio))) {
|
||||
check_distance = true;
|
||||
}
|
||||
|
||||
if (check_degree && check_distance) {
|
||||
int corner_info = 0;
|
||||
if ((deg1 >= 0 && deg1 <= 45 && deg2 >= 45 && deg2 <= 120) ||
|
||||
(deg2 >= 315 && deg1 >= 45 && deg1 <= 120)) {
|
||||
corner_info = 0; // blue
|
||||
} else if (deg1 >= 45 && deg1 <= 125 && deg2 >= 125 && deg2 <= 225) {
|
||||
corner_info = 1; // green
|
||||
} else if (deg1 >= 125 && deg1 <= 225 && deg2 >= 225 && deg2 <= 315) {
|
||||
corner_info = 2; // black
|
||||
} else if ((deg1 >= 0 && deg1 <= 45 && deg2 >= 225 && deg2 <= 315) ||
|
||||
(deg2 >= 315 && deg1 >= 225 && deg1 <= 315)) {
|
||||
corner_info = 3; // cyan
|
||||
} else {
|
||||
corner_info = 4; // red - we don't use it
|
||||
continue;
|
||||
}
|
||||
corner_dict.get(corner_info).add(new int[]{x, y, i, j});
|
||||
inter_points = inter_points.concat(manager.create(new int[]{x, y}).reshape(1, 2));
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
NDArray square_list = manager.zeros(new Shape(0, 8));
|
||||
NDArray connect_list = manager.zeros(new Shape(0, 4));
|
||||
NDArray segment_list = manager.zeros(new Shape(0, 8));
|
||||
|
||||
int corner0_line = 0;
|
||||
int corner1_line = 0;
|
||||
int corner2_line = 0;
|
||||
int corner3_line = 0;
|
||||
for (int[] corner0 : corner_dict.get(0)) {
|
||||
for (int[] corner1 : corner_dict.get(1)) {
|
||||
boolean connect01 = false;
|
||||
for (int i = 0; i < 2; i++) {
|
||||
corner0_line = corner0[2 + i];
|
||||
for (int j = 0; j < 2; j++) {
|
||||
if (corner0_line == corner1[2 + j]) {
|
||||
connect01 = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (connect01) {
|
||||
for (int[] corner2 : corner_dict.get(2)) {
|
||||
boolean connect12 = false;
|
||||
for (int i = 0; i < 2; i++) {
|
||||
corner1_line = corner1[2 + i];
|
||||
for (int j = 0; j < 2; j++) {
|
||||
if (corner1_line == corner2[2 + j]) {
|
||||
connect12 = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (connect12) {
|
||||
for (int[] corner3 : corner_dict.get(3)) {
|
||||
boolean connect23 = false;
|
||||
for (int i = 0; i < 2; i++) {
|
||||
corner2_line = corner1[2 + i];
|
||||
for (int j = 0; j < 2; j++) {
|
||||
if (corner2_line == corner2[2 + j]) {
|
||||
connect23 = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (connect23) {
|
||||
for (int i = 0; i < 2; i++) {
|
||||
corner3_line = corner3[2 + i];
|
||||
for (int j = 0; j < 2; j++) {
|
||||
if (corner3_line == corner0[2 + j]) {
|
||||
square_list = square_list.concat(manager.create(new int[]{corner0[0], corner0[1], corner1[0], corner1[1], corner2[0], corner2[1], corner3[0], corner3[1]}).reshape(1, 8));
|
||||
connect_list = connect_list.concat(manager.create(new int[]{corner0_line, corner1_line, corner2_line, corner3_line}).reshape(1, 4));
|
||||
segment_list = segment_list.concat(manager.create(new int[]{corner0[2], corner0[3], corner1[2], corner1[3], corner2[2], corner2[3], corner3[2], corner3[3]}).reshape(1, 8));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
float map_size = (int) imgArray.getShape().get(0) / 2;
|
||||
NDArray squares = square_list.reshape(-1, 4, 2);
|
||||
NDArray score_array = null;
|
||||
NDArray connect_array = connect_list;
|
||||
NDArray segments_array = segment_list.reshape(-1, 4, 2);
|
||||
//get degree of corners:
|
||||
|
||||
NDArray squares_rollup = squares.duplicate();
|
||||
NDArray last = squares.get(":," + (squares.size(1) - 1) + ",:");
|
||||
for (int i = ((int) squares.size(1) - 1); i > 0; i--) {
|
||||
squares_rollup.set(new NDIndex(":," + i + ",:"), squares.get(":," + (i - 1) + ",:"));
|
||||
}
|
||||
squares_rollup.set(new NDIndex(":,0,:"), last);
|
||||
|
||||
NDArray squares_rolldown = manager.zeros(squares.getShape());
|
||||
NDArray first = squares.get(":,0,:");
|
||||
for (int i = 0; i < squares.size(1) - 1; i++) {
|
||||
squares_rolldown.set(new NDIndex(":," + i + ",:"), squares.get(":," + (i + 1) + ",:"));
|
||||
}
|
||||
squares_rolldown.set(new NDIndex(":," + (squares.size(1) - 1) + ",:"), first);
|
||||
|
||||
NDArray vec1 = squares_rollup.sub(squares);
|
||||
NDArray normalized_vec1 = vec1.div(vec1.norm(new int[]{-1}, true).add(Math.exp(-10)));
|
||||
|
||||
NDArray vec2 = squares_rolldown.sub(squares);
|
||||
NDArray normalized_vec2 = vec2.div(vec2.norm(new int[]{-1}, true).add(Math.exp(-10)));
|
||||
|
||||
NDArray inner_products = normalized_vec1.mul(normalized_vec2).sum(new int[]{-1});
|
||||
|
||||
NDArray squares_degree = inner_products.acos().mul(180).div(Math.PI);
|
||||
|
||||
NDArray overlap_scores = null;
|
||||
NDArray degree_scores = null;
|
||||
NDArray length_scores = null;
|
||||
|
||||
for (int i = 0; i < connect_array.size(0); i++) {
|
||||
NDArray connects = connect_array.get(i);
|
||||
segments = segments_array.get(i);
|
||||
NDArray square = squares.get(i);
|
||||
NDArray degree = squares_degree.get(i);
|
||||
|
||||
// ###################################### OVERLAP SCORES
|
||||
float cover = 0;
|
||||
float perimeter = 0;
|
||||
// check 0 > 1 > 2 > 3
|
||||
float[] square_length = new float[4];
|
||||
|
||||
for (int start_idx = 0; start_idx < 4; start_idx++) {
|
||||
int end_idx = (start_idx + 1) % 4;
|
||||
int connect_idx = (int) connects.get(start_idx).toFloatArray()[0];
|
||||
NDArray start_segments = segments.get(start_idx);
|
||||
NDArray end_segments = segments.get(end_idx);
|
||||
|
||||
// check whether outside or inside
|
||||
int idx_i = (int) start_segments.toFloatArray()[0];
|
||||
int idx_j = (int) start_segments.toFloatArray()[1];
|
||||
NDArray check_dist_mat;
|
||||
if (connect_idx == idx_i) {
|
||||
check_dist_mat = dist_inter_to_segment1;
|
||||
} else {
|
||||
check_dist_mat = dist_inter_to_segment2;
|
||||
}
|
||||
float[] range = check_dist_mat.get(idx_i + "," + idx_j + ",:").toFloatArray();
|
||||
float min_dist = range[0];
|
||||
float max_dist = range[1];
|
||||
float connect_dist = dist_segments.get(connect_idx).toFloatArray()[0];
|
||||
String start_position;
|
||||
float start_min;
|
||||
int start_cover_param;
|
||||
int start_peri_param;
|
||||
if (max_dist > connect_dist) {
|
||||
start_position = "outside";
|
||||
start_min = min_dist;
|
||||
start_cover_param = 0;
|
||||
start_peri_param = 1;
|
||||
} else {
|
||||
start_position = "inside";
|
||||
start_min = min_dist;
|
||||
start_cover_param = -1;
|
||||
start_peri_param = -1;
|
||||
}
|
||||
|
||||
// check whether outside or inside
|
||||
idx_i = (int) end_segments.toFloatArray()[0];
|
||||
idx_j = (int) end_segments.toFloatArray()[1];
|
||||
if (connect_idx == idx_i) {
|
||||
check_dist_mat = dist_inter_to_segment1;
|
||||
} else {
|
||||
check_dist_mat = dist_inter_to_segment2;
|
||||
}
|
||||
range = check_dist_mat.get(idx_i + "," + idx_j + ",:").toFloatArray();
|
||||
min_dist = range[0];
|
||||
max_dist = range[1];
|
||||
connect_dist = dist_segments.get(connect_idx).toFloatArray()[0];
|
||||
String end_position;
|
||||
float end_min;
|
||||
int end_cover_param;
|
||||
int end_peri_param;
|
||||
if (max_dist > connect_dist) {
|
||||
end_position = "outside";
|
||||
end_min = min_dist;
|
||||
end_cover_param = 0;
|
||||
end_peri_param = 1;
|
||||
} else {
|
||||
end_position = "inside";
|
||||
end_min = min_dist;
|
||||
end_cover_param = -1;
|
||||
end_peri_param = -1;
|
||||
}
|
||||
|
||||
cover += connect_dist + start_cover_param * start_min + end_cover_param * end_min;
|
||||
perimeter += connect_dist + start_peri_param * start_min + end_peri_param * end_min;
|
||||
|
||||
square_length[start_idx] = connect_dist + start_peri_param * start_min + end_peri_param * end_min;
|
||||
}
|
||||
if (overlap_scores == null) {
|
||||
overlap_scores = manager.create(cover / perimeter).reshape(1);
|
||||
} else {
|
||||
overlap_scores = overlap_scores.concat(manager.create(cover / perimeter).reshape(1));
|
||||
}
|
||||
|
||||
// ######################################
|
||||
// ###################################### DEGREE SCORES
|
||||
float[] degreeArr = degree.toFloatArray();
|
||||
float deg0 = degreeArr[0];
|
||||
float deg1 = degreeArr[1];
|
||||
float deg2 = degreeArr[2];
|
||||
float deg3 = degreeArr[3];
|
||||
float deg_ratio1 = deg0 / deg2;
|
||||
if (deg_ratio1 > 1.0) {
|
||||
deg_ratio1 = 1 / deg_ratio1;
|
||||
}
|
||||
float deg_ratio2 = deg1 / deg3;
|
||||
if (deg_ratio2 > 1.0) {
|
||||
deg_ratio2 = 1 / deg_ratio2;
|
||||
}
|
||||
if (degree_scores == null) {
|
||||
degree_scores = manager.create((deg_ratio1 + deg_ratio2) / 2).reshape(1);
|
||||
} else {
|
||||
degree_scores = degree_scores.concat(manager.create((deg_ratio1 + deg_ratio2) / 2).reshape(1));
|
||||
}
|
||||
|
||||
// ######################################
|
||||
// ###################################### LENGTH SCORES
|
||||
float len0 = square_length[0];
|
||||
float len1 = square_length[1];
|
||||
float len2 = square_length[2];
|
||||
float len3 = square_length[3];
|
||||
float len_ratio1 = 0;
|
||||
if (len2 > len0) {
|
||||
len_ratio1 = len0 / len2;
|
||||
} else {
|
||||
len_ratio1 = len2 / len0;
|
||||
}
|
||||
float len_ratio2 = 0;
|
||||
if (len3 > len1) {
|
||||
len_ratio2 = len1 / len3;
|
||||
} else {
|
||||
len_ratio2 = len3 / len1;
|
||||
}
|
||||
if (length_scores == null) {
|
||||
length_scores = manager.create((len_ratio1 + len_ratio2) / 2).reshape(1);
|
||||
} else {
|
||||
length_scores = length_scores.concat(manager.create((len_ratio1 + len_ratio2) / 2).reshape(1));
|
||||
}
|
||||
}
|
||||
if (overlap_scores != null)
|
||||
overlap_scores = overlap_scores.div(overlap_scores.max().toFloatArray()[0]);
|
||||
|
||||
// ###################################### AREA SCORES
|
||||
NDArray area_scores = squares.reshape(new Shape(-1, 4, 2));
|
||||
NDArray area_x = area_scores.get(":, :, 0");
|
||||
NDArray area_y = area_scores.get(":, :, 1");
|
||||
NDArray correction = area_x.get(":, -1").mul(area_y.get(":, 0")).sub(area_y.get(":, -1").mul(area_x.get(":, 0")));
|
||||
|
||||
NDArray area_scores1 = area_x.get(":, :-1").mul(area_y.get(":, 1:")).sum(new int[]{-1});
|
||||
NDArray area_scores2 = area_y.get(":, :-1").mul(area_x.get(":, 1:")).sum(new int[]{-1});
|
||||
|
||||
area_scores = area_scores1.sub(area_scores2);
|
||||
area_scores = area_scores.add(correction).abs().mul(0.5);
|
||||
area_scores = area_scores.div(map_size * map_size);
|
||||
|
||||
// ###################################### CENTER SCORES
|
||||
NDArray centers = manager.create(new float[]{256 / 2, 256 / 2});
|
||||
NDArray square_centers = squares.mean(new int[]{1});
|
||||
NDArray center2center = centers.sub(square_centers).square().sum().sqrt();
|
||||
NDArray center_scores = center2center.div(map_size / Math.sqrt(2.0));
|
||||
|
||||
if (overlap_scores != null) {
|
||||
score_array = overlap_scores.mul(this.w_overlap).add(degree_scores.mul(this.w_degree)).add(area_scores.mul(this.w_area)).add(center_scores.mul(this.w_center)).add(length_scores.mul(this.w_length));
|
||||
NDArray sorted_idx = score_array.argSort(0, false);
|
||||
score_array = score_array.get(sorted_idx);
|
||||
squares = squares.get(sorted_idx);
|
||||
}
|
||||
|
||||
try {
|
||||
new_segments.get(":, 0").muli(2);
|
||||
new_segments.get(":, 1").muli(2);
|
||||
new_segments.get(":, 2").muli(2);
|
||||
new_segments.get(":, 3").muli(2);
|
||||
} catch (Exception e) {
|
||||
new_segments = null;
|
||||
}
|
||||
|
||||
try {
|
||||
squares.get(":, :, 0").muli(2).divi(input_shape[1]).muli(original_shape[1]);
|
||||
squares.get(":, :, 1").muli(2).divi(input_shape[0]).muli(original_shape[0]);
|
||||
} catch (Exception e) {
|
||||
squares = null;
|
||||
score_array = null;
|
||||
}
|
||||
|
||||
try {
|
||||
inter_points.get(":, 0").muli(2);
|
||||
inter_points.get(":, 1").muli(2);
|
||||
} catch (Exception e) {
|
||||
inter_points = null;
|
||||
}
|
||||
|
||||
Image img = ImageFactory.getInstance().fromNDArray(imgArray);
|
||||
Mat mat = (Mat) img.getWrappedImage();
|
||||
|
||||
if(squares.getShape().get(0) == 0)
|
||||
return null;
|
||||
NDArray maxSquare = squares.get(0);
|
||||
float[] points = maxSquare.toFloatArray();
|
||||
int[] wh = OpenCVUtils.imgCrop(points);
|
||||
|
||||
Mat dst = OpenCVUtils.perspectiveTransform(mat, points);
|
||||
|
||||
img = ImageFactory.getInstance().fromImage(dst);
|
||||
// return img;
|
||||
return img.getSubImage(0,0,wh[0],wh[1]);
|
||||
}
|
||||
}
|
||||
|
||||
private int[] resize64(double h, double w, double resolution) {
|
||||
|
||||
double k = resolution / Math.min(h, w);
|
||||
h *= k;
|
||||
w *= k;
|
||||
|
||||
int height = (int) (Math.round(h / 64.0)) * 64;
|
||||
int width = (int) (Math.round(w / 64.0)) * 64;
|
||||
|
||||
return new int[]{height, width};
|
||||
}
|
||||
|
||||
@Override
|
||||
public Batchifier getBatchifier() {
|
||||
return batchifier;
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,292 @@
|
||||
package top.aias.iocr.model;
|
||||
|
||||
import ai.djl.MalformedModelException;
|
||||
import ai.djl.inference.Predictor;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.output.BoundingBox;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
import ai.djl.modality.cv.output.Rectangle;
|
||||
import ai.djl.modality.cv.util.NDImageUtils;
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.opencv.OpenCVImageFactory;
|
||||
import ai.djl.repository.zoo.Criteria;
|
||||
import ai.djl.repository.zoo.ModelNotFoundException;
|
||||
import ai.djl.repository.zoo.ModelZoo;
|
||||
import ai.djl.repository.zoo.ZooModel;
|
||||
import ai.djl.training.util.ProgressBar;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import top.aias.iocr.bean.Point;
|
||||
import top.aias.iocr.bean.RotatedBox;
|
||||
import top.aias.iocr.model.pool.DetectorPool;
|
||||
import top.aias.iocr.model.pool.HorizontalDetectorPool;
|
||||
import top.aias.iocr.model.pool.RecognizerPool;
|
||||
import top.aias.iocr.translator.OCRDetectionTranslator;
|
||||
import top.aias.iocr.translator.PpWordDetectionTranslator;
|
||||
import top.aias.iocr.translator.PpWordRecognitionTranslator;
|
||||
import top.aias.iocr.utils.OpenCVUtils;
|
||||
import org.opencv.core.Mat;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.nio.file.Paths;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.concurrent.ConcurrentHashMap;
|
||||
|
||||
/**
|
||||
* 文字识别模型
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public final class RecognitionModel implements AutoCloseable {
|
||||
private ZooModel<Image, DetectedObjects> horizontalDetectionModel;
|
||||
private ZooModel<Image, NDList> detectionModel;
|
||||
private ZooModel<Image, String> recognitionModel;
|
||||
|
||||
private DetectorPool detectorPool;
|
||||
private HorizontalDetectorPool horizontalDetectorPool;
|
||||
private RecognizerPool recognizerPool;
|
||||
|
||||
public void init(String detModel, String recModel, int poolSize) throws MalformedModelException, ModelNotFoundException, IOException {
|
||||
this.recognitionModel = ModelZoo.loadModel(recognizeCriteria(recModel));
|
||||
this.detectionModel = ModelZoo.loadModel(detectCriteria(detModel));
|
||||
this.horizontalDetectionModel = ModelZoo.loadModel(horizontalCriteria(detModel));
|
||||
|
||||
this.detectorPool = new DetectorPool(poolSize, detectionModel);
|
||||
this.horizontalDetectorPool = new HorizontalDetectorPool(poolSize, horizontalDetectionModel);
|
||||
this.recognizerPool = new RecognizerPool(poolSize, recognitionModel);
|
||||
|
||||
}
|
||||
/**
|
||||
* 释放资源
|
||||
*/
|
||||
public void close() {
|
||||
this.recognitionModel.close();
|
||||
this.detectionModel.close();
|
||||
this.horizontalDetectionModel.close();
|
||||
this.detectorPool.close();
|
||||
this.horizontalDetectorPool.close();
|
||||
this.recognizerPool.close();
|
||||
}
|
||||
|
||||
/**
|
||||
* 文本检测（支持有倾斜角的文本）
|
||||
*
|
||||
* @return
|
||||
*/
|
||||
private Criteria<Image, NDList> detectCriteria(String detUri) {
|
||||
Criteria<Image, NDList> criteria =
|
||||
Criteria.builder()
|
||||
.optEngine("OnnxRuntime")
|
||||
.optModelName("inference")
|
||||
.setTypes(Image.class, NDList.class)
|
||||
.optModelPath(Paths.get(detUri))
|
||||
// .optModelUrls(detUri)
|
||||
.optTranslator(new OCRDetectionTranslator(new ConcurrentHashMap<String, String>()))
|
||||
.optProgress(new ProgressBar())
|
||||
.build();
|
||||
|
||||
return criteria;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* 水平文本检测
|
||||
*
|
||||
* @return
|
||||
*/
|
||||
private Criteria<Image, DetectedObjects> horizontalCriteria(String detUri) {
|
||||
Criteria<Image, DetectedObjects> criteria =
|
||||
Criteria.builder()
|
||||
.optEngine("OnnxRuntime")
|
||||
.optModelName("inference")
|
||||
.setTypes(Image.class, DetectedObjects.class)
|
||||
.optModelPath(Paths.get(detUri))
|
||||
// .optModelUrls(detUri)
|
||||
.optTranslator(new PpWordDetectionTranslator(new ConcurrentHashMap<String, String>()))
|
||||
.optProgress(new ProgressBar())
|
||||
.build();
|
||||
|
||||
return criteria;
|
||||
}
|
||||
|
||||
/**
|
||||
* 文本识别
|
||||
*
|
||||
* @return
|
||||
*/
|
||||
private Criteria<Image, String> recognizeCriteria(String recUri) {
|
||||
Criteria<Image, String> criteria =
|
||||
Criteria.builder()
|
||||
.optEngine("OnnxRuntime")
|
||||
.optModelName("inference")
|
||||
.setTypes(Image.class, String.class)
|
||||
.optModelPath(Paths.get(recUri))
|
||||
// .optModelUrls(recUri)
|
||||
.optProgress(new ProgressBar())
|
||||
.optTranslator(new PpWordRecognitionTranslator((new ConcurrentHashMap<String, String>())))
|
||||
.build();
|
||||
|
||||
return criteria;
|
||||
}
|
||||
|
||||
// 多线程环境，每个线程一个predictor，共享一个model, 资源池（CPU Core 核心数）达到上限则等待
|
||||
public String predictSingleLineText(Image image)
|
||||
throws TranslateException {
|
||||
Predictor<Image, String> recognizer = recognizerPool.getRecognizer();
|
||||
String text = recognizer.predict(image);
|
||||
// 释放资源
|
||||
recognizerPool.releaseRecognizer(recognizer);
|
||||
return text;
|
||||
}
|
||||
|
||||
// 多线程环境，每个线程一个predictor，共享一个model, 资源池（CPU Core 核心数）达到上限则等待
|
||||
public DetectedObjects predict(Image image)
|
||||
throws TranslateException {
|
||||
Predictor<Image, DetectedObjects> horizontalDetector = horizontalDetectorPool.getDetector();
|
||||
DetectedObjects detections = horizontalDetector.predict(image);
|
||||
horizontalDetectorPool.releaseDetector(horizontalDetector);
|
||||
|
||||
List<DetectedObjects.DetectedObject> boxes = detections.items();
|
||||
List<String> names = new ArrayList<>();
|
||||
List<Double> prob = new ArrayList<>();
|
||||
List<BoundingBox> rect = new ArrayList<>();
|
||||
|
||||
Predictor<Image, String> recognizer = recognizerPool.getRecognizer();
|
||||
for (int i = 0; i < boxes.size(); i++) {
|
||||
Image subImg = getSubImage(image, boxes.get(i).getBoundingBox());
|
||||
if (subImg.getHeight() * 1.0 / subImg.getWidth() > 1.5) {
|
||||
subImg = rotateImg(subImg);
|
||||
}
|
||||
String name = recognizer.predict(subImg);
|
||||
System.out.println(name);
|
||||
names.add(name);
|
||||
prob.add(-1.0);
|
||||
rect.add(boxes.get(i).getBoundingBox());
|
||||
}
|
||||
// 释放资源
|
||||
recognizerPool.releaseRecognizer(recognizer);
|
||||
|
||||
DetectedObjects detectedObjects = new DetectedObjects(names, prob, rect);
|
||||
return detectedObjects;
|
||||
}
|
||||
|
||||
// 多线程环境，每个线程一个predictor，共享一个model, 资源池（CPU Core 核心数）达到上限则等待
|
||||
public List<RotatedBox> predict(NDManager manager, Image image)
|
||||
throws TranslateException {
|
||||
|
||||
Predictor<Image, NDList> detector = detectorPool.getDetector();
|
||||
NDList boxes = detector.predict(image);
|
||||
// 释放资源
|
||||
detectorPool.releaseDetector(detector);
|
||||
|
||||
// 交给 NDManager自动管理内存
|
||||
// attach to manager for automatic memory management
|
||||
boxes.attach(manager);
|
||||
|
||||
List<RotatedBox> result = new ArrayList<>();
|
||||
Mat mat = (Mat) image.getWrappedImage();
|
||||
|
||||
Predictor<Image, String> recognizer = recognizerPool.getRecognizer();
|
||||
for (int i = 0; i < boxes.size(); i++) {
|
||||
NDArray box = boxes.get(i);
|
||||
|
||||
float[] pointsArr = box.toFloatArray();
|
||||
float[] lt = java.util.Arrays.copyOfRange(pointsArr, 0, 2);
|
||||
float[] rt = java.util.Arrays.copyOfRange(pointsArr, 2, 4);
|
||||
float[] rb = java.util.Arrays.copyOfRange(pointsArr, 4, 6);
|
||||
float[] lb = java.util.Arrays.copyOfRange(pointsArr, 6, 8);
|
||||
int img_crop_width = (int) Math.max(distance(lt, rt), distance(rb, lb));
|
||||
int img_crop_height = (int) Math.max(distance(lt, lb), distance(rt, rb));
|
||||
List<Point> srcPoints = new ArrayList<>();
|
||||
srcPoints.add(new Point((int) lt[0], (int) lt[1]));
|
||||
srcPoints.add(new Point((int) rt[0], (int) rt[1]));
|
||||
srcPoints.add(new Point((int) rb[0], (int) rb[1]));
|
||||
srcPoints.add(new Point((int) lb[0], (int) lb[1]));
|
||||
List<Point> dstPoints = new ArrayList<>();
|
||||
dstPoints.add(new Point(0, 0));
|
||||
dstPoints.add(new Point(img_crop_width, 0));
|
||||
dstPoints.add(new Point(img_crop_width, img_crop_height));
|
||||
dstPoints.add(new Point(0, img_crop_height));
|
||||
|
||||
Mat srcPoint2f = OpenCVUtils.toMat(srcPoints);
|
||||
Mat dstPoint2f = OpenCVUtils.toMat(dstPoints);
|
||||
|
||||
Mat cvMat = OpenCVUtils.perspectiveTransform(mat, srcPoint2f, dstPoint2f);
|
||||
|
||||
Image subImg = OpenCVImageFactory.getInstance().fromImage(cvMat);
|
||||
// ImageUtils.saveImage(subImg, i + ".png", "build/output");
|
||||
|
||||
subImg = subImg.getSubImage(0, 0, img_crop_width, img_crop_height);
|
||||
if (subImg.getHeight() * 1.0 / subImg.getWidth() > 1.5) {
|
||||
subImg = rotateImg(manager, subImg);
|
||||
}
|
||||
|
||||
String name = recognizer.predict(subImg);
|
||||
RotatedBox rotatedBox = new RotatedBox(box, name);
|
||||
result.add(rotatedBox);
|
||||
|
||||
cvMat.release();
|
||||
srcPoint2f.release();
|
||||
dstPoint2f.release();
|
||||
|
||||
}
|
||||
// 释放资源
|
||||
recognizerPool.releaseRecognizer(recognizer);
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
private Image getSubImage(Image img, BoundingBox box) {
|
||||
Rectangle rect = box.getBounds();
|
||||
double[] extended = extendRect(rect.getX(), rect.getY(), rect.getWidth(), rect.getHeight());
|
||||
int width = img.getWidth();
|
||||
int height = img.getHeight();
|
||||
int[] recovered = {
|
||||
(int) (extended[0] * width),
|
||||
(int) (extended[1] * height),
|
||||
(int) (extended[2] * width),
|
||||
(int) (extended[3] * height)
|
||||
};
|
||||
return img.getSubImage(recovered[0], recovered[1], recovered[2], recovered[3]);
|
||||
}
|
||||
|
||||
private double[] extendRect(double xmin, double ymin, double width, double height) {
|
||||
double centerx = xmin + width / 2;
|
||||
double centery = ymin + height / 2;
|
||||
if (width > height) {
|
||||
width += height * 2.0;
|
||||
height *= 3.0;
|
||||
} else {
|
||||
height += width * 2.0;
|
||||
width *= 3.0;
|
||||
}
|
||||
double newX = centerx - width / 2 < 0 ? 0 : centerx - width / 2;
|
||||
double newY = centery - height / 2 < 0 ? 0 : centery - height / 2;
|
||||
double newWidth = newX + width > 1 ? 1 - newX : width;
|
||||
double newHeight = newY + height > 1 ? 1 - newY : height;
|
||||
return new double[]{newX, newY, newWidth, newHeight};
|
||||
}
|
||||
|
||||
private float distance(float[] point1, float[] point2) {
|
||||
float disX = point1[0] - point2[0];
|
||||
float disY = point1[1] - point2[1];
|
||||
float dis = (float) Math.sqrt(disX * disX + disY * disY);
|
||||
return dis;
|
||||
}
|
||||
|
||||
private Image rotateImg(Image image) {
|
||||
try (NDManager manager = NDManager.newBaseManager()) {
|
||||
NDArray rotated = NDImageUtils.rotate90(image.toNDArray(manager), 1);
|
||||
return OpenCVImageFactory.getInstance().fromNDArray(rotated);
|
||||
}
|
||||
}
|
||||
|
||||
private Image rotateImg(NDManager manager, Image image) {
|
||||
NDArray rotated = NDImageUtils.rotate90(image.toNDArray(manager), 1);
|
||||
return OpenCVImageFactory.getInstance().fromNDArray(rotated);
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,55 @@
|
||||
package top.aias.iocr.model.pool;// 导入需要的包
|
||||
|
||||
import ai.djl.inference.Predictor;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.repository.zoo.ZooModel;
|
||||
|
||||
import java.util.ArrayList;
|
||||
/**
|
||||
* 文字检测连接池
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class DetectorPool {
|
||||
private int poolSize;
|
||||
private ZooModel<Image, NDList> detectionModel;
|
||||
private ArrayList<Predictor<Image, NDList>> detectorList = new ArrayList<>();
|
||||
|
||||
|
||||
public DetectorPool(int poolSize, ZooModel<Image, NDList> detectionModel) {
|
||||
this.poolSize = poolSize;
|
||||
this.detectionModel = detectionModel;
|
||||
|
||||
for (int i = 0; i < poolSize; i++) {
|
||||
Predictor<Image, NDList> detector = detectionModel.newPredictor();
|
||||
detectorList.add(detector);
|
||||
}
|
||||
}
|
||||
|
||||
public synchronized Predictor<Image, NDList> getDetector() {
|
||||
while (detectorList.isEmpty()) {
|
||||
try {
|
||||
wait();
|
||||
} catch (InterruptedException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
Predictor<Image, NDList> detector = detectorList.remove(0);
|
||||
return detector;
|
||||
}
|
||||
|
||||
public synchronized void releaseDetector(Predictor<Image, NDList> detector) {
|
||||
detectorList.add(detector);
|
||||
notifyAll();
|
||||
}
|
||||
|
||||
public void close() {
|
||||
for (Predictor<Image, NDList> detector : detectorList) {
|
||||
detector.close();
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,55 @@
|
||||
package top.aias.iocr.model.pool;// 导入需要的包
|
||||
|
||||
import ai.djl.inference.Predictor;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
import ai.djl.repository.zoo.ZooModel;
|
||||
|
||||
import java.util.ArrayList;
|
||||
/**
|
||||
* 水平文字检测连接池
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class HorizontalDetectorPool {
|
||||
private int poolSize;
|
||||
private ZooModel<Image, DetectedObjects> detectionModel;
|
||||
private ArrayList<Predictor<Image, DetectedObjects>> detectorList = new ArrayList<>();
|
||||
|
||||
|
||||
public HorizontalDetectorPool(int poolSize, ZooModel<Image, DetectedObjects> detectionModel) {
|
||||
this.poolSize = poolSize;
|
||||
this.detectionModel = detectionModel;
|
||||
|
||||
for (int i = 0; i < poolSize; i++) {
|
||||
Predictor<Image, DetectedObjects> detector = detectionModel.newPredictor();
|
||||
detectorList.add(detector);
|
||||
}
|
||||
}
|
||||
|
||||
public synchronized Predictor<Image, DetectedObjects> getDetector(){
|
||||
while (detectorList.isEmpty()) {
|
||||
try {
|
||||
wait();
|
||||
} catch (InterruptedException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
Predictor<Image, DetectedObjects> detector = detectorList.remove(0);
|
||||
return detector;
|
||||
}
|
||||
|
||||
public synchronized void releaseDetector(Predictor<Image, DetectedObjects> detector) {
|
||||
detectorList.add(detector);
|
||||
notifyAll();
|
||||
}
|
||||
|
||||
public void close() {
|
||||
for (Predictor<Image, DetectedObjects> detector : detectorList) {
|
||||
detector.close();
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,55 @@
|
||||
package top.aias.iocr.model.pool;// 导入需要的包
|
||||
|
||||
import ai.djl.inference.Predictor;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
import ai.djl.repository.zoo.ZooModel;
|
||||
|
||||
import java.util.ArrayList;
|
||||
/**
|
||||
* 文本转正连接池
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class MlsdPool {
|
||||
private int poolSize;
|
||||
private ZooModel<Image, Image> model;
|
||||
private ArrayList<Predictor<Image, Image>> predictorList = new ArrayList<>();
|
||||
|
||||
|
||||
public MlsdPool(int poolSize, ZooModel<Image, Image> model) {
|
||||
this.poolSize = poolSize;
|
||||
this.model = model;
|
||||
|
||||
for (int i = 0; i < poolSize; i++) {
|
||||
Predictor<Image, Image> predictor = model.newPredictor();
|
||||
predictorList.add(predictor);
|
||||
}
|
||||
}
|
||||
|
||||
public synchronized Predictor<Image, Image> getPredictor() {
|
||||
while (predictorList.isEmpty()) {
|
||||
try {
|
||||
wait();
|
||||
} catch (InterruptedException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
Predictor<Image, Image> predictor = predictorList.remove(0);
|
||||
return predictor;
|
||||
}
|
||||
|
||||
public synchronized void releasePredictor(Predictor<Image, Image> predictor) {
|
||||
predictorList.add(predictor);
|
||||
notifyAll();
|
||||
}
|
||||
|
||||
public void close() {
|
||||
for (Predictor<Image, Image> predictor : predictorList) {
|
||||
predictor.close();
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,54 @@
|
||||
package top.aias.iocr.model.pool;// 导入需要的包
|
||||
|
||||
import ai.djl.inference.Predictor;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.repository.zoo.ZooModel;
|
||||
|
||||
import java.util.ArrayList;
|
||||
/**
|
||||
* 文字识别连接池
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class RecognizerPool {
|
||||
private int poolSize;
|
||||
private ZooModel<Image, String> recognitionModel;
|
||||
private ArrayList<Predictor<Image, String>> recognizerList = new ArrayList<>();
|
||||
|
||||
|
||||
public RecognizerPool(int poolSize, ZooModel<Image, String> detectionModel) {
|
||||
this.poolSize = poolSize;
|
||||
this.recognitionModel = detectionModel;
|
||||
|
||||
for (int i = 0; i < poolSize; i++) {
|
||||
Predictor<Image, String> detector = detectionModel.newPredictor();
|
||||
recognizerList.add(detector);
|
||||
}
|
||||
}
|
||||
|
||||
public synchronized Predictor<Image, String> getRecognizer(){
|
||||
while (recognizerList.isEmpty()) {
|
||||
try {
|
||||
wait();
|
||||
} catch (InterruptedException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
Predictor<Image, String> recognizer = recognizerList.remove(0);
|
||||
return recognizer;
|
||||
}
|
||||
|
||||
public synchronized void releaseRecognizer(Predictor<Image, String> recognizer) {
|
||||
recognizerList.add(recognizer);
|
||||
notifyAll();
|
||||
}
|
||||
|
||||
public void close() {
|
||||
for (Predictor<Image, String> detector : recognizerList) {
|
||||
detector.close();
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,20 @@
|
||||
package top.aias.iocr.service;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import top.aias.iocr.bean.RotatedBox;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 文字识别接口
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public interface InferService {
|
||||
List<RotatedBox> getGeneralInfo(NDManager manager, Image image) throws TranslateException;
|
||||
Image getWarpImg(Image image) throws TranslateException;
|
||||
}
|
||||
@ -0,0 +1,44 @@
|
||||
package top.aias.iocr.service;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import top.aias.iocr.bean.LabelBean;
|
||||
import top.aias.iocr.bean.RotatedBox;
|
||||
import top.aias.iocr.bean.TemplateBean;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
/**
|
||||
* 模板识别接口
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public interface TemplateService {
|
||||
// Map<String, String> getMlsdImageInfo(TemplateBean templateBean, Image image) throws TranslateException, IOException;
|
||||
|
||||
List<LabelBean> getImageInfo(TemplateBean templateBean, List<RotatedBox> templateTextsDet);
|
||||
|
||||
Map<String, String> getImageInfo(TemplateBean templateBean, Image image) throws TranslateException, IOException;
|
||||
|
||||
List<TemplateBean> getTemplateList();
|
||||
|
||||
TemplateBean getTemplate(String uid) throws IOException;
|
||||
|
||||
void addTemplate(TemplateBean templateBean) throws IOException;
|
||||
|
||||
void updateTemplate(TemplateBean templateBean) throws IOException;
|
||||
|
||||
TemplateBean getTemplateRecInfo(String uid) throws IOException;
|
||||
|
||||
void updateTemplateRecInfo(TemplateBean templateBean) throws IOException;
|
||||
|
||||
void removeTemplate(String uid) throws IOException;
|
||||
|
||||
String getLabelData(String uid, LabelBean labelData) throws IOException, TranslateException;
|
||||
|
||||
List<LabelBean> getLabelDataByType(List<LabelBean> labelData, String type);
|
||||
}
|
||||
@ -0,0 +1,43 @@
|
||||
package top.aias.iocr.service.impl;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import top.aias.iocr.bean.RotatedBox;
|
||||
import top.aias.iocr.model.MlsdSquareModel;
|
||||
import top.aias.iocr.model.RecognitionModel;
|
||||
import top.aias.iocr.service.InferService;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 文字识别服务
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Service
|
||||
public class InferServiceImpl implements InferService {
|
||||
private Logger logger = LoggerFactory.getLogger(InferServiceImpl.class);
|
||||
|
||||
@Autowired
|
||||
private RecognitionModel recognitionModel;
|
||||
|
||||
@Autowired
|
||||
private MlsdSquareModel mlsdSquareModel;
|
||||
|
||||
public List<RotatedBox> getGeneralInfo(NDManager manager, Image image) throws TranslateException {
|
||||
List<RotatedBox> detectedObjects = recognitionModel.predict(manager, image);
|
||||
return detectedObjects;
|
||||
}
|
||||
|
||||
public Image getWarpImg(Image image) throws TranslateException {
|
||||
Image cropImg = mlsdSquareModel.predict(image);
|
||||
return cropImg;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,298 @@
|
||||
package top.aias.iocr.service.impl;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.opencv.OpenCVImageFactory;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import com.google.gson.Gson;
|
||||
import com.google.gson.GsonBuilder;
|
||||
import com.google.gson.reflect.TypeToken;
|
||||
import top.aias.iocr.bean.LabelBean;
|
||||
import top.aias.iocr.bean.Point;
|
||||
import top.aias.iocr.bean.RotatedBox;
|
||||
import top.aias.iocr.bean.TemplateBean;
|
||||
import top.aias.iocr.configuration.FileProperties;
|
||||
import top.aias.iocr.model.RecognitionModel;
|
||||
import top.aias.iocr.service.TemplateService;
|
||||
import top.aias.iocr.utils.FileUtils;
|
||||
import top.aias.iocr.utils.PerspectiveTransform;
|
||||
import top.aias.iocr.utils.PointUtils;
|
||||
import org.apache.commons.lang3.StringUtils;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import org.springframework.beans.BeanUtils;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.nio.file.Path;
|
||||
import java.nio.file.Paths;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
/**
|
||||
* 模板识别服务
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
@Service
|
||||
public class TemplateServiceImpl implements TemplateService {
|
||||
private static final String TEMPLATE_LIST_FILE = "templates.json";
|
||||
private Logger logger = LoggerFactory.getLogger(TemplateServiceImpl.class);
|
||||
|
||||
/**
|
||||
* file configuration
|
||||
*/
|
||||
@Autowired
|
||||
private FileProperties properties;
|
||||
|
||||
/**
|
||||
* ocr recognition model
|
||||
*/
|
||||
@Autowired
|
||||
private RecognitionModel recognitionModel;
|
||||
|
||||
@Value("${image.debug}")
|
||||
private boolean debug;
|
||||
|
||||
@Value("${distance.type}")
|
||||
private String distanceType;
|
||||
|
||||
@Value("${image.maxNum}")
|
||||
private int maxNum;
|
||||
@Value("${image.disThreshold}")
|
||||
private double disThreshold;
|
||||
|
||||
public Map<String, String> getImageInfo(TemplateBean templateBean, Image image) throws TranslateException, IOException {
|
||||
List<LabelBean> anchorlabels = getLabelDataByType(templateBean.getLabelData(), "anchor");
|
||||
List<LabelBean> contentLabels = getLabelDataByType(templateBean.getLabelData(), "rectangle");
|
||||
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String fileRelativePath = path.getPath().replace("\\", "/");
|
||||
Path imageFile = Paths.get(fileRelativePath + "images/" + templateBean.getImageName());
|
||||
// BufferedImage templateImg = ImageIO.read(new File(fileRelativePath + "images/" + templateBean.getImageName()));
|
||||
Image templateImg = OpenCVImageFactory.getInstance().fromFile(imageFile);
|
||||
try (NDManager manager = NDManager.newBaseManager()) {
|
||||
Map<String, String> hashMap = PerspectiveTransform.recognize(manager, templateImg, recognitionModel, image, anchorlabels, contentLabels, fileRelativePath, distanceType, maxNum, disThreshold, debug);
|
||||
return hashMap;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 将参考框的坐标替换为对应自动检测框的坐标
|
||||
* @param templateBean
|
||||
* @param templateTextsDet
|
||||
* @return
|
||||
*/
|
||||
public List<LabelBean> getImageInfo(TemplateBean templateBean, List<RotatedBox> templateTextsDet) {
|
||||
List<LabelBean> labels = templateBean.getLabelData();
|
||||
|
||||
// 模版文本检测 1
|
||||
// Text detection area
|
||||
for (RotatedBox rotatedBox : templateTextsDet) {
|
||||
List<Point> points = new ArrayList<>();
|
||||
float[] pointsArr = rotatedBox.getBox().toFloatArray();
|
||||
for (int i = 0; i < 4; i++) {
|
||||
Point point = new Point((int) pointsArr[2 * i], (int) pointsArr[2 * i + 1]);
|
||||
points.add(point);
|
||||
}
|
||||
|
||||
String detectedText = rotatedBox.getText();
|
||||
|
||||
// 替换对应检测框的坐标
|
||||
for (int j = 0; j < labels.size(); j++) {
|
||||
String labelText = labels.get(j).getValue();
|
||||
if (detectedText.equals(labelText)) {
|
||||
labels.get(j).setPoints(points);
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
return labels;
|
||||
}
|
||||
|
||||
public List<TemplateBean> getTemplateList() {
|
||||
List<TemplateBean> templateList = null;
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String fileRelativePath = path.getPath().replace("\\", "/");
|
||||
String json = null;
|
||||
try {
|
||||
json = FileUtils.readFile(fileRelativePath, TEMPLATE_LIST_FILE);
|
||||
} catch (IOException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
if (!StringUtils.isBlank(json)) {
|
||||
templateList = new Gson().fromJson(json, new TypeToken<List<TemplateBean>>() {
|
||||
}.getType());
|
||||
} else {
|
||||
templateList = new ArrayList<>();
|
||||
}
|
||||
return templateList;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取模板信息
|
||||
* Get Template
|
||||
*
|
||||
* @param uid
|
||||
*/
|
||||
public TemplateBean getTemplate(String uid) throws IOException {
|
||||
TemplateBean template = null;
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String fileRelativePath = path.getPath().replace("\\", "/") + "templates/";
|
||||
String json = FileUtils.readFile(fileRelativePath, uid + ".json");
|
||||
if (!StringUtils.isBlank(json)) {
|
||||
template = new Gson().fromJson(json, new TypeToken<TemplateBean>() {
|
||||
}.getType());
|
||||
}
|
||||
return template;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取模板图片检测信息
|
||||
* Get Template Recognition Info
|
||||
*
|
||||
* @param uid
|
||||
*/
|
||||
public TemplateBean getTemplateRecInfo(String uid) throws IOException {
|
||||
TemplateBean template = null;
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String fileRelativePath = path.getPath().replace("\\", "/") + "templates/recinfo/";
|
||||
String json = FileUtils.readFile(fileRelativePath, uid + ".json");
|
||||
if (!StringUtils.isBlank(json)) {
|
||||
template = new Gson().fromJson(json, new TypeToken<TemplateBean>() {
|
||||
}.getType());
|
||||
}
|
||||
return template;
|
||||
}
|
||||
|
||||
/**
|
||||
* 新增模板
|
||||
* Add Template
|
||||
*
|
||||
* @param templateBean
|
||||
*/
|
||||
public synchronized void addTemplate(TemplateBean templateBean) throws IOException {
|
||||
List<TemplateBean> templateList = getTemplateList();
|
||||
templateBean.setLabelData(null);
|
||||
templateList.add(templateBean);
|
||||
Gson gson = new GsonBuilder().setPrettyPrinting().create();
|
||||
String json = gson.toJson(templateList);
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
// 保存模版列表数据
|
||||
// Save template list data
|
||||
String fileRelativePath = path.getPath().replace("\\", "/");
|
||||
FileUtils.saveFile(fileRelativePath, TEMPLATE_LIST_FILE, json);
|
||||
// 保存模版数据
|
||||
// Save template data
|
||||
json = gson.toJson(templateBean);
|
||||
FileUtils.saveFile(fileRelativePath + "templates/", templateBean.getUid() + ".json", json);
|
||||
}
|
||||
|
||||
/**
|
||||
* 更新模板
|
||||
* Update Template
|
||||
*
|
||||
* @param templateBean
|
||||
*/
|
||||
public synchronized void updateTemplate(TemplateBean templateBean) throws IOException {
|
||||
List<TemplateBean> templateList = getTemplateList();
|
||||
for (TemplateBean item : templateList) {
|
||||
if (item.getUid().equals(templateBean.getUid())) {
|
||||
BeanUtils.copyProperties(templateBean, item);
|
||||
item.setLabelData(null);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
Gson gson = new GsonBuilder().setPrettyPrinting().create();
|
||||
String json = gson.toJson(templateList);
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
// 保存模版列表数据
|
||||
// Save template list data
|
||||
String fileRelativePath = path.getPath().replace("\\", "/");
|
||||
FileUtils.saveFile(fileRelativePath, TEMPLATE_LIST_FILE, json);
|
||||
// 保存模版数据
|
||||
// Save template data
|
||||
json = gson.toJson(templateBean);
|
||||
FileUtils.saveFile(fileRelativePath + "templates/", templateBean.getUid() + ".json", json);
|
||||
}
|
||||
|
||||
/**
|
||||
* 更新模板自动检测信息
|
||||
* Update Template
|
||||
*
|
||||
* @param templateBean
|
||||
*/
|
||||
public synchronized void updateTemplateRecInfo(TemplateBean templateBean) throws IOException {
|
||||
Gson gson = new GsonBuilder().setPrettyPrinting().create();
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
// 保存模版列表数据
|
||||
// Save template list data
|
||||
String fileRelativePath = path.getPath().replace("\\", "/");
|
||||
// 保存数据
|
||||
// Save data
|
||||
String json = gson.toJson(templateBean);
|
||||
FileUtils.saveFile(fileRelativePath + "templates/recinfo/", templateBean.getUid() + ".json", json);
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除模板
|
||||
* Delete Template
|
||||
*
|
||||
* @param uid
|
||||
*/
|
||||
public synchronized void removeTemplate(String uid) throws IOException {
|
||||
List<TemplateBean> templateList = getTemplateList();
|
||||
for (int i = 0; i < templateList.size(); i++) {
|
||||
if (templateList.get(i).getUid().equals(uid)) {
|
||||
templateList.remove(i);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
Gson gson = new GsonBuilder().setPrettyPrinting().create();
|
||||
String json = gson.toJson(templateList);
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
// 保存模版列表数据
|
||||
// Save template data
|
||||
String fileRelativePath = path.getPath().replace("\\", "/");
|
||||
FileUtils.saveFile(fileRelativePath, TEMPLATE_LIST_FILE, json);
|
||||
// 删除模版数据
|
||||
// Delete template data
|
||||
FileUtils.removeFile(fileRelativePath + "templates/", uid + ".json");
|
||||
}
|
||||
|
||||
|
||||
public String getLabelData(String uid, LabelBean labelData) throws IOException, TranslateException {
|
||||
TemplateBean template = getTemplate(uid);
|
||||
FileProperties.ElPath path = properties.getPath();
|
||||
String fileRelativePath = path.getPath().replace("\\", "/");
|
||||
Path imageFile = Paths.get(fileRelativePath + "images/" + template.getImageName());
|
||||
Image image = OpenCVImageFactory.getInstance().fromFile(imageFile);
|
||||
// int x = labelData.getPoints().get(0).getX();
|
||||
// int y = labelData.getPoints().get(0).getY();
|
||||
// int w = labelData.getPoints().get(1).getX() - labelData.getPoints().get(0).getX();
|
||||
// int h = labelData.getPoints().get(3).getY() - labelData.getPoints().get(0).getY();
|
||||
int[] rect = PointUtils.rectXYWH(labelData.getPoints());
|
||||
Image subImage = image.getSubImage(rect[0], rect[1], rect[2], rect[3]);
|
||||
String result = recognitionModel.predictSingleLineText(subImage);
|
||||
return result;
|
||||
}
|
||||
|
||||
public List<LabelBean> getLabelDataByType(List<LabelBean> labelData, String type) {
|
||||
List<LabelBean> labels = new ArrayList<>();
|
||||
for (int i = 0; i < labelData.size(); i++) {
|
||||
if (labelData.get(i).getType().equals(type)) {
|
||||
labels.add(labelData.get(i));
|
||||
}
|
||||
}
|
||||
return labels;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,520 @@
|
||||
package top.aias.iocr.translator;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.util.NDImageUtils;
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDArrays;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.ndarray.index.NDIndex;
|
||||
import ai.djl.ndarray.types.DataType;
|
||||
import ai.djl.ndarray.types.Shape;
|
||||
import ai.djl.translate.Batchifier;
|
||||
import ai.djl.translate.Translator;
|
||||
import ai.djl.translate.TranslatorContext;
|
||||
import top.aias.iocr.utils.NDArrayUtils;
|
||||
import org.opencv.core.*;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
/**
|
||||
* 文字识别前后处理（支持倾斜文本）
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class OCRDetectionTranslator implements Translator<Image, NDList> {
|
||||
// det_algorithm == "DB"
|
||||
private final float thresh = 0.3f;
|
||||
private final boolean use_dilation = false;
|
||||
private final String score_mode = "fast";
|
||||
private final String box_type = "quad";
|
||||
|
||||
private final int limit_side_len;
|
||||
private final int max_candidates;
|
||||
private final int min_size;
|
||||
private final float box_thresh;
|
||||
private final float unclip_ratio;
|
||||
private float ratio_h;
|
||||
private float ratio_w;
|
||||
private int img_height;
|
||||
private int img_width;
|
||||
|
||||
public OCRDetectionTranslator(Map<String, ?> arguments) {
|
||||
limit_side_len =
|
||||
arguments.containsKey("limit_side_len")
|
||||
? Integer.parseInt(arguments.get("limit_side_len").toString())
|
||||
: 960;
|
||||
max_candidates =
|
||||
arguments.containsKey("max_candidates")
|
||||
? Integer.parseInt(arguments.get("max_candidates").toString())
|
||||
: 1000;
|
||||
min_size =
|
||||
arguments.containsKey("min_size")
|
||||
? Integer.parseInt(arguments.get("min_size").toString())
|
||||
: 3;
|
||||
box_thresh =
|
||||
arguments.containsKey("box_thresh")
|
||||
? Float.parseFloat(arguments.get("box_thresh").toString())
|
||||
: 0.6f; // 0.5f
|
||||
unclip_ratio =
|
||||
arguments.containsKey("unclip_ratio")
|
||||
? Float.parseFloat(arguments.get("unclip_ratio").toString())
|
||||
: 1.6f;
|
||||
}
|
||||
|
||||
@Override
|
||||
public NDList processOutput(TranslatorContext ctx, NDList list) {
|
||||
NDManager manager = ctx.getNDManager();
|
||||
NDArray pred = list.get(0);
|
||||
pred = pred.squeeze();
|
||||
NDArray segmentation = pred.gt(thresh); // thresh=0.3 .mul(255f)
|
||||
|
||||
segmentation = segmentation.toType(DataType.UINT8, true);
|
||||
Shape shape = segmentation.getShape();
|
||||
int rows = (int) shape.get(0);
|
||||
int cols = (int) shape.get(1);
|
||||
|
||||
Mat newMask = new Mat();
|
||||
if (this.use_dilation) {
|
||||
Mat mask = new Mat();
|
||||
//convert from NDArray to Mat
|
||||
Mat srcMat = NDArrayUtils.uint8NDArrayToMat(segmentation);
|
||||
// size 越小，腐蚀的单位越小，图片越接近原图
|
||||
// Mat dilation_kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(2, 2));
|
||||
Mat dilation_kernel = NDArrayUtils.uint8ArrayToMat(new byte[][]{{1, 1}, {1, 1}});
|
||||
/**
|
||||
* 膨胀说明： 图像的一部分区域与指定的核进行卷积， 求核的最`大`值并赋值给指定区域。 膨胀可以理解为图像中`高亮区域`的'领域扩大'。
|
||||
* 意思是高亮部分会侵蚀不是高亮的部分，使高亮部分越来越多。
|
||||
*/
|
||||
Imgproc.dilate(srcMat, mask, dilation_kernel);
|
||||
//destination Matrix
|
||||
Scalar scalar = new Scalar(255);
|
||||
Core.multiply(mask, scalar, newMask);
|
||||
// release Mat
|
||||
mask.release();
|
||||
srcMat.release();
|
||||
dilation_kernel.release();
|
||||
} else {
|
||||
Mat srcMat = NDArrayUtils.uint8NDArrayToMat(segmentation);
|
||||
//destination Matrix
|
||||
Scalar scalar = new Scalar(255);
|
||||
Core.multiply(srcMat, scalar, newMask);
|
||||
// release Mat
|
||||
srcMat.release();
|
||||
}
|
||||
|
||||
NDArray boxes = boxes_from_bitmap(manager, pred, newMask);
|
||||
|
||||
//boxes[:, :, 0] = boxes[:, :, 0] / ratio_w
|
||||
NDArray boxes1 = boxes.get(":, :, 0").div(ratio_w);
|
||||
boxes.set(new NDIndex(":, :, 0"), boxes1);
|
||||
//boxes[:, :, 1] = boxes[:, :, 1] / ratio_h
|
||||
NDArray boxes2 = boxes.get(":, :, 1").div(ratio_h);
|
||||
boxes.set(new NDIndex(":, :, 1"), boxes2);
|
||||
|
||||
NDList dt_boxes = this.filter_tag_det_res(boxes);
|
||||
|
||||
dt_boxes.detach();
|
||||
|
||||
// release Mat
|
||||
newMask.release();
|
||||
|
||||
return dt_boxes;
|
||||
}
|
||||
|
||||
|
||||
private NDList filter_tag_det_res(NDArray dt_boxes) {
|
||||
NDList boxesList = new NDList();
|
||||
|
||||
int num = (int) dt_boxes.getShape().get(0);
|
||||
for (int i = 0; i < num; i++) {
|
||||
NDArray box = dt_boxes.get(i);
|
||||
box = order_points_clockwise(box);
|
||||
box = clip_det_res(box);
|
||||
float[] box0 = box.get(0).toFloatArray();
|
||||
float[] box1 = box.get(1).toFloatArray();
|
||||
float[] box3 = box.get(3).toFloatArray();
|
||||
int rect_width = (int) Math.sqrt(Math.pow(box1[0] - box0[0], 2) + Math.pow(box1[1] - box0[1], 2));
|
||||
int rect_height = (int) Math.sqrt(Math.pow(box3[0] - box0[0], 2) + Math.pow(box3[1] - box0[1], 2));
|
||||
if (rect_width <= 3 || rect_height <= 3)
|
||||
continue;
|
||||
boxesList.add(box);
|
||||
}
|
||||
|
||||
return boxesList;
|
||||
}
|
||||
|
||||
private NDArray clip_det_res(NDArray points) {
|
||||
for (int i = 0; i < points.getShape().get(0); i++) {
|
||||
int value = Math.max((int) points.get(i, 0).toFloatArray()[0], 0);
|
||||
value = Math.min(value, img_width - 1);
|
||||
points.set(new NDIndex(i + ",0"), value);
|
||||
value = Math.max((int) points.get(i, 1).toFloatArray()[0], 0);
|
||||
value = Math.min(value, img_height - 1);
|
||||
points.set(new NDIndex(i + ",1"), value);
|
||||
}
|
||||
|
||||
return points;
|
||||
}
|
||||
|
||||
/**
|
||||
* sort the points based on their x-coordinates
|
||||
* 顺时针
|
||||
*
|
||||
* @param pts
|
||||
* @return
|
||||
*/
|
||||
|
||||
private NDArray order_points_clockwise(NDArray pts) {
|
||||
NDList list = new NDList();
|
||||
long[] indexes = pts.get(":, 0").argSort().toLongArray();
|
||||
|
||||
// grab the left-most and right-most points from the sorted
|
||||
// x-roodinate points
|
||||
Shape s1 = pts.getShape();
|
||||
NDArray leftMost1 = pts.get(indexes[0] + ",:");
|
||||
NDArray leftMost2 = pts.get(indexes[1] + ",:");
|
||||
NDArray leftMost = leftMost1.concat(leftMost2).reshape(2, 2);
|
||||
NDArray rightMost1 = pts.get(indexes[2] + ",:");
|
||||
NDArray rightMost2 = pts.get(indexes[3] + ",:");
|
||||
NDArray rightMost = rightMost1.concat(rightMost2).reshape(2, 2);
|
||||
|
||||
// now, sort the left-most coordinates according to their
|
||||
// y-coordinates so we can grab the top-left and bottom-left
|
||||
// points, respectively
|
||||
indexes = leftMost.get(":, 1").argSort().toLongArray();
|
||||
NDArray lt = leftMost.get(indexes[0] + ",:");
|
||||
NDArray lb = leftMost.get(indexes[1] + ",:");
|
||||
indexes = rightMost.get(":, 1").argSort().toLongArray();
|
||||
NDArray rt = rightMost.get(indexes[0] + ",:");
|
||||
NDArray rb = rightMost.get(indexes[1] + ",:");
|
||||
|
||||
list.add(lt);
|
||||
list.add(rt);
|
||||
list.add(rb);
|
||||
list.add(lb);
|
||||
|
||||
NDArray rect = NDArrays.concat(list).reshape(4, 2);
|
||||
return rect;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get boxes from the binarized image predicted by DB
|
||||
*
|
||||
* @param manager
|
||||
* @param pred the binarized image predicted by DB.
|
||||
* @param bitmap new 'pred' after threshold filtering.
|
||||
*/
|
||||
private NDArray boxes_from_bitmap(NDManager manager, NDArray pred, Mat bitmap) {
|
||||
int dest_height = (int) pred.getShape().get(0);
|
||||
int dest_width = (int) pred.getShape().get(1);
|
||||
int height = bitmap.rows();
|
||||
int width = bitmap.cols();
|
||||
|
||||
List<MatOfPoint> contours = new ArrayList<>();
|
||||
Mat hierarchy = new Mat();
|
||||
// 寻找轮廓
|
||||
Imgproc.findContours(
|
||||
bitmap,
|
||||
contours,
|
||||
hierarchy,
|
||||
Imgproc.RETR_LIST,
|
||||
Imgproc.CHAIN_APPROX_SIMPLE);
|
||||
|
||||
int num_contours = Math.min(contours.size(), max_candidates);
|
||||
NDList boxList = new NDList();
|
||||
float[] scores = new float[num_contours];
|
||||
|
||||
for (int index = 0; index < num_contours; index++) {
|
||||
MatOfPoint contour = contours.get(index);
|
||||
MatOfPoint2f newContour = new MatOfPoint2f(contour.toArray());
|
||||
float[][] pointsArr = new float[4][2];
|
||||
int sside = get_mini_boxes(newContour, pointsArr);
|
||||
if (sside < this.min_size)
|
||||
continue;
|
||||
NDArray points = manager.create(pointsArr);
|
||||
float score = box_score_fast(manager, pred, points);
|
||||
if (score < this.box_thresh)
|
||||
continue;
|
||||
|
||||
NDArray box = unclip(manager, points); // TODO get_mini_boxes(box)
|
||||
|
||||
// box[:, 0] = np.clip(np.round(box[:, 0] / width * dest_width), 0, dest_width)
|
||||
NDArray boxes1 = box.get(":,0").div(width).mul(dest_width).round().clip(0, dest_width);
|
||||
box.set(new NDIndex(":, 0"), boxes1);
|
||||
// box[:, 1] = np.clip(np.round(box[:, 1] / height * dest_height), 0, dest_height)
|
||||
NDArray boxes2 = box.get(":,1").div(height).mul(dest_height).round().clip(0, dest_height);
|
||||
box.set(new NDIndex(":, 1"), boxes2);
|
||||
|
||||
boxList.add(box);
|
||||
scores[index] = score;
|
||||
|
||||
// release memory
|
||||
contour.release();
|
||||
newContour.release();
|
||||
}
|
||||
|
||||
NDArray boxes = NDArrays.stack(boxList);
|
||||
|
||||
// release
|
||||
hierarchy.release();
|
||||
|
||||
return boxes;
|
||||
}
|
||||
|
||||
/**
|
||||
* Shrink or expand the boxaccording to 'unclip_ratio'
|
||||
*
|
||||
* @param points The predicted box.
|
||||
* @return uncliped box
|
||||
*/
|
||||
private NDArray unclip(NDManager manager, NDArray points) {
|
||||
points = order_points_clockwise(points);
|
||||
float[] pointsArr = points.toFloatArray();
|
||||
float[] lt = java.util.Arrays.copyOfRange(pointsArr, 0, 2);
|
||||
float[] lb = java.util.Arrays.copyOfRange(pointsArr, 6, 8);
|
||||
|
||||
float[] rt = java.util.Arrays.copyOfRange(pointsArr, 2, 4);
|
||||
float[] rb = java.util.Arrays.copyOfRange(pointsArr, 4, 6);
|
||||
|
||||
float width = distance(lt, rt);
|
||||
float height = distance(lt, lb);
|
||||
|
||||
if (width > height) {
|
||||
float k = (lt[1] - rt[1]) / (lt[0] - rt[0]); // y = k * x + b
|
||||
|
||||
float delta_dis = height;
|
||||
float delta_x = (float) Math.sqrt((delta_dis * delta_dis) / (k * k + 1));
|
||||
float delta_y = Math.abs(k * delta_x);
|
||||
|
||||
if (k > 0) {
|
||||
pointsArr[0] = lt[0] - delta_x + delta_y;
|
||||
pointsArr[1] = lt[1] - delta_y - delta_x;
|
||||
pointsArr[2] = rt[0] + delta_x + delta_y;
|
||||
pointsArr[3] = rt[1] + delta_y - delta_x;
|
||||
|
||||
pointsArr[4] = rb[0] + delta_x - delta_y;
|
||||
pointsArr[5] = rb[1] + delta_y + delta_x;
|
||||
pointsArr[6] = lb[0] - delta_x - delta_y;
|
||||
pointsArr[7] = lb[1] - delta_y + delta_x;
|
||||
} else {
|
||||
pointsArr[0] = lt[0] - delta_x - delta_y;
|
||||
pointsArr[1] = lt[1] + delta_y - delta_x;
|
||||
pointsArr[2] = rt[0] + delta_x - delta_y;
|
||||
pointsArr[3] = rt[1] - delta_y - delta_x;
|
||||
|
||||
pointsArr[4] = rb[0] + delta_x + delta_y;
|
||||
pointsArr[5] = rb[1] - delta_y + delta_x;
|
||||
pointsArr[6] = lb[0] - delta_x + delta_y;
|
||||
pointsArr[7] = lb[1] + delta_y + delta_x;
|
||||
}
|
||||
} else {
|
||||
float k = (lt[1] - rt[1]) / (lt[0] - rt[0]); // y = k * x + b
|
||||
|
||||
float delta_dis = width;
|
||||
float delta_y = (float) Math.sqrt((delta_dis * delta_dis) / (k * k + 1));
|
||||
float delta_x = Math.abs(k * delta_y);
|
||||
|
||||
if (k > 0) {
|
||||
pointsArr[0] = lt[0] + delta_x - delta_y;
|
||||
pointsArr[1] = lt[1] - delta_y - delta_x;
|
||||
pointsArr[2] = rt[0] + delta_x + delta_y;
|
||||
pointsArr[3] = rt[1] - delta_y + delta_x;
|
||||
|
||||
pointsArr[4] = rb[0] - delta_x + delta_y;
|
||||
pointsArr[5] = rb[1] + delta_y + delta_x;
|
||||
pointsArr[6] = lb[0] - delta_x - delta_y;
|
||||
pointsArr[7] = lb[1] + delta_y - delta_x;
|
||||
} else {
|
||||
pointsArr[0] = lt[0] - delta_x - delta_y;
|
||||
pointsArr[1] = lt[1] - delta_y + delta_x;
|
||||
pointsArr[2] = rt[0] - delta_x + delta_y;
|
||||
pointsArr[3] = rt[1] - delta_y - delta_x;
|
||||
|
||||
pointsArr[4] = rb[0] + delta_x + delta_y;
|
||||
pointsArr[5] = rb[1] + delta_y - delta_x;
|
||||
pointsArr[6] = lb[0] + delta_x - delta_y;
|
||||
pointsArr[7] = lb[1] + delta_y + delta_x;
|
||||
}
|
||||
}
|
||||
points = manager.create(pointsArr).reshape(4, 2);
|
||||
|
||||
return points;
|
||||
}
|
||||
|
||||
private float distance(float[] point1, float[] point2) {
|
||||
float disX = point1[0] - point2[0];
|
||||
float disY = point1[1] - point2[1];
|
||||
float dis = (float) Math.sqrt(disX * disX + disY * disY);
|
||||
return dis;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get boxes from the contour or box.
|
||||
*
|
||||
* @param contour The predicted contour.
|
||||
* @param pointsArr The predicted box.
|
||||
* @return smaller side of box
|
||||
*/
|
||||
private int get_mini_boxes(MatOfPoint2f contour, float[][] pointsArr) {
|
||||
// https://blog.csdn.net/qq_37385726/article/details/82313558
|
||||
// bounding_box[1] - rect 返回矩形的长和宽
|
||||
RotatedRect rect = Imgproc.minAreaRect(contour);
|
||||
Mat points = new Mat();
|
||||
Imgproc.boxPoints(rect, points);
|
||||
|
||||
float[][] fourPoints = new float[4][2];
|
||||
for (int row = 0; row < 4; row++) {
|
||||
fourPoints[row][0] = (float) points.get(row, 0)[0];
|
||||
fourPoints[row][1] = (float) points.get(row, 1)[0];
|
||||
}
|
||||
|
||||
float[] tmpPoint = new float[2];
|
||||
for (int i = 0; i < 4; i++) {
|
||||
for (int j = i + 1; j < 4; j++) {
|
||||
if (fourPoints[j][0] < fourPoints[i][0]) {
|
||||
tmpPoint[0] = fourPoints[i][0];
|
||||
tmpPoint[1] = fourPoints[i][1];
|
||||
fourPoints[i][0] = fourPoints[j][0];
|
||||
fourPoints[i][1] = fourPoints[j][1];
|
||||
fourPoints[j][0] = tmpPoint[0];
|
||||
fourPoints[j][1] = tmpPoint[1];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
int index_1 = 0;
|
||||
int index_2 = 1;
|
||||
int index_3 = 2;
|
||||
int index_4 = 3;
|
||||
|
||||
if (fourPoints[1][1] > fourPoints[0][1]) {
|
||||
index_1 = 0;
|
||||
index_4 = 1;
|
||||
} else {
|
||||
index_1 = 1;
|
||||
index_4 = 0;
|
||||
}
|
||||
|
||||
if (fourPoints[3][1] > fourPoints[2][1]) {
|
||||
index_2 = 2;
|
||||
index_3 = 3;
|
||||
} else {
|
||||
index_2 = 3;
|
||||
index_3 = 2;
|
||||
}
|
||||
|
||||
pointsArr[0] = fourPoints[index_1];
|
||||
pointsArr[1] = fourPoints[index_2];
|
||||
pointsArr[2] = fourPoints[index_3];
|
||||
pointsArr[3] = fourPoints[index_4];
|
||||
|
||||
int height = rect.boundingRect().height;
|
||||
int width = rect.boundingRect().width;
|
||||
int sside = Math.min(height, width);
|
||||
|
||||
// release
|
||||
points.release();
|
||||
|
||||
return sside;
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate the score of box.
|
||||
*
|
||||
* @param bitmap The binarized image predicted by DB.
|
||||
* @param points The predicted box
|
||||
* @return
|
||||
*/
|
||||
private float box_score_fast(NDManager manager, NDArray bitmap, NDArray points) {
|
||||
NDArray box = points.get(":");
|
||||
long h = bitmap.getShape().get(0);
|
||||
long w = bitmap.getShape().get(1);
|
||||
// xmin = np.clip(np.floor(box[:, 0].min()).astype(np.int), 0, w - 1)
|
||||
int xmin = box.get(":, 0").min().floor().clip(0, w - 1).toType(DataType.INT32, true).toIntArray()[0];
|
||||
int xmax = box.get(":, 0").max().ceil().clip(0, w - 1).toType(DataType.INT32, true).toIntArray()[0];
|
||||
int ymin = box.get(":, 1").min().floor().clip(0, h - 1).toType(DataType.INT32, true).toIntArray()[0];
|
||||
int ymax = box.get(":, 1").max().ceil().clip(0, h - 1).toType(DataType.INT32, true).toIntArray()[0];
|
||||
|
||||
NDArray mask = manager.zeros(new Shape(ymax - ymin + 1, xmax - xmin + 1), DataType.UINT8);
|
||||
|
||||
box.set(new NDIndex(":, 0"), box.get(":, 0").sub(xmin));
|
||||
box.set(new NDIndex(":, 1"), box.get(":, 1").sub(ymin));
|
||||
|
||||
//mask - convert from NDArray to Mat
|
||||
Mat maskMat = NDArrayUtils.uint8NDArrayToMat(mask);
|
||||
|
||||
//mask - convert from NDArray to Mat - 4 rows, 2 cols
|
||||
Mat boxMat = NDArrayUtils.floatNDArrayToMat(box, CvType.CV_32S);
|
||||
|
||||
// boxMat.reshape(1, new int[]{1, 4, 2});
|
||||
List<MatOfPoint> pts = new ArrayList<>();
|
||||
MatOfPoint matOfPoint = NDArrayUtils.matToMatOfPoint(boxMat); // new MatOfPoint(boxMat);
|
||||
pts.add(matOfPoint);
|
||||
Imgproc.fillPoly(maskMat, pts, new Scalar(1));
|
||||
|
||||
|
||||
NDArray subBitMap = bitmap.get(ymin + ":" + (ymax + 1) + "," + xmin + ":" + (xmax + 1));
|
||||
Mat bitMapMat = NDArrayUtils.floatNDArrayToMat(subBitMap);
|
||||
|
||||
Scalar score = Core.mean(bitMapMat, maskMat);
|
||||
float scoreValue = (float) score.val[0];
|
||||
// release
|
||||
maskMat.release();
|
||||
boxMat.release();
|
||||
bitMapMat.release();
|
||||
|
||||
return scoreValue;
|
||||
}
|
||||
|
||||
@Override
|
||||
public NDList processInput(TranslatorContext ctx, Image input) {
|
||||
NDArray img = input.toNDArray(ctx.getNDManager());
|
||||
int h = input.getHeight();
|
||||
int w = input.getWidth();
|
||||
img_height = h;
|
||||
img_width = w;
|
||||
|
||||
// limit the max side
|
||||
float ratio = 1.0f;
|
||||
if (Math.max(h, w) > limit_side_len) {
|
||||
if (h > w) {
|
||||
ratio = (float) limit_side_len / (float) h;
|
||||
} else {
|
||||
ratio = (float) limit_side_len / (float) w;
|
||||
}
|
||||
}
|
||||
|
||||
int resize_h = (int) (h * ratio);
|
||||
int resize_w = (int) (w * ratio);
|
||||
|
||||
resize_h = Math.round((float) resize_h / 32f) * 32;
|
||||
resize_w = Math.round((float) resize_w / 32f) * 32;
|
||||
|
||||
ratio_h = resize_h / (float) h;
|
||||
ratio_w = resize_w / (float) w;
|
||||
|
||||
img = NDImageUtils.resize(img, resize_w, resize_h);
|
||||
|
||||
img = NDImageUtils.toTensor(img);
|
||||
|
||||
img =
|
||||
NDImageUtils.normalize(
|
||||
img,
|
||||
new float[]{0.485f, 0.456f, 0.406f},
|
||||
new float[]{0.229f, 0.224f, 0.225f});
|
||||
|
||||
img = img.expandDims(0);
|
||||
|
||||
return new NDList(img);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Batchifier getBatchifier() {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,314 @@
|
||||
package top.aias.iocr.translator;
|
||||
|
||||
import ai.djl.Model;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.output.BoundingBox;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
import ai.djl.modality.cv.output.Rectangle;
|
||||
import ai.djl.modality.cv.util.NDImageUtils;
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDArrays;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.ndarray.index.NDIndex;
|
||||
import ai.djl.ndarray.types.DataType;
|
||||
import ai.djl.ndarray.types.Shape;
|
||||
import ai.djl.translate.Batchifier;
|
||||
import ai.djl.translate.Translator;
|
||||
import ai.djl.translate.TranslatorContext;
|
||||
import ai.djl.util.Utils;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.io.InputStream;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
/**
|
||||
* 布局检测前后处理
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class PicoDetLayoutDetectionTranslator implements Translator<Image, DetectedObjects> {
|
||||
private List<String> table;
|
||||
|
||||
NDArray scale_factor;
|
||||
Shape input_shape;
|
||||
Shape ori_shape;
|
||||
|
||||
int[] strides = new int[]{8, 16, 32, 64};
|
||||
float score_threshold = 0.6f; // default = 0.4
|
||||
float nms_threshold = 0.5f;
|
||||
int nms_top_k = 1000;
|
||||
int keep_top_k = 100;
|
||||
|
||||
private int width;
|
||||
private int height;
|
||||
|
||||
public PicoDetLayoutDetectionTranslator() {
|
||||
}
|
||||
|
||||
@Override
|
||||
public void prepare(TranslatorContext ctx) throws IOException {
|
||||
Model model = ctx.getModel();
|
||||
try (InputStream is = model.getArtifact("dict.txt").openStream()) {
|
||||
table = Utils.readLines(is, true);
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public NDList processInput(TranslatorContext ctx, Image input) {
|
||||
NDArray img = input.toNDArray(ctx.getNDManager());
|
||||
width = input.getWidth();
|
||||
height = input.getHeight();
|
||||
|
||||
img = NDImageUtils.resize(img, 608, 800);
|
||||
img = img.transpose(2, 0, 1).div(255);
|
||||
img =
|
||||
NDImageUtils.normalize(
|
||||
img, new float[]{0.485f, 0.456f, 0.406f}, new float[]{0.229f, 0.224f, 0.225f});
|
||||
img = img.expandDims(0);
|
||||
|
||||
// (im_scale_y im_scale_x)
|
||||
scale_factor = ctx.getNDManager().create(new float[]{800f / height, 608f / width});
|
||||
input_shape = new Shape(800, 608);
|
||||
ori_shape = input_shape; //new Shape(height, width);
|
||||
|
||||
return new NDList(img);
|
||||
}
|
||||
|
||||
@Override
|
||||
public DetectedObjects processOutput(TranslatorContext ctx, NDList list) {
|
||||
// NDManager manager = ctx.getNDManager();
|
||||
try (NDManager manager =
|
||||
NDManager.newBaseManager(ctx.getNDManager().getDevice(), "PyTorch")) {
|
||||
|
||||
NDList raw_boxes = list.subNDList(4);
|
||||
NDList scores = list;
|
||||
scores.removeAll(raw_boxes);
|
||||
|
||||
int dimension = raw_boxes.get(0).getShape().dimension();
|
||||
int reg_max = (int) (raw_boxes.get(0).getShape().get(dimension - 1) / 4 - 1);
|
||||
NDArray out_boxes_list = manager.zeros(new Shape(0, 6));
|
||||
|
||||
List<BoundingBox> boxesList = new ArrayList<>();
|
||||
List<String> namesList = new ArrayList<>();
|
||||
List<Double> probsList = new ArrayList<>();
|
||||
|
||||
NDArray bboxes = manager.zeros(new Shape(0, 4));
|
||||
NDArray confidences = manager.zeros(new Shape(0, scores.get(0).getShape().get(2))); // CN 10, EN 5
|
||||
|
||||
for (int i = 0; i < scores.size(); i++) {
|
||||
NDArray box_distribute = raw_boxes.get(i);
|
||||
box_distribute = box_distribute.squeeze();
|
||||
NDArray score = scores.get(i);
|
||||
score = score.squeeze(0);
|
||||
int stride = strides[i];
|
||||
// centers
|
||||
float fm_h = input_shape.get(0) / (float) stride;
|
||||
float fm_w = input_shape.get(1) / (float) stride;
|
||||
NDArray h_range = manager.arange(fm_h);
|
||||
NDArray w_range = manager.arange(fm_w);
|
||||
w_range = w_range.reshape(1, w_range.size());
|
||||
|
||||
NDArray ww = manager.zeros(new Shape(0, w_range.size()));
|
||||
for (int j = 0; j < h_range.size(); j++) {
|
||||
ww = ww.concat(w_range, 0);
|
||||
}
|
||||
|
||||
h_range = h_range.reshape(h_range.size(), 1);
|
||||
|
||||
NDArray hh = manager.zeros(new Shape(h_range.size(), 0));
|
||||
for (int j = 0; j < w_range.size(); j++) {
|
||||
hh = hh.concat(h_range, 1);
|
||||
}
|
||||
|
||||
NDArray ct_row = hh.flatten().add(0.5).mul(stride);
|
||||
NDArray ct_col = ww.flatten().add(0.5).mul(stride);
|
||||
ct_row = ct_row.reshape(ct_row.size(), 1);
|
||||
ct_col = ct_col.reshape(ct_col.size(), 1);
|
||||
|
||||
NDArray center = ct_col.concat(ct_row, 1).concat(ct_col, 1).concat(ct_row, 1);
|
||||
// box distribution to distance
|
||||
NDArray reg_range = manager.arange(reg_max + 1);
|
||||
NDArray box_distance = box_distribute.reshape(-1, reg_max + 1);
|
||||
box_distance = box_distance.softmax(1);
|
||||
box_distance = box_distance.mul(reg_range.expandDims(0));
|
||||
box_distance = box_distance.sum(new int[]{1}).reshape(-1, 4);
|
||||
box_distance = box_distance.mul(stride);
|
||||
|
||||
// top K candidate
|
||||
NDArray topk_idx = score.max(new int[]{1}).argSort(0, false);
|
||||
topk_idx = topk_idx.get(new NDIndex(":" + this.nms_top_k));
|
||||
center = center.get(topk_idx);
|
||||
score = score.get(topk_idx);
|
||||
box_distance = box_distance.get(topk_idx);
|
||||
|
||||
// decode box
|
||||
NDArray decode_box = center.add(manager.create(new int[]{-1, -1, 1, 1}).mul(box_distance));
|
||||
bboxes = bboxes.concat(decode_box, 0);
|
||||
confidences = confidences.concat(score, 0);
|
||||
}
|
||||
|
||||
// nms
|
||||
NDArray picked_box_probs = manager.zeros(new Shape(0, 5));
|
||||
ArrayList<Integer> picked_labels = new ArrayList<>();
|
||||
for (int class_index = 0; class_index < confidences.getShape().get(1); class_index++) {
|
||||
NDArray probs = confidences.get(new NDIndex(":," + class_index));
|
||||
NDArray mask = probs.gt(this.score_threshold);
|
||||
probs = probs.get(mask);
|
||||
if (probs.getShape().get(0) == 0) {
|
||||
continue;
|
||||
}
|
||||
NDArray subset_boxes = bboxes.get(mask);
|
||||
NDArray box_probs = subset_boxes.concat(probs.reshape(-1, 1), 1);
|
||||
box_probs = hard_nms(manager, box_probs, this.nms_threshold, this.keep_top_k, 200);
|
||||
|
||||
picked_box_probs = picked_box_probs.concat(box_probs);
|
||||
for (int i = 0; i < box_probs.size(0); i++) {
|
||||
picked_labels.add(class_index);
|
||||
}
|
||||
}
|
||||
|
||||
if (picked_box_probs.size() == 0) {
|
||||
// out_boxes_list.concat(manager.zeros(new Shape(0,4)));
|
||||
// out_boxes_num.concat(manager.create(0));
|
||||
} else {
|
||||
// resize output boxes
|
||||
NDArray wb = warp_boxes(manager, picked_box_probs.get(new NDIndex(":, :4")));
|
||||
picked_box_probs.set(new NDIndex(":, :4"), wb);
|
||||
|
||||
NDArray im_scale = scale_factor.flip(0).concat(scale_factor.flip(0));
|
||||
|
||||
picked_box_probs.set(new NDIndex(":, :4"), picked_box_probs.get(new NDIndex(":, :4")).div(im_scale));
|
||||
|
||||
// clas score box
|
||||
float[] arr = new float[picked_labels.size()];
|
||||
for (int i = 0; i < picked_labels.size(); i++) {
|
||||
arr[i] = picked_labels.get(i);
|
||||
}
|
||||
|
||||
int rows = picked_labels.size();
|
||||
NDArray labels = manager.create(arr).reshape(rows, 1);
|
||||
NDArray picked_box_prob_1 = picked_box_probs.get(new NDIndex(":, 4")).reshape(rows, 1);
|
||||
NDArray picked_box_prob_2 = picked_box_probs.get(new NDIndex(":, :4"));
|
||||
NDArray out_boxes = labels.concat(picked_box_prob_1, 1).concat(picked_box_prob_2, 1);
|
||||
out_boxes_list = out_boxes_list.concat(out_boxes);
|
||||
}
|
||||
|
||||
|
||||
for (int i = 0; i < out_boxes_list.size(0); i++) {
|
||||
NDArray dt = out_boxes_list.get(i);
|
||||
float[] array = dt.toFloatArray();
|
||||
// if (array[1] <= 0.5 || array[0] <= -1) continue;
|
||||
int clsid = (int) array[0];
|
||||
double score = array[1];
|
||||
String name = table.get(clsid);
|
||||
|
||||
float x = array[2] / width;
|
||||
float y = array[3] / height;
|
||||
float w = (array[4] - array[2]) / width;
|
||||
float h = (array[5] - array[3]) / height;
|
||||
|
||||
Rectangle rect = new Rectangle(x, y, w, h);
|
||||
boxesList.add(rect);
|
||||
namesList.add(name);
|
||||
probsList.add(score);
|
||||
}
|
||||
return new DetectedObjects(namesList, probsList, boxesList);
|
||||
}
|
||||
}
|
||||
|
||||
private NDArray warp_boxes(NDManager manager, NDArray boxes) {
|
||||
int width = (int) ori_shape.get(1);
|
||||
int height = (int) ori_shape.get(0);
|
||||
int n = (int) boxes.size(0);
|
||||
if (n > 0) {
|
||||
// warp points
|
||||
NDArray xy = manager.ones(new Shape(n * 4, 3));
|
||||
NDArray box1 = boxes.get(new NDIndex(":,0")).reshape(n, 1);
|
||||
NDArray box2 = boxes.get(new NDIndex(":,3")).reshape(n, 1);
|
||||
NDArray box3 = boxes.get(new NDIndex(":,2")).reshape(n, 1);
|
||||
NDArray box4 = boxes.get(new NDIndex(":,1")).reshape(n, 1);
|
||||
boxes = boxes.concat(box1, 1).concat(box2, 1).concat(box3, 1).concat(box4, 1);
|
||||
boxes = boxes.reshape(n * 4, 2);
|
||||
xy.set(new NDIndex(":, :2"), boxes);
|
||||
|
||||
xy = xy.get(new NDIndex(":, :2")).div(xy.get(new NDIndex(":, 2:3"))).reshape(n, 8);
|
||||
|
||||
// create new boxes
|
||||
NDArray xy0 = xy.get(new NDIndex(":,0")).reshape(n, 1);
|
||||
NDArray xy2 = xy.get(new NDIndex(":,2")).reshape(n, 1);
|
||||
NDArray xy4 = xy.get(new NDIndex(":,4")).reshape(n, 1);
|
||||
NDArray xy6 = xy.get(new NDIndex(":,6")).reshape(n, 1);
|
||||
NDArray x = xy0.concat(xy2, 1).concat(xy4, 1).concat(xy6, 1);
|
||||
|
||||
NDArray xy1 = xy.get(new NDIndex(":,1")).reshape(n, 1);
|
||||
NDArray xy3 = xy.get(new NDIndex(":,3")).reshape(n, 1);
|
||||
NDArray xy5 = xy.get(new NDIndex(":,5")).reshape(n, 1);
|
||||
NDArray xy7 = xy.get(new NDIndex(":,7")).reshape(n, 1);
|
||||
NDArray y = xy1.concat(xy3, 1).concat(xy5, 1).concat(xy7, 1);
|
||||
xy = x.min(new int[]{1}).concat(y.min(new int[]{1})).concat(x.max(new int[]{1})).concat(y.max(new int[]{1})).reshape(4, n).transpose();
|
||||
|
||||
// clip boxes
|
||||
xy.set(new NDIndex(":,0"), xy.get(new NDIndex(":,0")).clip(0, width));
|
||||
xy.set(new NDIndex(":,2"), xy.get(new NDIndex(":,2")).clip(0, width));
|
||||
xy.set(new NDIndex(":,1"), xy.get(new NDIndex(":,1")).clip(0, height));
|
||||
xy.set(new NDIndex(":,3"), xy.get(new NDIndex(":,3")).clip(0, height));
|
||||
|
||||
return xy;
|
||||
|
||||
} else {
|
||||
return boxes;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
private NDArray hard_nms(NDManager manager, NDArray box_scores, float iou_threshold, int top_k, int candidate_size) {
|
||||
NDArray scores = box_scores.get(new NDIndex(":, -1"));
|
||||
NDArray boxes = box_scores.get(new NDIndex(":, :-1"));
|
||||
NDArray indexes = scores.argSort();
|
||||
if (candidate_size < indexes.size()) {
|
||||
indexes = indexes.get(new NDIndex((-candidate_size) + ":"));
|
||||
}
|
||||
NDArray picked = manager.zeros(new Shape(0), DataType.INT64);
|
||||
while (indexes.size() > 0) {
|
||||
NDArray current = indexes.get(new NDIndex("-1")).reshape(1);
|
||||
picked = picked.concat(current, 0);
|
||||
if (top_k == picked.size() || indexes.size() == 1) {
|
||||
break;
|
||||
}
|
||||
NDArray current_box = boxes.get(current);
|
||||
indexes = indexes.get(new NDIndex(":-1"));
|
||||
NDArray rest_boxes = boxes.get(indexes);
|
||||
NDArray iou = iou_of(rest_boxes, current_box.expandDims(0));
|
||||
iou = iou.squeeze();
|
||||
if (iou.getShape().dimension() == 0)
|
||||
iou = iou.reshape(1);
|
||||
NDArray cutOff = iou.lte(iou_threshold);
|
||||
indexes = indexes.get(cutOff);
|
||||
}
|
||||
|
||||
return box_scores.get(picked);
|
||||
}
|
||||
|
||||
private NDArray iou_of(NDArray boxes0, NDArray boxes1) {
|
||||
NDArray overlap_left_top = NDArrays.maximum(boxes0.get(new NDIndex("..., :2")), boxes1.get(new NDIndex("..., :2")));
|
||||
NDArray overlap_right_bottom = NDArrays.minimum(boxes0.get(new NDIndex("..., 2:")), boxes1.get(new NDIndex("..., 2:")));
|
||||
NDArray overlap_area = area_of(overlap_left_top, overlap_right_bottom);
|
||||
NDArray area0 = area_of(boxes0.get(new NDIndex("..., :2")), boxes0.get(new NDIndex("..., 2:")));
|
||||
NDArray area1 = area_of(boxes1.get(new NDIndex("..., :2")), boxes1.get(new NDIndex("..., 2:")));
|
||||
return overlap_area.div(area0.add(area1).sub(overlap_area).add(Math.exp(-5)));
|
||||
|
||||
}
|
||||
|
||||
private NDArray area_of(NDArray left_top, NDArray right_bottom) {
|
||||
NDArray hw = right_bottom.sub(left_top).clip(0.0f, Float.MAX_VALUE);
|
||||
return hw.get(new NDIndex("..., 0")).mul(hw.get(new NDIndex("..., 1")));
|
||||
}
|
||||
|
||||
@Override
|
||||
public Batchifier getBatchifier() {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,114 @@
|
||||
package top.aias.iocr.translator;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.output.BoundingBox;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
import ai.djl.modality.cv.util.NDImageUtils;
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.ndarray.types.DataType;
|
||||
import ai.djl.ndarray.types.Shape;
|
||||
import ai.djl.paddlepaddle.zoo.cv.objectdetection.BoundFinder;
|
||||
import ai.djl.translate.Batchifier;
|
||||
import ai.djl.translate.Translator;
|
||||
import ai.djl.translate.TranslatorContext;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.stream.IntStream;
|
||||
/**
|
||||
* 水平文字检测前后处理
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class PpWordDetectionTranslator implements Translator<Image, DetectedObjects> {
|
||||
|
||||
private final int max_side_len;
|
||||
|
||||
public PpWordDetectionTranslator(Map<String, ?> arguments) {
|
||||
max_side_len =
|
||||
arguments.containsKey("maxLength")
|
||||
? Integer.parseInt(arguments.get("maxLength").toString())
|
||||
: 960;
|
||||
}
|
||||
|
||||
@Override
|
||||
public DetectedObjects processOutput(TranslatorContext ctx, NDList list) {
|
||||
NDArray result = list.get(0);
|
||||
result = result.squeeze().mul(255f).toType(DataType.UINT8, true).gt(0.3); // thresh=0.3
|
||||
boolean[] flattened = result.toBooleanArray();
|
||||
Shape shape = result.getShape();
|
||||
int w = (int) shape.get(0);
|
||||
int h = (int) shape.get(1);
|
||||
boolean[][] grid = new boolean[w][h];
|
||||
IntStream.range(0, flattened.length)
|
||||
.parallel()
|
||||
.forEach(i -> grid[i / h][i % h] = flattened[i]);
|
||||
List<BoundingBox> boxes = new BoundFinder(grid).getBoxes();
|
||||
List<String> names = new ArrayList<>();
|
||||
List<Double> probs = new ArrayList<>();
|
||||
int boxSize = boxes.size();
|
||||
for (int i = 0; i < boxSize; i++) {
|
||||
names.add("word");
|
||||
probs.add(1.0);
|
||||
}
|
||||
return new DetectedObjects(names, probs, boxes);
|
||||
}
|
||||
|
||||
@Override
|
||||
public NDList processInput(TranslatorContext ctx, Image input) {
|
||||
NDArray img = input.toNDArray(ctx.getNDManager());
|
||||
int h = input.getHeight();
|
||||
int w = input.getWidth();
|
||||
int resize_w = w;
|
||||
int resize_h = h;
|
||||
|
||||
// limit the max side
|
||||
float ratio = 1.0f;
|
||||
if (Math.max(resize_h, resize_w) > max_side_len) {
|
||||
if (resize_h > resize_w) {
|
||||
ratio = (float) max_side_len / (float) resize_h;
|
||||
} else {
|
||||
ratio = (float) max_side_len / (float) resize_w;
|
||||
}
|
||||
}
|
||||
|
||||
resize_h = (int) (resize_h * ratio);
|
||||
resize_w = (int) (resize_w * ratio);
|
||||
|
||||
if (resize_h % 32 == 0) {
|
||||
resize_h = resize_h;
|
||||
} else if (Math.floor((float) resize_h / 32f) <= 1) {
|
||||
resize_h = 32;
|
||||
} else {
|
||||
resize_h = (int) Math.floor((float) resize_h / 32f) * 32;
|
||||
}
|
||||
|
||||
if (resize_w % 32 == 0) {
|
||||
resize_w = resize_w;
|
||||
} else if (Math.floor((float) resize_w / 32f) <= 1) {
|
||||
resize_w = 32;
|
||||
} else {
|
||||
resize_w = (int) Math.floor((float) resize_w / 32f) * 32;
|
||||
}
|
||||
|
||||
img = NDImageUtils.resize(img, resize_w, resize_h);
|
||||
img = NDImageUtils.toTensor(img);
|
||||
img =
|
||||
NDImageUtils.normalize(
|
||||
img,
|
||||
new float[]{0.485f, 0.456f, 0.406f},
|
||||
new float[]{0.229f, 0.224f, 0.225f});
|
||||
img = img.expandDims(0);
|
||||
return new NDList(img);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Batchifier getBatchifier() {
|
||||
return null;
|
||||
}
|
||||
|
||||
}
|
||||
@ -0,0 +1,125 @@
|
||||
package top.aias.iocr.translator;
|
||||
|
||||
import ai.djl.Model;
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.util.NDImageUtils;
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.ndarray.index.NDIndex;
|
||||
import ai.djl.ndarray.types.DataType;
|
||||
import ai.djl.ndarray.types.Shape;
|
||||
import ai.djl.translate.Batchifier;
|
||||
import ai.djl.translate.Translator;
|
||||
import ai.djl.translate.TranslatorContext;
|
||||
import ai.djl.util.Utils;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.io.InputStream;
|
||||
import java.util.Arrays;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
/**
|
||||
* 文字识别前后处理
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class PpWordRecognitionTranslator implements Translator<Image, String> {
|
||||
private List<String> table;
|
||||
private final boolean use_space_char;
|
||||
|
||||
public PpWordRecognitionTranslator(Map<String, ?> arguments) {
|
||||
use_space_char =
|
||||
arguments.containsKey("use_space_char")
|
||||
? Boolean.parseBoolean(arguments.get("use_space_char").toString())
|
||||
: true;
|
||||
}
|
||||
|
||||
@Override
|
||||
public void prepare(TranslatorContext ctx) throws IOException {
|
||||
Model model = ctx.getModel();
|
||||
try (InputStream is = model.getArtifact("dict.txt").openStream()) {
|
||||
table = Utils.readLines(is, true);
|
||||
table.add(0, "blank");
|
||||
if(use_space_char){
|
||||
table.add(" ");
|
||||
table.add(" ");
|
||||
}
|
||||
else{
|
||||
table.add("");
|
||||
table.add("");
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public String processOutput(TranslatorContext ctx, NDList list) throws IOException {
|
||||
StringBuilder sb = new StringBuilder();
|
||||
NDArray tokens = list.singletonOrThrow();
|
||||
|
||||
long[] indices = tokens.get(0).argMax(1).toLongArray();
|
||||
boolean[] selection = new boolean[indices.length];
|
||||
Arrays.fill(selection, true);
|
||||
for (int i = 1; i < indices.length; i++) {
|
||||
if (indices[i] == indices[i - 1]) {
|
||||
selection[i] = false;
|
||||
}
|
||||
}
|
||||
|
||||
// 字符置信度
|
||||
// float[] probs = new float[indices.length];
|
||||
// for (int row = 0; row < indices.length; row++) {
|
||||
// NDArray value = tokens.get(0).get(new NDIndex(""+ row +":" + (row + 1) +"," + indices[row] +":" + ( indices[row] + 1)));
|
||||
// probs[row] = value.toFloatArray()[0];
|
||||
// }
|
||||
|
||||
int lastIdx = 0;
|
||||
for (int i = 0; i < indices.length; i++) {
|
||||
if (selection[i] == true && indices[i] > 0 && !(i > 0 && indices[i] == lastIdx)) {
|
||||
sb.append(table.get((int) indices[i]));
|
||||
}
|
||||
}
|
||||
return sb.toString();
|
||||
}
|
||||
|
||||
@Override
|
||||
public NDList processInput(TranslatorContext ctx, Image input) {
|
||||
NDArray img = input.toNDArray(ctx.getNDManager(), Image.Flag.COLOR);
|
||||
int imgC = 3;
|
||||
int imgH = 48;
|
||||
int imgW = 320;
|
||||
|
||||
float max_wh_ratio = (float) imgW / (float) imgH;
|
||||
|
||||
int h = input.getHeight();
|
||||
int w = input.getWidth();
|
||||
float wh_ratio = (float) w / (float) h;
|
||||
|
||||
max_wh_ratio = Math.max(max_wh_ratio,wh_ratio);
|
||||
imgW = (int)(imgH * max_wh_ratio);
|
||||
|
||||
int resized_w;
|
||||
if (Math.ceil(imgH * wh_ratio) > imgW) {
|
||||
resized_w = imgW;
|
||||
} else {
|
||||
resized_w = (int) (Math.ceil(imgH * wh_ratio));
|
||||
}
|
||||
NDArray resized_image = NDImageUtils.resize(img, resized_w, imgH);
|
||||
resized_image = resized_image.transpose(2, 0, 1).toType(DataType.FLOAT32,false);
|
||||
resized_image.divi(255f).subi(0.5f).divi(0.5f);
|
||||
NDArray padding_im = ctx.getNDManager().zeros(new Shape(imgC, imgH, imgW), DataType.FLOAT32);
|
||||
padding_im.set(new NDIndex(":,:,0:" + resized_w), resized_image);
|
||||
|
||||
padding_im = padding_im.flip(0);
|
||||
padding_im = padding_im.expandDims(0);
|
||||
return new NDList(padding_im);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Batchifier getBatchifier() {
|
||||
return null;
|
||||
}
|
||||
|
||||
}
|
||||
@ -0,0 +1,25 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
/**
|
||||
* 配置常量
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class Constants {
|
||||
/**
|
||||
* win systems
|
||||
*/
|
||||
public static final String WIN = "win";
|
||||
|
||||
/**
|
||||
* mac system
|
||||
*/
|
||||
public static final String MAC = "mac";
|
||||
|
||||
/**
|
||||
* mac system
|
||||
*/
|
||||
public static final String LINUX = "linux";
|
||||
}
|
||||
@ -0,0 +1,253 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import top.aias.iocr.bean.CrossRangeCellMeta;
|
||||
import org.apache.commons.lang3.StringUtils;
|
||||
import org.apache.commons.lang3.math.NumberUtils;
|
||||
import org.apache.poi.hssf.usermodel.*;
|
||||
import org.apache.poi.ss.usermodel.BorderStyle;
|
||||
import org.apache.poi.ss.usermodel.CellType;
|
||||
import org.apache.poi.ss.usermodel.HorizontalAlignment;
|
||||
import org.apache.poi.ss.usermodel.VerticalAlignment;
|
||||
import org.apache.poi.ss.util.CellRangeAddress;
|
||||
import org.dom4j.Document;
|
||||
import org.dom4j.DocumentException;
|
||||
import org.dom4j.DocumentHelper;
|
||||
import org.dom4j.Element;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* @Auther: xiaoqiang
|
||||
* @Date: 2020/12/9 9:16
|
||||
* @Description:
|
||||
*/
|
||||
public class ConvertHtml2Excel {
|
||||
/**
|
||||
* html表格转excel
|
||||
* Convert HTML table to Excel
|
||||
*
|
||||
* @param tableHtml
|
||||
* <table>
|
||||
* ..
|
||||
* </table>
|
||||
* @return
|
||||
*/
|
||||
public static HSSFWorkbook table2Excel(String tableHtml) {
|
||||
HSSFWorkbook wb = new HSSFWorkbook();
|
||||
HSSFSheet sheet = wb.createSheet();
|
||||
List<CrossRangeCellMeta> crossRowEleMetaLs = new ArrayList<>();
|
||||
int rowIndex = 0;
|
||||
try {
|
||||
Document data = DocumentHelper.parseText(tableHtml);
|
||||
// 生成表头
|
||||
// generate header
|
||||
Element thead = data.getRootElement().element("thead");
|
||||
HSSFCellStyle titleStyle = getTitleStyle(wb);
|
||||
int ls=0;//列数 //column number
|
||||
if (thead != null) {
|
||||
List<Element> trLs = thead.elements("tr");
|
||||
for (Element trEle : trLs) {
|
||||
HSSFRow row = sheet.createRow(rowIndex);
|
||||
List<Element> thLs = trEle.elements("td");
|
||||
ls=thLs.size();
|
||||
makeRowCell(thLs, rowIndex, row, 0, titleStyle, crossRowEleMetaLs);
|
||||
rowIndex++;
|
||||
}
|
||||
}
|
||||
// 生成表体
|
||||
// generate body
|
||||
Element tbody = data.getRootElement().element("tbody");
|
||||
HSSFCellStyle contentStyle = getContentStyle(wb);
|
||||
if (tbody != null) {
|
||||
List<Element> trLs = tbody.elements("tr");
|
||||
for (Element trEle : trLs) {
|
||||
HSSFRow row = sheet.createRow(rowIndex);
|
||||
List<Element> thLs = trEle.elements("th");
|
||||
int cellIndex = makeRowCell(thLs, rowIndex, row, 0, titleStyle, crossRowEleMetaLs);
|
||||
List<Element> tdLs = trEle.elements("td");
|
||||
makeRowCell(tdLs, rowIndex, row, cellIndex, contentStyle, crossRowEleMetaLs);
|
||||
rowIndex++;
|
||||
}
|
||||
}
|
||||
// 合并表头
|
||||
// merge header
|
||||
for (CrossRangeCellMeta crcm : crossRowEleMetaLs) {
|
||||
sheet.addMergedRegion(new CellRangeAddress(crcm.getFirstRow(), crcm.getLastRow(), crcm.getFirstCol(), crcm.getLastCol()));
|
||||
setRegionStyle(sheet, new CellRangeAddress(crcm.getFirstRow(), crcm.getLastRow(), crcm.getFirstCol(), crcm.getLastCol()),titleStyle);
|
||||
}
|
||||
for(int i=0;i<sheet.getRow(0).getPhysicalNumberOfCells();i++){
|
||||
sheet.autoSizeColumn(i, true);
|
||||
//设置列宽
|
||||
//set column width
|
||||
if(sheet.getColumnWidth(i)<255*256){
|
||||
sheet.setColumnWidth(i, sheet.getColumnWidth(i) < 9000 ? 9000 : sheet.getColumnWidth(i));
|
||||
}else{
|
||||
sheet.setColumnWidth(i, 15000);
|
||||
}
|
||||
}
|
||||
} catch (DocumentException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
|
||||
return wb;
|
||||
}
|
||||
|
||||
/**
|
||||
* 生产行内容
|
||||
* Generate row content
|
||||
*
|
||||
* @return 最后一列的cell index - the index of the last cell
|
||||
*/
|
||||
/**
|
||||
* @param tdLs th或者td集合 - th or td list
|
||||
* @param rowIndex 行号 - row number
|
||||
* @param row POI行对象 - POI row object
|
||||
* @param startCellIndex
|
||||
* @param cellStyle 样式 - style
|
||||
* @param crossRowEleMetaLs 跨行元数据集合 - row and column span metadata set
|
||||
* @return
|
||||
*/
|
||||
private static int makeRowCell(List<Element> tdLs, int rowIndex, HSSFRow row, int startCellIndex, HSSFCellStyle cellStyle,
|
||||
List<CrossRangeCellMeta> crossRowEleMetaLs) {
|
||||
int i = startCellIndex;
|
||||
for (int eleIndex = 0; eleIndex < tdLs.size(); i++, eleIndex++) {
|
||||
int captureCellSize = getCaptureCellSize(rowIndex, i, crossRowEleMetaLs);
|
||||
while (captureCellSize > 0) {
|
||||
for (int j = 0; j < captureCellSize; j++) {
|
||||
// 当前行跨列处理（补单元格）
|
||||
//handle the current row span (fill in cells)
|
||||
row.createCell(i);
|
||||
i++;
|
||||
}
|
||||
captureCellSize = getCaptureCellSize(rowIndex, i, crossRowEleMetaLs);
|
||||
}
|
||||
Element thEle = tdLs.get(eleIndex);
|
||||
String val = thEle.getTextTrim();
|
||||
if (StringUtils.isBlank(val)) {
|
||||
Element e = thEle.element("a");
|
||||
if (e != null) {
|
||||
val = e.getTextTrim();
|
||||
}
|
||||
}
|
||||
HSSFCell c = row.createCell(i);
|
||||
if (NumberUtils.isNumber(val)) {
|
||||
c.setCellValue(Double.parseDouble(val));
|
||||
c.setCellType(CellType.NUMERIC);
|
||||
} else {
|
||||
c.setCellValue(val);
|
||||
}
|
||||
int rowSpan = NumberUtils.toInt(thEle.attributeValue("rowspan"), 1);
|
||||
int colSpan = NumberUtils.toInt(thEle.attributeValue("colspan"), 1);
|
||||
c.setCellStyle(cellStyle);
|
||||
if (rowSpan > 1 || colSpan > 1) {
|
||||
// 存在跨行或跨列
|
||||
//exists row and column span
|
||||
crossRowEleMetaLs.add(new CrossRangeCellMeta(rowIndex, i, rowSpan, colSpan));
|
||||
}
|
||||
if (colSpan > 1) {
|
||||
// 当前行跨列处理（补单元格）
|
||||
// handle the current row span (fill in cells)
|
||||
for (int j = 1; j < colSpan; j++) {
|
||||
i++;
|
||||
row.createCell(i);
|
||||
}
|
||||
}
|
||||
}
|
||||
return i;
|
||||
}
|
||||
|
||||
/**
|
||||
* 设置合并单元格的边框样式
|
||||
* Set the border style of the merged cells
|
||||
*
|
||||
* @param sheet
|
||||
* @param region
|
||||
* @param cs
|
||||
*/
|
||||
public static void setRegionStyle(HSSFSheet sheet, CellRangeAddress region, HSSFCellStyle cs) {
|
||||
for (int i = region.getFirstRow(); i <= region.getLastRow(); i++) {
|
||||
HSSFRow row = sheet.getRow(i);
|
||||
for (int j = region.getFirstColumn(); j <= region.getLastColumn(); j++) {
|
||||
HSSFCell cell = row.getCell(j);
|
||||
cell.setCellStyle(cs);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获得因rowSpan占据的单元格
|
||||
* Get the cells occupied by rowSpan
|
||||
*
|
||||
* @param rowIndex 行号 - row number
|
||||
* @param colIndex 列号 - column number
|
||||
* @param crossRowEleMetaLs 跨行列元数据 - row and column span metadata
|
||||
* @return 当前行在某列需要占据单元格 - the number of cells to be occupied in a column on the current row
|
||||
*/
|
||||
private static int getCaptureCellSize(int rowIndex, int colIndex, List<CrossRangeCellMeta> crossRowEleMetaLs) {
|
||||
int captureCellSize = 0;
|
||||
for (CrossRangeCellMeta crossRangeCellMeta : crossRowEleMetaLs) {
|
||||
if (crossRangeCellMeta.getFirstRow() < rowIndex && crossRangeCellMeta.getLastRow() >= rowIndex) {
|
||||
if (crossRangeCellMeta.getFirstCol() <= colIndex && crossRangeCellMeta.getLastCol() >= colIndex) {
|
||||
captureCellSize = crossRangeCellMeta.getLastCol() - colIndex + 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
return captureCellSize;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获得标题样式
|
||||
* Get the title style
|
||||
*
|
||||
* @param workbook
|
||||
* @return
|
||||
*/
|
||||
private static HSSFCellStyle getTitleStyle(HSSFWorkbook workbook) {
|
||||
//short titlebackgroundcolor = IndexedColors.GREY_25_PERCENT.index;
|
||||
short fontSize = 12;
|
||||
String fontName = "宋体";
|
||||
HSSFCellStyle style = workbook.createCellStyle();
|
||||
style.setVerticalAlignment(VerticalAlignment.CENTER);
|
||||
style.setAlignment(HorizontalAlignment.CENTER);
|
||||
style.setBorderBottom(BorderStyle.THIN); //下边框 bottom border
|
||||
style.setBorderLeft(BorderStyle.THIN);//左边框 left border
|
||||
style.setBorderTop(BorderStyle.THIN);//上边框 top border
|
||||
style.setBorderRight(BorderStyle.THIN);//右边框 right border
|
||||
//style.setFillPattern(FillPatternType.SOLID_FOREGROUND);
|
||||
//style.setFillForegroundColor(titlebackgroundcolor);// 背景色 background color
|
||||
|
||||
HSSFFont font = workbook.createFont();
|
||||
font.setFontName(fontName);
|
||||
font.setFontHeightInPoints(fontSize);
|
||||
font.setBold(true);
|
||||
style.setFont(font);
|
||||
return style;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获得内容样式
|
||||
* Get the content style
|
||||
*
|
||||
* @param wb
|
||||
* @return
|
||||
*/
|
||||
private static HSSFCellStyle getContentStyle(HSSFWorkbook wb) {
|
||||
short fontSize = 12;
|
||||
String fontName = "宋体";
|
||||
HSSFCellStyle style = wb.createCellStyle();
|
||||
style.setBorderBottom(BorderStyle.THIN); //下边框 bottom border
|
||||
style.setBorderLeft(BorderStyle.THIN);//左边框 left border
|
||||
style.setBorderTop(BorderStyle.THIN);//上边框 top border
|
||||
style.setBorderRight(BorderStyle.THIN);//右边框 right border
|
||||
HSSFFont font = wb.createFont();
|
||||
font.setFontName(fontName);
|
||||
font.setFontHeightInPoints(fontSize);
|
||||
style.setFont(font);
|
||||
style.setAlignment(HorizontalAlignment.CENTER);//水平居中 horizontal center
|
||||
style.setVerticalAlignment(VerticalAlignment.CENTER);//垂直居中 vertical center
|
||||
style.setWrapText(true);
|
||||
return style;
|
||||
}
|
||||
}
|
||||
|
||||
@ -0,0 +1,82 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
|
||||
import java.awt.*;
|
||||
import java.awt.image.BufferedImage;
|
||||
import java.io.IOException;
|
||||
import java.nio.file.Files;
|
||||
import java.nio.file.Path;
|
||||
import java.nio.file.Paths;
|
||||
/**
|
||||
* DJL 图像工具类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class DJLImageUtils {
|
||||
|
||||
public static void saveDJLImage(Image img, String name, String path) {
|
||||
Path outputDir = Paths.get(path);
|
||||
Path imagePath = outputDir.resolve(name);
|
||||
try {
|
||||
img.save(Files.newOutputStream(imagePath), "png");
|
||||
} catch (IOException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
|
||||
public static void saveBoundingBoxImage(
|
||||
Image img, DetectedObjects detection, String name, String path) throws IOException {
|
||||
// Make imageName copy with alpha channel because original imageName was jpg
|
||||
img.drawBoundingBoxes(detection);
|
||||
Path outputDir = Paths.get(path);
|
||||
Files.createDirectories(outputDir);
|
||||
Path imagePath = outputDir.resolve(name);
|
||||
// OpenJDK can't save jpg with alpha channel
|
||||
img.save(Files.newOutputStream(imagePath), "png");
|
||||
}
|
||||
|
||||
public static void drawImageRect(BufferedImage image, int x, int y, int width, int height) {
|
||||
Graphics2D g = (Graphics2D) image.getGraphics();
|
||||
try {
|
||||
g.setColor(new Color(246, 96, 0));
|
||||
BasicStroke bStroke = new BasicStroke(4, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER);
|
||||
g.setStroke(bStroke);
|
||||
g.drawRect(x, y, width, height);
|
||||
|
||||
} finally {
|
||||
g.dispose();
|
||||
}
|
||||
}
|
||||
|
||||
public static void drawImageRect(
|
||||
BufferedImage image, int x, int y, int width, int height, Color c) {
|
||||
Graphics2D g = (Graphics2D) image.getGraphics();
|
||||
try {
|
||||
g.setColor(c);
|
||||
BasicStroke bStroke = new BasicStroke(4, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER);
|
||||
g.setStroke(bStroke);
|
||||
g.drawRect(x, y, width, height);
|
||||
|
||||
} finally {
|
||||
g.dispose();
|
||||
}
|
||||
}
|
||||
|
||||
public static void drawImageText(BufferedImage image, String text) {
|
||||
Graphics graphics = image.getGraphics();
|
||||
int fontSize = 100;
|
||||
Font font = new Font("楷体", Font.PLAIN, fontSize);
|
||||
try {
|
||||
graphics.setFont(font);
|
||||
graphics.setColor(new Color(246, 96, 0));
|
||||
int strWidth = graphics.getFontMetrics().stringWidth(text);
|
||||
graphics.drawString(text, fontSize - (strWidth / 2), fontSize + 30);
|
||||
} finally {
|
||||
graphics.dispose();
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,113 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import top.aias.iocr.bean.LabelBean;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.concurrent.ConcurrentHashMap;
|
||||
|
||||
/**
|
||||
* 距离计算工具类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class DistanceUtils {
|
||||
/**
|
||||
* Calculate L2 distance
|
||||
*
|
||||
* @param contentLabels 内容识别区 - the list of labels for content recognition area
|
||||
* @param detectedTexts 文本检测区 - the list of labels for text detection area
|
||||
* @return
|
||||
*/
|
||||
public static Map<String, String> l2Distance(List<LabelBean> contentLabels, List<LabelBean> detectedTexts) {
|
||||
Map<String, String> hashMap = new ConcurrentHashMap<>();
|
||||
for (int i = 0; i < contentLabels.size(); i++) {
|
||||
String field = contentLabels.get(i).getField();
|
||||
double minDistance = Double.MAX_VALUE;
|
||||
String value = "";
|
||||
for (int j = 0; j < detectedTexts.size(); j++) {
|
||||
double dis = l2Distance(contentLabels.get(i).getCenterPoint(), detectedTexts.get(j).getCenterPoint());
|
||||
if (dis < minDistance) {
|
||||
minDistance = dis;
|
||||
value = detectedTexts.get(j).getValue();
|
||||
}
|
||||
}
|
||||
System.out.println(field + " : " + value);
|
||||
hashMap.put(field, value);
|
||||
}
|
||||
return hashMap;
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate iou
|
||||
*
|
||||
* @param contentLabels 内容识别区 - the list of labels for content recognition area
|
||||
* @param detectedTexts 文本检测区 - the list of labels for text detection area
|
||||
* @return
|
||||
*/
|
||||
public static Map<String, String> iou(List<LabelBean> contentLabels, List<LabelBean> detectedTexts) {
|
||||
Map<String, String> hashMap = new ConcurrentHashMap<>();
|
||||
for (int i = 0; i < contentLabels.size(); i++) {
|
||||
String field = contentLabels.get(i).getField();
|
||||
double maxIOU = 0d;
|
||||
String value = "";
|
||||
int[] box_1 = PointUtils.rectXYXY(contentLabels.get(i).getPoints());
|
||||
for (int j = 0; j < detectedTexts.size(); j++) {
|
||||
int[] box_2 = PointUtils.rectXYXY(detectedTexts.get(j).getPoints());
|
||||
double iou = compute_iou(box_1, box_2);
|
||||
if (iou > maxIOU) {
|
||||
maxIOU = iou;
|
||||
value = detectedTexts.get(j).getValue();
|
||||
}
|
||||
}
|
||||
System.out.println(field + " : " + value);
|
||||
hashMap.put(field, value);
|
||||
}
|
||||
return hashMap;
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate L2 distance
|
||||
*
|
||||
* @param point1
|
||||
* @param point2
|
||||
* @return
|
||||
*/
|
||||
public static double l2Distance(ai.djl.modality.cv.output.Point point1, ai.djl.modality.cv.output.Point point2) {
|
||||
double partX = Math.pow((point1.getX() - point2.getX()), 2);
|
||||
double partY = Math.pow((point1.getY() - point2.getY()), 2);
|
||||
return Math.sqrt(partX + partY);
|
||||
}
|
||||
|
||||
/**
|
||||
* computing IoU
|
||||
*
|
||||
* @param rec1: (y0, x0, y1, x1), which reflects (top, left, bottom, right)
|
||||
* @param rec2: (y0, x0, y1, x1)
|
||||
* @return scala value of IoU
|
||||
*/
|
||||
public static float compute_iou(int[] rec1, int[] rec2) {
|
||||
// computing area of each rectangles
|
||||
int S_rec1 = (rec1[2] - rec1[0]) * (rec1[3] - rec1[1]);
|
||||
int S_rec2 = (rec2[2] - rec2[0]) * (rec2[3] - rec2[1]);
|
||||
|
||||
// computing the sum_area
|
||||
int sum_area = S_rec1 + S_rec2;
|
||||
|
||||
// find the each edge of intersect rectangle
|
||||
int left_line = Math.max(rec1[1], rec2[1]);
|
||||
int right_line = Math.min(rec1[3], rec2[3]);
|
||||
int top_line = Math.max(rec1[0], rec2[0]);
|
||||
int bottom_line = Math.min(rec1[2], rec2[2]);
|
||||
|
||||
// judge if there is an intersect
|
||||
if (left_line >= right_line || top_line >= bottom_line) {
|
||||
return 0.0f;
|
||||
} else {
|
||||
float intersect = (right_line - left_line) * (bottom_line - top_line);
|
||||
return (intersect / (sum_area - intersect)) * 1.0f;
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,139 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.util.Utils;
|
||||
import org.springframework.web.multipart.MultipartFile;
|
||||
|
||||
import java.io.*;
|
||||
import java.nio.file.Path;
|
||||
import java.nio.file.Paths;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 文件上传工具包
|
||||
* File upload tool package
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class FileUtils {
|
||||
/**
|
||||
* @param file 文件 - file
|
||||
* @param path 文件存放路径 - file storage path
|
||||
* @param fileName 源文件名 - source file name
|
||||
* @return
|
||||
*/
|
||||
public static boolean upload(MultipartFile file, String path, String fileName) {
|
||||
// 生成新的文件名
|
||||
// Generate a new file name
|
||||
//String realPath = path + "/" + FileNameUtils.getFileName(fileName);
|
||||
Path filePath = Paths.get(path + fileName);
|
||||
File dest = filePath.toAbsolutePath().toFile();
|
||||
|
||||
//判断文件父目录是否存在
|
||||
// Determine if the parent directory of the file exists
|
||||
if (!dest.getParentFile().exists()) {
|
||||
dest.getParentFile().mkdir();
|
||||
}
|
||||
|
||||
try {
|
||||
//保存文件
|
||||
// Save the file
|
||||
file.transferTo(dest);
|
||||
return true;
|
||||
} catch (IllegalStateException e) {
|
||||
e.printStackTrace();
|
||||
return false;
|
||||
} catch (IOException e) {
|
||||
e.printStackTrace();
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取文件后缀
|
||||
* Get file suffix
|
||||
*
|
||||
* @param fileName
|
||||
* @return
|
||||
*/
|
||||
public static String getSuffix(String fileName) {
|
||||
return fileName.substring(fileName.lastIndexOf("."));
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成新的文件名
|
||||
* Generate a new file name
|
||||
* @param fileOriginName 源文件名 - source file name
|
||||
* @return
|
||||
*/
|
||||
public static String getFileName(String fileOriginName) {
|
||||
return UUIDUtils.getUUID() + getSuffix(fileOriginName);
|
||||
}
|
||||
|
||||
/**
|
||||
* 读取json文件
|
||||
* Read json file
|
||||
*
|
||||
* @param path 文件路径信息 - file path information
|
||||
* @param fileName 文件名 - file name
|
||||
* @return
|
||||
*/
|
||||
public static String readFile(String path, String fileName) throws IOException {
|
||||
StringBuilder json = new StringBuilder();
|
||||
Path filePath = Paths.get(path + fileName);
|
||||
List<String> lines = Utils.readLines(filePath, true);
|
||||
lines.stream()
|
||||
.filter(line -> (line != null && line != ""))
|
||||
.forEach(
|
||||
line -> {
|
||||
json.append(line);
|
||||
});
|
||||
|
||||
return json.toString();
|
||||
}
|
||||
|
||||
/**
|
||||
* 保存json文件
|
||||
* Save json file
|
||||
*
|
||||
* @param path 文件路径信息 file path information
|
||||
* @param fileName 文件名 file name
|
||||
* @param json json信息 json information
|
||||
* @return
|
||||
*/
|
||||
public static void saveFile(String path, String fileName, String json) throws IOException {
|
||||
Path filePath = Paths.get(path + fileName);
|
||||
try (PrintStream ps = new PrintStream(new FileOutputStream(filePath.toFile()))) {
|
||||
ps.print(json);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除json文件
|
||||
* Delete json file
|
||||
*
|
||||
* @param path 文件路径信息 file path information
|
||||
* @param fileName 文件名 file name
|
||||
* @return
|
||||
*/
|
||||
public static void removeFile(String path, String fileName) {
|
||||
Path filePath = Paths.get(path + fileName);
|
||||
filePath.toFile().delete();
|
||||
}
|
||||
|
||||
/**
|
||||
* Check & create file path
|
||||
*
|
||||
* @param fileRelativePath 文件路径信息 - file path information
|
||||
* @return
|
||||
*/
|
||||
public static void checkAndCreatePath(String fileRelativePath) {
|
||||
//Check & create file path
|
||||
Path filePath = Paths.get(fileRelativePath).toAbsolutePath();
|
||||
File file = filePath.toFile();
|
||||
if (!file.exists() && !file.isDirectory()) {
|
||||
file.mkdirs();
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,263 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.ImageFactory;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.opencv.OpenCVImageFactory;
|
||||
import org.opencv.core.Mat;
|
||||
import org.opencv.core.Point;
|
||||
import org.opencv.core.Scalar;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
|
||||
import javax.imageio.ImageIO;
|
||||
import java.awt.*;
|
||||
import java.awt.image.BufferedImage;
|
||||
import java.io.ByteArrayOutputStream;
|
||||
import java.io.File;
|
||||
import java.io.IOException;
|
||||
import java.nio.file.Files;
|
||||
import java.nio.file.Path;
|
||||
import java.nio.file.Paths;
|
||||
import java.util.ArrayList;
|
||||
import java.util.Base64;
|
||||
import java.util.List;
|
||||
/**
|
||||
* 图像工具类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class ImageUtils {
|
||||
|
||||
/**
|
||||
* 保存BufferedImage图片
|
||||
*
|
||||
* @param bufferedImage
|
||||
* @param name
|
||||
* @param path
|
||||
*/
|
||||
public static void saveImage(BufferedImage bufferedImage, String name, String path) {
|
||||
try {
|
||||
Path outputDir = Paths.get(path);
|
||||
Path imagePath = outputDir.resolve(name);
|
||||
File output = imagePath.toFile();
|
||||
ImageIO.write(bufferedImage, "png", output);
|
||||
} catch (IOException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 保存DJL图片
|
||||
*
|
||||
* @param img
|
||||
* @param name
|
||||
* @param path
|
||||
*/
|
||||
public static void saveImage(Image img, String name, String path) {
|
||||
Path outputDir = Paths.get(path);
|
||||
Path imagePath = outputDir.resolve(name);
|
||||
// OpenJDK 不能保存 jpg 图片的 alpha channel
|
||||
try {
|
||||
img.save(Files.newOutputStream(imagePath), "png");
|
||||
} catch (IOException e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 保存图片,含检测框
|
||||
*
|
||||
* @param img
|
||||
* @param detection
|
||||
* @param name
|
||||
* @param path
|
||||
* @throws IOException
|
||||
*/
|
||||
public static void saveBoundingBoxImage(
|
||||
Image img, DetectedObjects detection, String name, String path) throws IOException {
|
||||
// Make image copy with alpha channel because original image was jpg
|
||||
img.drawBoundingBoxes(detection);
|
||||
Path outputDir = Paths.get(path);
|
||||
Files.createDirectories(outputDir);
|
||||
Path imagePath = outputDir.resolve(name);
|
||||
// OpenJDK can't save jpg with alpha channel
|
||||
img.save(Files.newOutputStream(imagePath), "png");
|
||||
}
|
||||
|
||||
/**
|
||||
* 画矩形
|
||||
*
|
||||
* @param mat
|
||||
* @param box
|
||||
* @return
|
||||
*/
|
||||
public static void drawRect(Mat mat, NDArray box) {
|
||||
|
||||
float[] points = box.toFloatArray();
|
||||
List<Point> list = new ArrayList<>();
|
||||
|
||||
for (int i = 0; i < 4; i++) {
|
||||
Point point = new Point((int) points[2 * i], (int) points[2 * i + 1]);
|
||||
list.add(point);
|
||||
}
|
||||
|
||||
Imgproc.line(mat, list.get(0), list.get(1), new Scalar(0, 255, 0), 1);
|
||||
Imgproc.line(mat, list.get(1), list.get(2), new Scalar(0, 255, 0), 1);
|
||||
Imgproc.line(mat, list.get(2), list.get(3), new Scalar(0, 255, 0), 1);
|
||||
Imgproc.line(mat, list.get(3), list.get(0), new Scalar(0, 255, 0), 1);
|
||||
}
|
||||
|
||||
/**
|
||||
* 画矩形
|
||||
*
|
||||
* @param mat
|
||||
* @param box
|
||||
* @return
|
||||
*/
|
||||
public static void drawRectWithText(Mat mat, NDArray box, String text) {
|
||||
|
||||
float[] points = box.toFloatArray();
|
||||
List<Point> list = new ArrayList<>();
|
||||
|
||||
for (int i = 0; i < 4; i++) {
|
||||
Point point = new Point((int) points[2 * i], (int) points[2 * i + 1]);
|
||||
list.add(point);
|
||||
}
|
||||
|
||||
Imgproc.line(mat, list.get(0), list.get(1), new Scalar(0, 255, 0), 1);
|
||||
Imgproc.line(mat, list.get(1), list.get(2), new Scalar(0, 255, 0), 1);
|
||||
Imgproc.line(mat, list.get(2), list.get(3), new Scalar(0, 255, 0), 1);
|
||||
Imgproc.line(mat, list.get(3), list.get(0), new Scalar(0, 255, 0), 1);
|
||||
// 中文乱码
|
||||
Imgproc.putText(mat, text, list.get(0), Imgproc.FONT_HERSHEY_SCRIPT_SIMPLEX, 1.0, new Scalar(0, 255, 0), 1);
|
||||
}
|
||||
|
||||
/**
|
||||
* 画检测框(有倾斜角)
|
||||
*
|
||||
* @param image
|
||||
* @param box
|
||||
*/
|
||||
public static void drawImageRect(BufferedImage image, NDArray box) {
|
||||
float[] points = box.toFloatArray();
|
||||
int[] xPoints = new int[5];
|
||||
int[] yPoints = new int[5];
|
||||
|
||||
for (int i = 0; i < 4; i++) {
|
||||
xPoints[i] = (int) points[2 * i];
|
||||
yPoints[i] = (int) points[2 * i + 1];
|
||||
}
|
||||
xPoints[4] = xPoints[0];
|
||||
yPoints[4] = yPoints[0];
|
||||
|
||||
// 将绘制图像转换为Graphics2D
|
||||
Graphics2D g = (Graphics2D) image.getGraphics();
|
||||
try {
|
||||
g.setColor(new Color(0, 255, 0));
|
||||
// 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角
|
||||
BasicStroke bStroke = new BasicStroke(4, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER);
|
||||
g.setStroke(bStroke);
|
||||
g.drawPolyline(xPoints, yPoints, 5); // xPoints, yPoints, nPoints
|
||||
} finally {
|
||||
g.dispose();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 画检测框(有倾斜角)和文本
|
||||
*
|
||||
* @param image
|
||||
* @param box
|
||||
* @param text
|
||||
*/
|
||||
public static void drawImageRectWithText(BufferedImage image, NDArray box, String text) {
|
||||
float[] points = box.toFloatArray();
|
||||
int[] xPoints = new int[5];
|
||||
int[] yPoints = new int[5];
|
||||
|
||||
for (int i = 0; i < 4; i++) {
|
||||
xPoints[i] = (int) points[2 * i];
|
||||
yPoints[i] = (int) points[2 * i + 1];
|
||||
}
|
||||
xPoints[4] = xPoints[0];
|
||||
yPoints[4] = yPoints[0];
|
||||
|
||||
// 将绘制图像转换为Graphics2D
|
||||
Graphics2D g = (Graphics2D) image.getGraphics();
|
||||
try {
|
||||
int fontSize = 32;
|
||||
Font font = new Font("楷体", Font.PLAIN, fontSize);
|
||||
g.setFont(font);
|
||||
g.setColor(new Color(0, 0, 255));
|
||||
// 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角
|
||||
BasicStroke bStroke = new BasicStroke(2, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER);
|
||||
g.setStroke(bStroke);
|
||||
g.drawPolyline(xPoints, yPoints, 5); // xPoints, yPoints, nPoints
|
||||
g.drawString(text, xPoints[0], yPoints[0]);
|
||||
} finally {
|
||||
g.dispose();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 画检测框
|
||||
*
|
||||
* @param image
|
||||
* @param x
|
||||
* @param y
|
||||
* @param width
|
||||
* @param height
|
||||
*/
|
||||
public static void drawImageRect(BufferedImage image, int x, int y, int width, int height) {
|
||||
// 将绘制图像转换为Graphics2D
|
||||
Graphics2D g = (Graphics2D) image.getGraphics();
|
||||
try {
|
||||
g.setColor(new Color(0, 255, 0));
|
||||
// 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角
|
||||
BasicStroke bStroke = new BasicStroke(2, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER);
|
||||
g.setStroke(bStroke);
|
||||
g.drawRect(x, y, width, height);
|
||||
} finally {
|
||||
g.dispose();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 显示文字
|
||||
*
|
||||
* @param image
|
||||
* @param text
|
||||
* @param x
|
||||
* @param y
|
||||
*/
|
||||
public static void drawImageText(BufferedImage image, String text, int x, int y) {
|
||||
Graphics graphics = image.getGraphics();
|
||||
int fontSize = 32;
|
||||
Font font = new Font("楷体", Font.PLAIN, fontSize);
|
||||
try {
|
||||
graphics.setFont(font);
|
||||
graphics.setColor(new Color(0, 0, 255));
|
||||
int strWidth = graphics.getFontMetrics().stringWidth(text);
|
||||
graphics.drawString(text, x, y);
|
||||
} finally {
|
||||
graphics.dispose();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* BufferedImage 转 base64
|
||||
* @param image
|
||||
* @param type - JPG、PNG、GIF、BMP 等
|
||||
* @return
|
||||
* @throws IOException
|
||||
*/
|
||||
public static String toBase64(BufferedImage image, String type) throws IOException {
|
||||
ByteArrayOutputStream baos = new ByteArrayOutputStream();
|
||||
ImageIO.write(image, "jpg", baos);
|
||||
byte[] bytes = baos.toByteArray();
|
||||
return Base64.getEncoder().encodeToString(bytes);
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,339 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.ndarray.index.NDIndex;
|
||||
import ai.djl.ndarray.types.DataType;
|
||||
import ai.djl.ndarray.types.Shape;
|
||||
import org.opencv.core.CvType;
|
||||
import org.opencv.core.Mat;
|
||||
import org.opencv.core.MatOfPoint;
|
||||
import org.opencv.core.Point;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
/**
|
||||
* NDArray Utils 工具类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class NDArrayUtils {
|
||||
/**
|
||||
* Sigmoid 激活函数
|
||||
*
|
||||
* @param input
|
||||
* @return
|
||||
*/
|
||||
public static NDArray Sigmoid(NDArray input) {
|
||||
// Sigmoid 函数，即f(x)=1/(1+e-x)
|
||||
return input.neg().exp().add(1).pow(-1);
|
||||
}
|
||||
|
||||
/**
|
||||
* np.arctan2和np.arctan都是计算反正切值的NumPy函数，但它们的参数和返回值不同。一般来说，np.arctan2的参数为(y, x)，
|
||||
* 返回值为[-π, π]之间的弧度值；而np.arctan的参数为x，返回值为[-π/2, π/2]之间的弧度值。两者之间的换算关系是：
|
||||
* np.arctan(y/x) = np.arctan2(y, x)（当x>0时），
|
||||
* 或 np.pi + np.arctan(y/x) = np.arctan2(y, x) （当x<0且y>=0时），
|
||||
* 或 np.pi - np.arctan(y/x) = np.arctan2(y, x) （当x<0且y<0时）。
|
||||
* @param y
|
||||
* @param x
|
||||
* @return
|
||||
*/
|
||||
public static NDArray arctan2(NDArray y, NDArray x) {
|
||||
NDArray x_neg = x.lt(0).toType(DataType.INT32, false);
|
||||
NDArray y_pos = y.gte(0).toType(DataType.INT32, false);
|
||||
NDArray y_neg = y.lt(0).toType(DataType.INT32, false);
|
||||
|
||||
NDArray theta = y.div(x).atan();
|
||||
// np.arctan(y/x) + np.pi = np.arctan2(y, x) （当x<0且y>=0时）
|
||||
theta = theta.add(x_neg.mul(y_pos).mul((float) Math.PI));
|
||||
// np.arctan(y/x) - np.pi = np.arctan2(y, x) （当x<0且y<0时）
|
||||
theta = theta.add(x_neg.mul(y_neg).mul(-(float) Math.PI));
|
||||
|
||||
theta = theta.mul(180).div((float) Math.PI);
|
||||
|
||||
return theta;
|
||||
}
|
||||
|
||||
/**
|
||||
* 最大池化
|
||||
*
|
||||
* @param manager
|
||||
* @param heat
|
||||
* @param ksize
|
||||
* @param stride
|
||||
* @param padding
|
||||
* @return
|
||||
*/
|
||||
public static NDArray maxPool(NDManager manager, NDArray heat, int ksize, int stride, int padding) {
|
||||
int rows = (int) (heat.getShape().get(0));
|
||||
int cols = (int) (heat.getShape().get(1));
|
||||
// hmax = F.max_pool2d( heat, (ksize, ksize), stride=1, padding=(ksize-1)//2)
|
||||
NDArray max_pool2d = manager.zeros(new Shape(rows + 2 * padding, cols + 2 * padding));
|
||||
max_pool2d.set(new NDIndex(padding + ":" + (rows + padding) + ","+ padding + ":" + (cols + padding)), heat);
|
||||
float[][] max_pool2d_arr = NDArrayUtils.floatNDArrayToArray(max_pool2d);
|
||||
float[][] arr = new float[rows][cols];
|
||||
|
||||
for (int row = 0; row < rows; row++) {
|
||||
for (int col = 0; col < cols; col++) {
|
||||
float max = max_pool2d_arr[row][col];
|
||||
for (int i = row; i < row + ksize; i++) {
|
||||
for (int j = col; j < col + ksize; j++) {
|
||||
if (max_pool2d_arr[i][j] > max) {
|
||||
max = max_pool2d_arr[i][j];
|
||||
}
|
||||
}
|
||||
}
|
||||
arr[row][col] = max;
|
||||
}
|
||||
}
|
||||
|
||||
NDArray hmax = manager.create(arr).reshape(rows, cols);
|
||||
return hmax;
|
||||
}
|
||||
|
||||
/**
|
||||
* mat To MatOfPoint
|
||||
*
|
||||
* @param mat
|
||||
* @return
|
||||
*/
|
||||
public static MatOfPoint matToMatOfPoint(Mat mat) {
|
||||
int rows = mat.rows();
|
||||
MatOfPoint matOfPoint = new MatOfPoint();
|
||||
|
||||
List<Point> list = new ArrayList<>();
|
||||
for (int i = 0; i < rows; i++) {
|
||||
Point point = new Point((float) mat.get(i, 0)[0], (float) mat.get(i, 1)[0]);
|
||||
list.add(point);
|
||||
}
|
||||
matOfPoint.fromList(list);
|
||||
|
||||
return matOfPoint;
|
||||
}
|
||||
|
||||
/**
|
||||
* int NDArray To int[][] Array
|
||||
*
|
||||
* @param ndArray
|
||||
* @return
|
||||
*/
|
||||
public static int[][] intNDArrayToArray(NDArray ndArray) {
|
||||
int rows = (int) (ndArray.getShape().get(0));
|
||||
int cols = (int) (ndArray.getShape().get(1));
|
||||
int[][] arr = new int[rows][cols];
|
||||
|
||||
int[] arrs = ndArray.toIntArray();
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
arr[i][j] = arrs[i * cols + j];
|
||||
}
|
||||
}
|
||||
return arr;
|
||||
}
|
||||
|
||||
/**
|
||||
* float NDArray To float[][] Array
|
||||
*
|
||||
* @param ndArray
|
||||
* @return
|
||||
*/
|
||||
public static float[][] floatNDArrayToArray(NDArray ndArray) {
|
||||
int rows = (int) (ndArray.getShape().get(0));
|
||||
int cols = (int) (ndArray.getShape().get(1));
|
||||
float[][] arr = new float[rows][cols];
|
||||
|
||||
float[] arrs = ndArray.toFloatArray();
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
arr[i][j] = arrs[i * cols + j];
|
||||
}
|
||||
}
|
||||
return arr;
|
||||
}
|
||||
|
||||
/**
|
||||
* mat To double[][] Array
|
||||
*
|
||||
* @param mat
|
||||
* @return
|
||||
*/
|
||||
public static double[][] matToDoubleArray(Mat mat) {
|
||||
int rows = mat.rows();
|
||||
int cols = mat.cols();
|
||||
|
||||
double[][] doubles = new double[rows][cols];
|
||||
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
doubles[i][j] = mat.get(i, j)[0];
|
||||
}
|
||||
}
|
||||
|
||||
return doubles;
|
||||
}
|
||||
|
||||
/**
|
||||
* mat To float[][] Array
|
||||
*
|
||||
* @param mat
|
||||
* @return
|
||||
*/
|
||||
public static float[][] matToFloatArray(Mat mat) {
|
||||
int rows = mat.rows();
|
||||
int cols = mat.cols();
|
||||
|
||||
float[][] floats = new float[rows][cols];
|
||||
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
floats[i][j] = (float) mat.get(i, j)[0];
|
||||
}
|
||||
}
|
||||
|
||||
return floats;
|
||||
}
|
||||
|
||||
/**
|
||||
* mat To byte[][] Array
|
||||
*
|
||||
* @param mat
|
||||
* @return
|
||||
*/
|
||||
public static byte[][] matToUint8Array(Mat mat) {
|
||||
int rows = mat.rows();
|
||||
int cols = mat.cols();
|
||||
|
||||
byte[][] bytes = new byte[rows][cols];
|
||||
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
bytes[i][j] = (byte) mat.get(i, j)[0];
|
||||
}
|
||||
}
|
||||
|
||||
return bytes;
|
||||
}
|
||||
|
||||
/**
|
||||
* float NDArray To Mat
|
||||
*
|
||||
* @param ndArray
|
||||
* @param cvType
|
||||
* @return
|
||||
*/
|
||||
public static Mat floatNDArrayToMat(NDArray ndArray, int cvType) {
|
||||
int rows = (int) (ndArray.getShape().get(0));
|
||||
int cols = (int) (ndArray.getShape().get(1));
|
||||
Mat mat = new Mat(rows, cols, cvType);
|
||||
|
||||
float[] arrs = ndArray.toFloatArray();
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
mat.put(i, j, arrs[i * cols + j]);
|
||||
}
|
||||
}
|
||||
return mat;
|
||||
}
|
||||
|
||||
/**
|
||||
* float NDArray To Mat
|
||||
*
|
||||
* @param ndArray
|
||||
* @return
|
||||
*/
|
||||
public static Mat floatNDArrayToMat(NDArray ndArray) {
|
||||
int rows = (int) (ndArray.getShape().get(0));
|
||||
int cols = (int) (ndArray.getShape().get(1));
|
||||
Mat mat = new Mat(rows, cols, CvType.CV_32F);
|
||||
|
||||
float[] arrs = ndArray.toFloatArray();
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
mat.put(i, j, arrs[i * cols + j]);
|
||||
}
|
||||
}
|
||||
|
||||
return mat;
|
||||
|
||||
}
|
||||
|
||||
/**
|
||||
* uint8 NDArray To Mat
|
||||
*
|
||||
* @param ndArray
|
||||
* @return
|
||||
*/
|
||||
public static Mat uint8NDArrayToMat(NDArray ndArray) {
|
||||
int rows = (int) (ndArray.getShape().get(0));
|
||||
int cols = (int) (ndArray.getShape().get(1));
|
||||
Mat mat = new Mat(rows, cols, CvType.CV_8U);
|
||||
|
||||
byte[] arrs = ndArray.toByteArray();
|
||||
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
mat.put(i, j, arrs[i * cols + j]);
|
||||
}
|
||||
}
|
||||
return mat;
|
||||
}
|
||||
|
||||
/**
|
||||
* float[][] Array To Mat
|
||||
* @param arr
|
||||
* @return
|
||||
*/
|
||||
public static Mat floatArrayToMat(float[][] arr) {
|
||||
int rows = arr.length;
|
||||
int cols = arr[0].length;
|
||||
Mat mat = new Mat(rows, cols, CvType.CV_32F);
|
||||
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
mat.put(i, j, arr[i][j]);
|
||||
}
|
||||
}
|
||||
|
||||
return mat;
|
||||
}
|
||||
|
||||
/**
|
||||
* uint8Array To Mat
|
||||
* @param arr
|
||||
* @return
|
||||
*/
|
||||
public static Mat uint8ArrayToMat(byte[][] arr) {
|
||||
int rows = arr.length;
|
||||
int cols = arr[0].length;
|
||||
Mat mat = new Mat(rows, cols, CvType.CV_8U);
|
||||
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
mat.put(i, j, arr[i][j]);
|
||||
}
|
||||
}
|
||||
|
||||
return mat;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* list 转 Mat
|
||||
*
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public static Mat toMat(List<ai.djl.modality.cv.output.Point> points) {
|
||||
Mat mat = new Mat(points.size(), 2, CvType.CV_32F);
|
||||
for (int i = 0; i < points.size(); i++) {
|
||||
ai.djl.modality.cv.output.Point point = points.get(i);
|
||||
mat.put(i, 0, (float) point.getX());
|
||||
mat.put(i, 1, (float) point.getY());
|
||||
}
|
||||
|
||||
return mat;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,247 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import top.aias.iocr.bean.Point;
|
||||
import org.opencv.core.CvType;
|
||||
import org.opencv.core.Mat;
|
||||
import org.opencv.core.MatOfPoint;
|
||||
import org.opencv.core.Scalar;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
|
||||
import java.awt.image.BufferedImage;
|
||||
import java.awt.image.DataBufferByte;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* OpenCV Utils 工具类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class OpenCVUtils {
|
||||
/**
|
||||
* Mat to BufferedImage
|
||||
*
|
||||
* @param mat
|
||||
* @return
|
||||
*/
|
||||
public static BufferedImage mat2Image(Mat mat) {
|
||||
int width = mat.width();
|
||||
int height = mat.height();
|
||||
byte[] data = new byte[width * height * (int) mat.elemSize()];
|
||||
Imgproc.cvtColor(mat, mat, 4);
|
||||
mat.get(0, 0, data);
|
||||
BufferedImage ret = new BufferedImage(width, height, 5);
|
||||
ret.getRaster().setDataElements(0, 0, width, height, data);
|
||||
return ret;
|
||||
}
|
||||
|
||||
/**
|
||||
* BufferedImage to Mat
|
||||
*
|
||||
* @param img
|
||||
* @return
|
||||
*/
|
||||
public static Mat image2Mat(BufferedImage img) {
|
||||
int width = img.getWidth();
|
||||
int height = img.getHeight();
|
||||
byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData();
|
||||
Mat mat = new Mat(height, width, CvType.CV_8UC3);
|
||||
mat.put(0, 0, data);
|
||||
return mat;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* list 转 Mat
|
||||
*
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public static Mat toMat(List<Point> points) {
|
||||
Mat mat = new Mat(points.size(), 2, CvType.CV_32F);
|
||||
for (int i = 0; i < points.size(); i++) {
|
||||
Point point = points.get(i);
|
||||
mat.put(i, 0, (float) point.getX());
|
||||
mat.put(i, 1, (float) point.getY());
|
||||
}
|
||||
|
||||
return mat;
|
||||
}
|
||||
|
||||
/**
|
||||
* 透视变换
|
||||
*
|
||||
* @param src
|
||||
* @param dst
|
||||
* @param warp_mat
|
||||
* @return
|
||||
*/
|
||||
public static Mat warpPerspective(Mat src, Mat dst, Mat warp_mat) {
|
||||
Mat dstClone = dst.clone();
|
||||
// org.opencv.core.Mat mat = new org.opencv.core.Mat(dst.rows(), dst.cols(), CvType.CV_8UC3);
|
||||
Imgproc.warpPerspective(src, dstClone, warp_mat, dst.size());
|
||||
return dstClone;
|
||||
}
|
||||
|
||||
/**
|
||||
* 透视变换
|
||||
*
|
||||
* @param src
|
||||
* @param srcPoints
|
||||
* @param dstPoints
|
||||
* @return
|
||||
*/
|
||||
public static Mat perspectiveTransform(Mat src, Mat srcPoints, Mat dstPoints) {
|
||||
Mat dst = src.clone();
|
||||
Mat warp_mat = Imgproc.getPerspectiveTransform(srcPoints, dstPoints);
|
||||
Imgproc.warpPerspective(src, dst, warp_mat, dst.size());
|
||||
warp_mat.release();
|
||||
|
||||
return dst;
|
||||
}
|
||||
|
||||
/**
|
||||
* 透视变换
|
||||
*
|
||||
* @param src
|
||||
* @param dst
|
||||
* @param srcPoints
|
||||
* @param dstPoints
|
||||
* @return
|
||||
*/
|
||||
public static Mat perspectiveTransform(Mat src, Mat dst, Mat srcPoints, Mat dstPoints) {
|
||||
Mat dstClone = dst.clone();
|
||||
Mat warp_mat = Imgproc.getPerspectiveTransform(srcPoints, dstPoints);
|
||||
Imgproc.warpPerspective(src, dstClone, warp_mat, dst.size());
|
||||
warp_mat.release();
|
||||
|
||||
return dstClone;
|
||||
}
|
||||
|
||||
/**
|
||||
* 图片裁剪
|
||||
*
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public static int[] imgCrop(float[] points) {
|
||||
int[] wh = new int[2];
|
||||
float[] lt = java.util.Arrays.copyOfRange(points, 0, 2);
|
||||
float[] rt = java.util.Arrays.copyOfRange(points, 2, 4);
|
||||
float[] rb = java.util.Arrays.copyOfRange(points, 4, 6);
|
||||
float[] lb = java.util.Arrays.copyOfRange(points, 6, 8);
|
||||
wh[0] = (int) Math.max(PointUtils.distance(lt, rt), PointUtils.distance(rb, lb));
|
||||
wh[1] = (int) Math.max(PointUtils.distance(lt, lb), PointUtils.distance(rt, rb));
|
||||
return wh;
|
||||
}
|
||||
|
||||
/**
|
||||
* 转正图片
|
||||
*
|
||||
* @param mat
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public static Mat perspectiveTransform(Mat mat, float[] points) {
|
||||
float[] lt = java.util.Arrays.copyOfRange(points, 0, 2);
|
||||
float[] rt = java.util.Arrays.copyOfRange(points, 2, 4);
|
||||
float[] rb = java.util.Arrays.copyOfRange(points, 4, 6);
|
||||
float[] lb = java.util.Arrays.copyOfRange(points, 6, 8);
|
||||
int img_crop_width = (int) Math.max(PointUtils.distance(lt, rt), PointUtils.distance(rb, lb));
|
||||
int img_crop_height = (int) Math.max(PointUtils.distance(lt, lb), PointUtils.distance(rt, rb));
|
||||
List<Point> srcPoints = new ArrayList<>();
|
||||
srcPoints.add(new Point((int)lt[0], (int)lt[1]));
|
||||
srcPoints.add(new Point((int)rt[0], (int)rt[1]));
|
||||
srcPoints.add(new Point((int)rb[0], (int)rb[1]));
|
||||
srcPoints.add(new Point((int)lb[0], (int)lb[1]));
|
||||
List<Point> dstPoints = new ArrayList<>();
|
||||
dstPoints.add(new Point(0, 0));
|
||||
dstPoints.add(new Point(img_crop_width, 0));
|
||||
dstPoints.add(new Point(img_crop_width, img_crop_height));
|
||||
dstPoints.add(new Point(0, img_crop_height));
|
||||
|
||||
Mat srcPoint2f = toMat(srcPoints);
|
||||
Mat dstPoint2f = toMat(dstPoints);
|
||||
|
||||
Mat cvMat = OpenCVUtils.perspectiveTransform(mat, srcPoint2f, dstPoint2f);
|
||||
srcPoint2f.release();
|
||||
dstPoint2f.release();
|
||||
return cvMat;
|
||||
}
|
||||
/**
|
||||
* 转正图片 - 废弃
|
||||
*
|
||||
* @param mat
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public Mat perspectiveTransformOld(Mat mat, float[] points) {
|
||||
List<org.opencv.core.Point> pointList = new ArrayList<>();
|
||||
float[][] srcArr = new float[4][2];
|
||||
float min_X = Float.MAX_VALUE;
|
||||
float min_Y = Float.MAX_VALUE;
|
||||
float max_X = -1;
|
||||
float max_Y = -1;
|
||||
|
||||
for (int j = 0; j < 4; j++) {
|
||||
org.opencv.core.Point pt = new org.opencv.core.Point(points[2 * j], points[2 * j + 1]);
|
||||
pointList.add(pt);
|
||||
srcArr[j][0] = points[2 * j];
|
||||
srcArr[j][1] = points[2 * j + 1];
|
||||
if (points[2 * j] > max_X) {
|
||||
max_X = points[2 * j];
|
||||
}
|
||||
if (points[2 * j] < min_X) {
|
||||
min_X = points[2 * j];
|
||||
}
|
||||
if (points[2 * j + 1] > max_Y) {
|
||||
max_Y = points[2 * j + 1];
|
||||
}
|
||||
if (points[2 * j + 1] < min_Y) {
|
||||
min_Y = points[2 * j + 1];
|
||||
}
|
||||
}
|
||||
|
||||
Mat src = NDArrayUtils.floatArrayToMat(srcArr);
|
||||
|
||||
float width = max_Y - min_Y;
|
||||
float height = max_X - min_X;
|
||||
|
||||
float[][] dstArr = new float[4][2];
|
||||
dstArr[0] = new float[]{0, 0};
|
||||
dstArr[1] = new float[]{width - 1, 0};
|
||||
dstArr[2] = new float[]{width - 1, height - 1};
|
||||
dstArr[3] = new float[]{0, height - 1};
|
||||
|
||||
Mat dst = NDArrayUtils.floatArrayToMat(dstArr);
|
||||
return OpenCVUtils.perspectiveTransform(mat, src, dst);
|
||||
}
|
||||
|
||||
/**
|
||||
* 画边框
|
||||
*
|
||||
* @param mat
|
||||
* @param squares
|
||||
* @param topK
|
||||
*/
|
||||
public static void drawSquares(Mat mat, NDArray squares, int topK) {
|
||||
for (int i = 0; i < topK; i++) {
|
||||
float[] points = squares.get(i).toFloatArray();
|
||||
List<MatOfPoint> matOfPoints = new ArrayList<>();
|
||||
MatOfPoint matOfPoint = new MatOfPoint();
|
||||
matOfPoints.add(matOfPoint);
|
||||
List<org.opencv.core.Point> pointList = new ArrayList<>();
|
||||
for (int j = 0; j < 4; j++) {
|
||||
org.opencv.core.Point pt = new org.opencv.core.Point(points[2 * j], points[2 * j + 1]);
|
||||
pointList.add(pt);
|
||||
Imgproc.circle(mat, pt, 10, new Scalar(0, 255, 255), -1);
|
||||
Imgproc.putText(mat, "" + j, pt, Imgproc.FONT_HERSHEY_SCRIPT_SIMPLEX, 1.0, new Scalar(0, 255, 0), 1);
|
||||
}
|
||||
matOfPoint.fromList(pointList);
|
||||
Imgproc.polylines(mat, matOfPoints, true, new Scalar(200, 200, 0), 5);
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,190 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.modality.cv.output.DetectedObjects;
|
||||
import ai.djl.modality.cv.output.Rectangle;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.opencv.OpenCVImageFactory;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import ai.djl.util.Pair;
|
||||
import top.aias.iocr.bean.LabelBean;
|
||||
import top.aias.iocr.bean.Point;
|
||||
import top.aias.iocr.bean.ProjBean;
|
||||
import top.aias.iocr.model.RecognitionModel;
|
||||
import org.opencv.core.Mat;
|
||||
|
||||
import java.awt.*;
|
||||
import java.awt.image.BufferedImage;
|
||||
import java.util.List;
|
||||
import java.util.*;
|
||||
|
||||
/**
|
||||
* 文本转正，根据四边形顶点的距离，多轮透视变换
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class PerspectiveTransform {
|
||||
/**
|
||||
* 文本检测,锚点识别区,内容识别区 - 计算中心点坐标，用于透视变换及距离计算
|
||||
*
|
||||
* @param manager
|
||||
* @param templateImg
|
||||
* @param recognitionModel
|
||||
* @param image
|
||||
* @param anchorlabels
|
||||
* @param contentLabels
|
||||
* @param fileRelativePath
|
||||
* @param distanceType
|
||||
* @param maxNum
|
||||
* @param disThreshold
|
||||
* @param save
|
||||
* @return
|
||||
* @throws TranslateException
|
||||
*/
|
||||
public static Map<String, String> recognize(NDManager manager, Image templateImg, RecognitionModel recognitionModel, Image image, List<LabelBean> anchorlabels, List<LabelBean> contentLabels, String fileRelativePath, String distanceType, int maxNum, double disThreshold, boolean save) throws TranslateException {
|
||||
// 锚点识别区 - 计算中心点坐标，用于透视变换及距离计算
|
||||
// Anchor recognition area - calculating the center point coordinates for perspective transformation
|
||||
for (int i = 0; i < anchorlabels.size(); i++) {
|
||||
List<Point> points = anchorlabels.get(i).getPoints();
|
||||
anchorlabels.get(i).setCenterPoint(PointUtils.getCenterPoint(points));
|
||||
}
|
||||
|
||||
// 文本转正，根据四边形顶点的距离，多轮透视变换，直到符合最小距离要求，或者达到最大次数上限
|
||||
Image finalImg = finalImg(manager, recognitionModel, templateImg, image, anchorlabels, fileRelativePath, maxNum, disThreshold, save);
|
||||
|
||||
// 转 BufferedImage 解决 Imgproc.putText 中文乱码问题
|
||||
org.opencv.core.Mat wrappedImage = (Mat) finalImg.getWrappedImage();
|
||||
BufferedImage bufferedImage = OpenCVUtils.mat2Image(wrappedImage);
|
||||
Color c = new Color(0, 255, 0);
|
||||
|
||||
// 文本检测 - 计算中心点坐标，用于距离计算
|
||||
// Text detection area
|
||||
List<LabelBean> detectedTexts = new ArrayList<>();
|
||||
DetectedObjects textDetections = recognitionModel.predict(finalImg);
|
||||
List<DetectedObjects.DetectedObject> dt_boxes = textDetections.items();
|
||||
for (DetectedObjects.DetectedObject item : dt_boxes) {
|
||||
LabelBean labelBean = new LabelBean();
|
||||
List<Point> points = new ArrayList<>();
|
||||
labelBean.setValue(item.getClassName());
|
||||
Rectangle rectangle = item.getBoundingBox().getBounds();
|
||||
|
||||
Iterable<ai.djl.modality.cv.output.Point> pathIterator = rectangle.getPath();
|
||||
for (Iterator iter = pathIterator.iterator(); iter.hasNext(); ) {
|
||||
Point point = new Point();
|
||||
ai.djl.modality.cv.output.Point djlPoint = (ai.djl.modality.cv.output.Point) iter.next();
|
||||
point.setX((int) (djlPoint.getX() * finalImg.getWidth()));
|
||||
point.setY((int) (djlPoint.getY() * finalImg.getHeight()));
|
||||
points.add(point);
|
||||
}
|
||||
|
||||
labelBean.setPoints(points);
|
||||
ai.djl.modality.cv.output.Point point = PointUtils.getCenterPoint(points);
|
||||
labelBean.setCenterPoint(point);
|
||||
detectedTexts.add(labelBean);
|
||||
|
||||
if (save) {
|
||||
DJLImageUtils.drawImageRect(bufferedImage, (int) point.getX(), (int) point.getY(), 4, 4);
|
||||
}
|
||||
}
|
||||
|
||||
// 内容识别区 - 计算中心点坐标，用于距离计算
|
||||
// Content recognition area - calculating the center point coordinates for distance calculation
|
||||
for (int i = 0; i < contentLabels.size(); i++) {
|
||||
List<Point> points = contentLabels.get(i).getPoints();
|
||||
ai.djl.modality.cv.output.Point point = PointUtils.getCenterPoint(points);
|
||||
contentLabels.get(i).setCenterPoint(point);
|
||||
|
||||
if (save) {
|
||||
DJLImageUtils.drawImageRect(bufferedImage, (int) point.getX(), (int) point.getY(), 4, 4, c);
|
||||
}
|
||||
}
|
||||
|
||||
if (save) {
|
||||
ImageUtils.saveImage(bufferedImage, "center_points_result.png", fileRelativePath);
|
||||
}
|
||||
|
||||
Map<String, String> hashMap;
|
||||
if (distanceType.equalsIgnoreCase("IoU")) {
|
||||
hashMap = DistanceUtils.iou(contentLabels, detectedTexts);
|
||||
} else {
|
||||
hashMap = DistanceUtils.l2Distance(contentLabels, detectedTexts);
|
||||
}
|
||||
|
||||
return hashMap;
|
||||
}
|
||||
|
||||
/**
|
||||
* 多轮透视变换，获得最后符合距离阈值的图片
|
||||
*
|
||||
* @param manager
|
||||
* @param recognitionModel
|
||||
* @param templateImg
|
||||
* @param targetImg
|
||||
* @param anchorlabels
|
||||
* @param fileRelativePath
|
||||
* @param maxNum
|
||||
* @param disThreshold
|
||||
* @param save
|
||||
* @return
|
||||
* @throws TranslateException
|
||||
*/
|
||||
public static Image finalImg(NDManager manager, RecognitionModel recognitionModel, Image templateImg, Image targetImg, List<LabelBean> anchorlabels, String fileRelativePath, int maxNum, double disThreshold, boolean save) throws TranslateException {
|
||||
List<ProjBean> projList = new ArrayList<>();
|
||||
Image origTargetImg = targetImg.duplicate();
|
||||
|
||||
for (int num = 0; num < maxNum; num++) {
|
||||
Pair pair = ProjUtils.projPointsPair(manager, recognitionModel, anchorlabels, targetImg);
|
||||
List<Point> srcQuadPoints = (List<Point>) pair.getKey();
|
||||
List<Point> dstQuadPoints = (List<Point>) pair.getValue();
|
||||
|
||||
// 计算距离
|
||||
double[] distances = new double[4];
|
||||
for (int i = 0; i < 4; i++) {
|
||||
distances[i] = PointUtils.distance(srcQuadPoints.get(i), dstQuadPoints.get(i));
|
||||
}
|
||||
|
||||
System.out.println(Arrays.toString(distances));
|
||||
|
||||
boolean pass = true;
|
||||
for (int i = 0; i < 4; i++) {
|
||||
if (distances[i] > disThreshold) {
|
||||
pass = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (!pass) {
|
||||
ProjBean projItemBean = ProjUtils.projTransform(srcQuadPoints, dstQuadPoints, templateImg, targetImg);
|
||||
targetImg = projItemBean.getImage();
|
||||
projList.add(projItemBean);
|
||||
|
||||
if (save) {
|
||||
ImageUtils.saveImage(projItemBean.getImage(), "perspectiveTransform_" + num + ".png", fileRelativePath);
|
||||
}
|
||||
} else {
|
||||
break;
|
||||
}
|
||||
}
|
||||
if (projList.size() > 0) {
|
||||
org.opencv.core.Mat warp_mat = projList.get(projList.size() - 1).getWarpMat();
|
||||
if (projList.size() > 1) {
|
||||
for (int i = projList.size() - 2; i >= 0; i--) {
|
||||
org.opencv.core.Mat matItem = projList.get(i).getWarpMat();
|
||||
warp_mat = warp_mat.matMul(matItem);
|
||||
}
|
||||
}
|
||||
org.opencv.core.Mat mat = OpenCVUtils.warpPerspective((Mat) origTargetImg.getWrappedImage(), (Mat) templateImg.getWrappedImage(), warp_mat);
|
||||
Image finalImg = OpenCVImageFactory.getInstance().fromImage(mat);
|
||||
|
||||
if (save) {
|
||||
ImageUtils.saveImage(finalImg, "perspectiveTransform_final.png", fileRelativePath);
|
||||
}
|
||||
|
||||
return finalImg;
|
||||
}else {
|
||||
return targetImg;
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,343 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.ndarray.NDArray;
|
||||
import ai.djl.ndarray.NDArrays;
|
||||
import ai.djl.ndarray.NDList;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.ndarray.types.Shape;
|
||||
import top.aias.iocr.bean.Point;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 点工具类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class PointUtils {
|
||||
/**
|
||||
* 计算两点距离
|
||||
* @param point1
|
||||
* @param point2
|
||||
* @return
|
||||
*/
|
||||
public static float distance(float[] point1, float[] point2) {
|
||||
float disX = point1[0] - point2[0];
|
||||
float disY = point1[1] - point2[1];
|
||||
float dis = (float) Math.sqrt(disX * disX + disY * disY);
|
||||
return dis;
|
||||
}
|
||||
|
||||
/**
|
||||
* 计算两点距离
|
||||
* @param point1
|
||||
* @param point2
|
||||
* @return
|
||||
*/
|
||||
public static float distance(Point point1, Point point2) {
|
||||
double disX = point1.getX() - point2.getX();
|
||||
double disY = point1.getY() - point2.getY();
|
||||
float dis = (float) Math.sqrt(disX * disX + disY * disY);
|
||||
return dis;
|
||||
}
|
||||
|
||||
/**
|
||||
* sort the points based on their x-coordinates
|
||||
* 顺时针排序
|
||||
*
|
||||
* @param pts
|
||||
* @return
|
||||
*/
|
||||
|
||||
private static NDArray order_points_clockwise(NDArray pts) {
|
||||
NDList list = new NDList();
|
||||
long[] indexes = pts.get(":, 0").argSort().toLongArray();
|
||||
|
||||
// grab the left-most and right-most points from the sorted
|
||||
// x-roodinate points
|
||||
Shape s1 = pts.getShape();
|
||||
NDArray leftMost1 = pts.get(indexes[0] + ",:");
|
||||
NDArray leftMost2 = pts.get(indexes[1] + ",:");
|
||||
NDArray leftMost = leftMost1.concat(leftMost2).reshape(2, 2);
|
||||
NDArray rightMost1 = pts.get(indexes[2] + ",:");
|
||||
NDArray rightMost2 = pts.get(indexes[3] + ",:");
|
||||
NDArray rightMost = rightMost1.concat(rightMost2).reshape(2, 2);
|
||||
|
||||
// now, sort the left-most coordinates according to their
|
||||
// y-coordinates so we can grab the top-left and bottom-left
|
||||
// points, respectively
|
||||
indexes = leftMost.get(":, 1").argSort().toLongArray();
|
||||
NDArray lt = leftMost.get(indexes[0] + ",:");
|
||||
NDArray lb = leftMost.get(indexes[1] + ",:");
|
||||
indexes = rightMost.get(":, 1").argSort().toLongArray();
|
||||
NDArray rt = rightMost.get(indexes[0] + ",:");
|
||||
NDArray rb = rightMost.get(indexes[1] + ",:");
|
||||
|
||||
list.add(lt);
|
||||
list.add(rt);
|
||||
list.add(rb);
|
||||
list.add(lb);
|
||||
|
||||
NDArray rect = NDArrays.concat(list).reshape(4, 2);
|
||||
return rect;
|
||||
}
|
||||
|
||||
/**
|
||||
* 计算四边形的面积
|
||||
* 根据海伦公式（Heron's formula）计算面积
|
||||
*
|
||||
* @param arr
|
||||
* @return
|
||||
*/
|
||||
public static double getQuadArea(NDManager manager, double[][] arr) {
|
||||
NDArray ndArray = manager.create(arr).reshape(4, 2);
|
||||
ndArray = order_points_clockwise(ndArray);
|
||||
double[] array = ndArray.toDoubleArray();
|
||||
|
||||
double x1 = array[0];
|
||||
double y1 = array[1];
|
||||
double x2 = array[2];
|
||||
double y2 = array[3];
|
||||
double x3 = array[4];
|
||||
double y3 = array[5];
|
||||
double x4 = array[6];
|
||||
double y4 = array[7];
|
||||
|
||||
double totalArea;
|
||||
if (isInTriangle(x2, y2, x3, y3, x4, y4, x1, y1)) { // 判断点 (x1, y1) 是否在三角形 (x2,y2)，(x3,y3)，(x4,y4) 内
|
||||
double area1 = getTriangleArea(x2, y2, x3, y3, x1, y1);
|
||||
double area2 = getTriangleArea(x2, y2, x4, y4, x1, y1);
|
||||
double area3 = getTriangleArea(x3, y3, x4, y4, x1, y1);
|
||||
totalArea = area1 + area2 + area3;
|
||||
} else if (isInTriangle(x1, y1, x3, y3, x4, y4, x2, y2)) {// 判断点 (x2, y2) 是否在三角形 (x1,y1)，(x3,y3)，(x4,y4) 内
|
||||
double area1 = getTriangleArea(x1, y1, x3, y3, x2, y2);
|
||||
double area2 = getTriangleArea(x1, y1, x4, y4, x2, y2);
|
||||
double area3 = getTriangleArea(x3, y3, x4, y4, x2, y2);
|
||||
totalArea = area1 + area2 + area3;
|
||||
} else if (isInTriangle(x1, y1, x2, y2, x4, y4, x3, y3)) {// 判断点 (x3, y3) 是否在三角形 (x1,y1)，(x2,y2)，(x4,y4) 内
|
||||
double area1 = getTriangleArea(x1, y1, x2, y2, x3, y3);
|
||||
double area2 = getTriangleArea(x1, y1, x4, y4, x3, y3);
|
||||
double area3 = getTriangleArea(x2, y2, x4, y4, x3, y3);
|
||||
totalArea = area1 + area2 + area3;
|
||||
} else if (isInTriangle(x1, y1, x2, y2, x3, y3, x4, y4)) {// 判断点 (x4, y4) 是否在三角形 (x1,y1)，(x2,y2)，(x3,y3) 内
|
||||
double area1 = getTriangleArea(x1, y1, x2, y2, x4, y4);
|
||||
double area2 = getTriangleArea(x1, y1, x3, y3, x4, y4);
|
||||
double area3 = getTriangleArea(x2, y2, x3, y3, x4, y4);
|
||||
totalArea = area1 + area2 + area3;
|
||||
} else {
|
||||
double area1 = getTriangleArea(x1, y1, x2, y2, x3, y3);
|
||||
double area2 = getTriangleArea(x1, y1, x3, y3, x4, y4);
|
||||
totalArea = area1 + area2;
|
||||
}
|
||||
|
||||
return totalArea;
|
||||
}
|
||||
|
||||
/**
|
||||
* 判断点 (px, py) 是否在三角形 (x1,y1)，(x2,y2)，(x3,y3) 内
|
||||
*
|
||||
* @param x1
|
||||
* @param y1
|
||||
* @param x2
|
||||
* @param y2
|
||||
* @param x3
|
||||
* @param y3
|
||||
* @param px
|
||||
* @param py
|
||||
* @return
|
||||
*/
|
||||
public static boolean isInTriangle(double x1, double y1, double x2, double y2, double x3, double y3, double px, double py) {
|
||||
if(!isTriangle(x1, y1, x2, y2, px, py))
|
||||
return false;
|
||||
double area1 = getTriangleArea(x1, y1, x2, y2, px, py);
|
||||
if(!isTriangle(x1, y1, x3, y3, px, py))
|
||||
return false;
|
||||
double area2 = getTriangleArea(x1, y1, x3, y3, px, py);
|
||||
if(!isTriangle(x2, y2, x3, y3, px, py))
|
||||
return false;
|
||||
double area3 = getTriangleArea(x2, y2, x3, y3, px, py);
|
||||
if(!isTriangle(x1, y1, x2, y2, x3, y3))
|
||||
return false;
|
||||
double totalArea = getTriangleArea(x1, y1, x2, y2, x3, y3);
|
||||
double delta = Math.abs(totalArea - (area1 + area2 + area3));
|
||||
if (delta < 1)
|
||||
return true;
|
||||
else
|
||||
return false;
|
||||
}
|
||||
|
||||
/**
|
||||
* 给定3个点坐标(x1,y1)，(x2,y2)，(x3,y3)，给出判断是否能组成三角形
|
||||
* @param x1
|
||||
* @param y1
|
||||
* @param x2
|
||||
* @param y2
|
||||
* @param x3
|
||||
* @param y3
|
||||
* @return
|
||||
*/
|
||||
public static boolean isTriangle(double x1, double y1, double x2, double y2, double x3, double y3) {
|
||||
double a = Math.sqrt(Math.pow(x1-x2, 2) + Math.pow(y1-y2, 2));
|
||||
double b = Math.sqrt(Math.pow(x1-x3, 2) + Math.pow(y1-y3, 2));
|
||||
double c = Math.sqrt(Math.pow(x2-x3, 2) + Math.pow(y2-y3, 2));
|
||||
return a + b > c && b + c > a && a + c > b;
|
||||
}
|
||||
|
||||
/**
|
||||
* 计算三角形的面积
|
||||
* 根据海伦公式（Heron's formula）计算三角形面积
|
||||
*
|
||||
* @param x1
|
||||
* @param y1
|
||||
* @param x2
|
||||
* @param y2
|
||||
* @param x3
|
||||
* @param y3
|
||||
* @return
|
||||
*/
|
||||
public static double getTriangleArea(double x1, double y1, double x2, double y2, double x3, double y3) {
|
||||
double a = Math.sqrt(Math.pow(x2 - x1, 2) + Math.pow(y2 - y1, 2));
|
||||
double b = Math.sqrt(Math.pow(x3 - x2, 2) + Math.pow(y3 - y2, 2));
|
||||
double c = Math.sqrt(Math.pow(x1 - x3, 2) + Math.pow(y1 - y3, 2));
|
||||
double p = (a + b + c) / 2;
|
||||
double area = Math.sqrt(p * (p - a) * (p - b) * (p - c));
|
||||
return area;
|
||||
}
|
||||
|
||||
public static ai.djl.modality.cv.output.Point getCenterPoint(List<Point> points) {
|
||||
double sumX = 0;
|
||||
double sumY = 0;
|
||||
|
||||
for (Point point : points) {
|
||||
sumX = sumX + point.getX();
|
||||
sumY = sumY + point.getY();
|
||||
}
|
||||
|
||||
ai.djl.modality.cv.output.Point centerPoint = new ai.djl.modality.cv.output.Point(sumX / 4, sumY / 4);
|
||||
return centerPoint;
|
||||
}
|
||||
|
||||
/**
|
||||
* 点坐标变换
|
||||
*
|
||||
* @param manager
|
||||
* @param mat
|
||||
* @param point
|
||||
* @return
|
||||
*/
|
||||
public static Point transformPoint(NDManager manager, org.opencv.core.Mat mat, Point point) {
|
||||
double[][] pointsArray = new double[3][3];
|
||||
for (int i = 0; i < 3; i++) {
|
||||
for (int j = 0; j < 3; j++) {
|
||||
pointsArray[i][j] = mat.get(i, j)[0];
|
||||
}
|
||||
}
|
||||
NDArray ndPoints = manager.create(pointsArray);
|
||||
|
||||
double[] vector = new double[3];
|
||||
vector[0] = point.getX();
|
||||
vector[1] = point.getY();
|
||||
vector[2] = 1f;
|
||||
NDArray vPoints = manager.create(vector);
|
||||
vPoints = vPoints.reshape(3, 1);
|
||||
NDArray result = ndPoints.matMul(vPoints);
|
||||
double[] dArray = result.toDoubleArray();
|
||||
if (dArray[2] != 0) {
|
||||
point.setX((int) (dArray[0] / dArray[2]));
|
||||
point.setY((int) (dArray[1] / dArray[2]));
|
||||
}
|
||||
|
||||
return point;
|
||||
}
|
||||
|
||||
/**
|
||||
* 坐标变换
|
||||
*
|
||||
* @param manager
|
||||
* @param mat
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public static List<Point> transformPoints(NDManager manager, org.opencv.core.Mat mat, List<Point> points) {
|
||||
int cols = mat.cols();
|
||||
int rows = mat.rows();
|
||||
double[][] pointsArray = new double[rows][cols];
|
||||
for (int i = 0; i < rows; i++) {
|
||||
for (int j = 0; j < cols; j++) {
|
||||
pointsArray[i][j] = mat.get(i, j)[0];
|
||||
}
|
||||
}
|
||||
NDArray ndPoints = manager.create(pointsArray);
|
||||
|
||||
double[] vector = new double[3];
|
||||
for (int i = 0; i < points.size(); i++) {
|
||||
vector[0] = points.get(i).getX();
|
||||
vector[1] = points.get(i).getY();
|
||||
vector[2] = 1f;
|
||||
NDArray vPoints = manager.create(vector);
|
||||
vPoints = vPoints.reshape(3, 1);
|
||||
NDArray result = ndPoints.matMul(vPoints);
|
||||
double[] dArray = result.toDoubleArray();
|
||||
if (dArray.length > 2) {
|
||||
if (dArray[2] != 0) {
|
||||
points.get(i).setX((int) (dArray[0] / dArray[2]));
|
||||
points.get(i).setY((int) (dArray[1] / dArray[2]));
|
||||
}
|
||||
} else {
|
||||
points.get(i).setX((int) (dArray[0]));
|
||||
points.get(i).setY((int) (dArray[1]));
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
return points;
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取左上角和有下角的坐标
|
||||
* Get (x1,y1,x2,y2) coordinations
|
||||
*
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public static int[] rectXYXY(List<Point> points) {
|
||||
int left = points.get(0).getX();
|
||||
int top = points.get(0).getY();
|
||||
int right = points.get(2).getX();
|
||||
int bottom = points.get(2).getY();
|
||||
return new int[]{left, top, right, bottom};
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取左上角的坐标，宽度，高度
|
||||
* Get (x1,y1,w,h) coordinations
|
||||
*
|
||||
* @param points
|
||||
* @return
|
||||
*/
|
||||
public static int[] rectXYWH(List<Point> points) {
|
||||
int minX = Integer.MAX_VALUE;
|
||||
int minY = Integer.MAX_VALUE;
|
||||
int maxX = Integer.MIN_VALUE;
|
||||
int maxY = Integer.MIN_VALUE;
|
||||
|
||||
for (Point point : points) {
|
||||
int x = point.getX();
|
||||
int y = point.getY();
|
||||
if (x < minX)
|
||||
minX = x;
|
||||
if (x > maxX)
|
||||
maxX = x;
|
||||
if (y < minY)
|
||||
minY = y;
|
||||
if (y > maxY)
|
||||
maxY = y;
|
||||
}
|
||||
|
||||
int w = maxX - minX;
|
||||
int h = maxY - minY;
|
||||
return new int[]{minX, minY, w, h};
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,159 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import ai.djl.modality.cv.Image;
|
||||
import ai.djl.ndarray.NDManager;
|
||||
import ai.djl.opencv.OpenCVImageFactory;
|
||||
import ai.djl.translate.TranslateException;
|
||||
import ai.djl.util.Pair;
|
||||
import top.aias.iocr.bean.LabelBean;
|
||||
import top.aias.iocr.bean.Point;
|
||||
import top.aias.iocr.bean.ProjBean;
|
||||
import top.aias.iocr.bean.RotatedBox;
|
||||
import top.aias.iocr.model.RecognitionModel;
|
||||
import org.opencv.core.Mat;
|
||||
import org.opencv.imgproc.Imgproc;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 透视变换工具类
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class ProjUtils {
|
||||
|
||||
/**
|
||||
* 获取图片对应2个4变形4对顶点
|
||||
*
|
||||
* @return
|
||||
*/
|
||||
|
||||
public static Pair<List<Point>, List<Point>> projPointsPair(NDManager manager, RecognitionModel recognitionModel, List<LabelBean> anchorlabels, Image targetImg) throws TranslateException {
|
||||
// 目标文本检测
|
||||
// Text detection area
|
||||
List<LabelBean> targetTexts = new ArrayList<>();
|
||||
List<RotatedBox> textDetections = recognitionModel.predict(manager, targetImg);
|
||||
for (RotatedBox rotatedBox : textDetections) {
|
||||
LabelBean labelBean = new LabelBean();
|
||||
List<Point> points = new ArrayList<>();
|
||||
labelBean.setValue(rotatedBox.getText());
|
||||
|
||||
float[] pointsArr = rotatedBox.getBox().toFloatArray();
|
||||
for (int i = 0; i < 4; i++) {
|
||||
Point point = new Point((int) pointsArr[2 * i], (int) pointsArr[2 * i + 1]);
|
||||
points.add(point);
|
||||
}
|
||||
|
||||
labelBean.setPoints(points);
|
||||
labelBean.setCenterPoint(PointUtils.getCenterPoint(points));
|
||||
targetTexts.add(labelBean);
|
||||
}
|
||||
|
||||
List<LabelBean> srcPoints = new ArrayList<>();
|
||||
List<LabelBean> dstPoints = new ArrayList<>();
|
||||
for (int i = 0; i < anchorlabels.size(); i++) {
|
||||
String anchorText = anchorlabels.get(i).getValue();
|
||||
for (int j = 0; j < targetTexts.size(); j++) {
|
||||
String detectedText = targetTexts.get(j).getValue();
|
||||
if (detectedText.equals(anchorText)) { // 根据实际情况，也可以改成 contains 之类的。
|
||||
dstPoints.add(anchorlabels.get(i));
|
||||
srcPoints.add(targetTexts.get(j));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
List<double[][]> srcPointsList = new ArrayList<>();
|
||||
List<double[][]> dstPointsList = new ArrayList<>();
|
||||
|
||||
for (int i = 0; i < srcPoints.size(); i++) {
|
||||
for (int j = i + 1; j < srcPoints.size(); j++) {
|
||||
for (int k = j + 1; k < srcPoints.size(); k++) {
|
||||
for (int l = k + 1; l < srcPoints.size(); l++) {
|
||||
double[][] srcArr = new double[4][2];
|
||||
srcArr[0][0] = srcPoints.get(i).getCenterPoint().getX();
|
||||
srcArr[0][1] = srcPoints.get(i).getCenterPoint().getY();
|
||||
srcArr[1][0] = srcPoints.get(j).getCenterPoint().getX();
|
||||
srcArr[1][1] = srcPoints.get(j).getCenterPoint().getY();
|
||||
srcArr[2][0] = srcPoints.get(k).getCenterPoint().getX();
|
||||
srcArr[2][1] = srcPoints.get(k).getCenterPoint().getY();
|
||||
srcArr[3][0] = srcPoints.get(l).getCenterPoint().getX();
|
||||
srcArr[3][1] = srcPoints.get(l).getCenterPoint().getY();
|
||||
srcPointsList.add(srcArr);
|
||||
|
||||
double[][] dstArr = new double[4][2];
|
||||
dstArr[0][0] = dstPoints.get(i).getCenterPoint().getX();
|
||||
dstArr[0][1] = dstPoints.get(i).getCenterPoint().getY();
|
||||
dstArr[1][0] = dstPoints.get(j).getCenterPoint().getX();
|
||||
dstArr[1][1] = dstPoints.get(j).getCenterPoint().getY();
|
||||
dstArr[2][0] = dstPoints.get(k).getCenterPoint().getX();
|
||||
dstArr[2][1] = dstPoints.get(k).getCenterPoint().getY();
|
||||
dstArr[3][0] = dstPoints.get(l).getCenterPoint().getX();
|
||||
dstArr[3][1] = dstPoints.get(l).getCenterPoint().getY();
|
||||
dstPointsList.add(dstArr);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 根据海伦公式（Heron's formula）计算4边形面积
|
||||
double maxArea = 0;
|
||||
int index = -1;
|
||||
for (int i = 0; i < dstPointsList.size(); i++) {
|
||||
double[][] dstArr = dstPointsList.get(i);
|
||||
double area = PointUtils.getQuadArea(manager, dstArr);
|
||||
if (area > maxArea) {
|
||||
maxArea = area;
|
||||
index = i;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
double[][] srcArr = srcPointsList.get(index);
|
||||
double[][] dstArr = dstPointsList.get(index);
|
||||
|
||||
List<Point> srcQuadPoints = new ArrayList<>();
|
||||
List<Point> dstQuadPoints = new ArrayList<>();
|
||||
for (int i = 0; i < 4; i++) {
|
||||
double x = srcArr[i][0];
|
||||
double y = srcArr[i][1];
|
||||
Point point1 = new Point((int) x, (int) y);
|
||||
srcQuadPoints.add(point1);
|
||||
|
||||
x = dstArr[i][0];
|
||||
y = dstArr[i][1];
|
||||
Point point2 = new Point((int) x, (int) y);
|
||||
dstQuadPoints.add(point2);
|
||||
}
|
||||
|
||||
return new Pair<>(srcQuadPoints, dstQuadPoints);
|
||||
}
|
||||
|
||||
/**
|
||||
* 透视变换
|
||||
*
|
||||
* @return
|
||||
*/
|
||||
|
||||
public static ProjBean projTransform(List<Point> srcQuadPoints, List<Point> dstQuadPoints, Image templateImg, Image targetImg) {
|
||||
Mat srcPoint2f = OpenCVUtils.toMat(srcQuadPoints);
|
||||
Mat dstPoint2f = OpenCVUtils.toMat(dstQuadPoints);
|
||||
|
||||
// 透视变换矩阵
|
||||
// perspective transformation
|
||||
Mat warp_mat = Imgproc.getPerspectiveTransform(srcPoint2f, dstPoint2f);
|
||||
|
||||
// 透视变换
|
||||
// perspective transformation
|
||||
Mat mat = OpenCVUtils.perspectiveTransform((Mat) targetImg.getWrappedImage(), (Mat) templateImg.getWrappedImage(), srcPoint2f, dstPoint2f);
|
||||
Image newImg = OpenCVImageFactory.getInstance().fromImage(mat);
|
||||
ProjBean projItemBean = new ProjBean();
|
||||
projItemBean.setImage(newImg);
|
||||
projItemBean.setWarpMat(warp_mat);
|
||||
|
||||
return projItemBean;
|
||||
}
|
||||
|
||||
}
|
||||
@ -0,0 +1,19 @@
|
||||
package top.aias.iocr.utils;
|
||||
|
||||
import java.util.UUID;
|
||||
|
||||
/**
|
||||
* 生成文件名
|
||||
* Generate file name
|
||||
*
|
||||
* @author Calvin
|
||||
* @mail 179209347@qq.com
|
||||
* @website www.aias.top
|
||||
*/
|
||||
public class UUIDUtils {
|
||||
|
||||
public static String getUUID() {
|
||||
return UUID.randomUUID().toString().replace("-", "");
|
||||
}
|
||||
|
||||
}
|
||||
11
6_web_app/iocr/ocr_backend/src/main/main.iml
Normal file
11
6_web_app/iocr/ocr_backend/src/main/main.iml
Normal file
@ -0,0 +1,11 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<module type="JAVA_MODULE" version="4">
|
||||
<component name="NewModuleRootManager" inherit-compiler-output="true">
|
||||
<exclude-output />
|
||||
<content url="file://$MODULE_DIR$">
|
||||
<sourceFolder url="file://$MODULE_DIR$/java" isTestSource="false" />
|
||||
</content>
|
||||
<orderEntry type="inheritedJdk" />
|
||||
<orderEntry type="sourceFolder" forTests="false" />
|
||||
</component>
|
||||
</module>
|
||||
@ -0,0 +1,19 @@
|
||||
# Server Port
|
||||
server:
|
||||
port: 8089
|
||||
tomcat:
|
||||
uri-encoding: UTF-8
|
||||
baseUri: http://127.0.0.1:${server.port}
|
||||
|
||||
model:
|
||||
# 设置为 CPU 核心数 (Core Number)
|
||||
poolSize: 4
|
||||
ocrv4:
|
||||
# server detection model URI
|
||||
det: /home/models/iocr/ch_PP-OCRv4_det_infer.zip
|
||||
# server recognition model URI
|
||||
rec: /home/models/iocr/ch_PP-OCRv4_rec_infer.zip
|
||||
mlsd:
|
||||
# mlsd model URI
|
||||
model: /home/models/ocr/mlsd_traced_model_onnx.zip
|
||||
|
||||
@ -0,0 +1,21 @@
|
||||
# Server Port
|
||||
server:
|
||||
port: 8089
|
||||
tomcat:
|
||||
uri-encoding: UTF-8
|
||||
baseUri: http://127.0.0.1:${server.port}
|
||||
|
||||
model:
|
||||
# 设置为 CPU 核心数 (Core Number)
|
||||
poolSize: 4
|
||||
ocrv4:
|
||||
# server detection model URI
|
||||
det: /Users/calvin/AIAS/6_web_app/iocr/ocr_backend/models/ch_PP-OCRv4_det_infer.zip
|
||||
# server recognition model URI
|
||||
rec: /Users/calvin/AIAS/6_web_app/iocr/ocr_backend/models/ch_PP-OCRv4_rec_infer.zip
|
||||
mlsd:
|
||||
# mlsd model URI
|
||||
model: /Users/calvin/AIAS/6_web_app/iocr/ocr_backend/models/mlsd_traced_model_onnx.zip
|
||||
|
||||
|
||||
|
||||
@ -0,0 +1,21 @@
|
||||
# Server Port
|
||||
server:
|
||||
port: 8089
|
||||
tomcat:
|
||||
uri-encoding: UTF-8
|
||||
baseUri: http://127.0.0.1:${server.port}
|
||||
|
||||
model:
|
||||
# 设置为 CPU 核心数 (Core Number)
|
||||
poolSize: 4
|
||||
ocrv4:
|
||||
# server detection model URI
|
||||
det: https://aias-home.oss-cn-beijing.aliyuncs.com/models/iocr/ch_PP-OCRv4_det_infer.zip
|
||||
# server recognition model URI
|
||||
rec: https://aias-home.oss-cn-beijing.aliyuncs.com/models/iocr/ch_PP-OCRv4_rec_infer.zip
|
||||
mlsd:
|
||||
# mlsd model URI
|
||||
model: https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr/mlsd_traced_model_onnx.zip
|
||||
|
||||
|
||||
|
||||
@ -0,0 +1,23 @@
|
||||
# Server Port
|
||||
server:
|
||||
port: 8089
|
||||
tomcat:
|
||||
uri-encoding: UTF-8
|
||||
baseUri: http://127.0.0.1:${server.port}
|
||||
|
||||
model:
|
||||
# 设置为 CPU 核心数 (Core Number)
|
||||
poolSize: 4
|
||||
ocrv4:
|
||||
# server detection model URI
|
||||
det: D:\\ai_projects\\products\\4_apps\\iocr\\ocr_backend\\models\\ch_PP-OCRv4_det_infer.zip
|
||||
# server recognition model URI
|
||||
rec: D:\\ai_projects\\products\\4_apps\\iocr\\ocr_backend\\models\\ch_PP-OCRv4_rec_infer.zip
|
||||
mlsd:
|
||||
# mlsd model URI
|
||||
model: D:\\ai_projects\\AIAS\\6_web_app\\ocr_web_app\\ocr_backend\\models\\mlsd_traced_model_onnx.zip
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@ -0,0 +1,46 @@
|
||||
|
||||
spring:
|
||||
profiles:
|
||||
active: mac
|
||||
servlet:
|
||||
multipart:
|
||||
enabled: true
|
||||
max-file-size: 30MB
|
||||
max-request-size: 30MB
|
||||
http:
|
||||
encoding:
|
||||
charset: utf-8
|
||||
enabled: true
|
||||
force: true
|
||||
messages:
|
||||
encoding: UTF-8
|
||||
|
||||
# Swagger-ui
|
||||
swagger:
|
||||
enabled: true
|
||||
|
||||
# File path
|
||||
file:
|
||||
mac:
|
||||
path: file/
|
||||
linux:
|
||||
path: file/
|
||||
windows:
|
||||
path: C:\\iocr\\file\\
|
||||
# File max size - MB
|
||||
maxSize: 100
|
||||
|
||||
|
||||
# Verify image transformation result
|
||||
image:
|
||||
debug: true
|
||||
# 设置图片摆正对齐透视变换次数的上限
|
||||
maxNum: 4
|
||||
# 4个锚点框对应的4边形的4个顶点，与待识别图片检测框对应的4个顶点距离
|
||||
disThreshold: 3
|
||||
|
||||
# distance calculation type: L2, IoU
|
||||
distance:
|
||||
type: IoU
|
||||
|
||||
|
||||
17
6_web_app/iocr/ocr_backend/src/main/resources/log4j2.xml
Normal file
17
6_web_app/iocr/ocr_backend/src/main/resources/log4j2.xml
Normal file
@ -0,0 +1,17 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Configuration status="INFO">
|
||||
<Appenders>
|
||||
<Console name="console" target="SYSTEM_OUT">
|
||||
<PatternLayout
|
||||
pattern="[%-5level] - %msg%n"/>
|
||||
</Console>
|
||||
</Appenders>
|
||||
<Loggers>
|
||||
<Root level="info" additivity="false">
|
||||
<AppenderRef ref="console"/>
|
||||
</Root>
|
||||
<Logger name="me.calvin" level="${sys:me.calvin.logging.level:-info}" additivity="false">
|
||||
<AppenderRef ref="console"/>
|
||||
</Logger>
|
||||
</Loggers>
|
||||
</Configuration>
|
||||
12
6_web_app/iocr/ocr_backend/src/test/test.iml
Normal file
12
6_web_app/iocr/ocr_backend/src/test/test.iml
Normal file
@ -0,0 +1,12 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<module type="JAVA_MODULE" version="4">
|
||||
<component name="NewModuleRootManager" inherit-compiler-output="true">
|
||||
<exclude-output />
|
||||
<content url="file://$MODULE_DIR$">
|
||||
<sourceFolder url="file://$MODULE_DIR$/java" isTestSource="true" />
|
||||
</content>
|
||||
<orderEntry type="inheritedJdk" />
|
||||
<orderEntry type="sourceFolder" forTests="false" />
|
||||
<orderEntry type="module" module-name="main" />
|
||||
</component>
|
||||
</module>
|
||||
14
6_web_app/iocr/ocr_ui/.editorconfig
Normal file
14
6_web_app/iocr/ocr_ui/.editorconfig
Normal file
@ -0,0 +1,14 @@
|
||||
# http://editorconfig.org
|
||||
root = true
|
||||
|
||||
[*]
|
||||
charset = utf-8
|
||||
indent_style = space
|
||||
indent_size = 2
|
||||
end_of_line = lf
|
||||
insert_final_newline = true
|
||||
trim_trailing_whitespace = true
|
||||
|
||||
[*.md]
|
||||
insert_final_newline = false
|
||||
trim_trailing_whitespace = false
|
||||
6
6_web_app/iocr/ocr_ui/.env.development
Normal file
6
6_web_app/iocr/ocr_ui/.env.development
Normal file
@ -0,0 +1,6 @@
|
||||
# just a flag
|
||||
ENV = 'development'
|
||||
|
||||
# base api 127.0.0.1
|
||||
VUE_APP_BASE_API = 'http://121.41.167.160:8089'
|
||||
|
||||
6
6_web_app/iocr/ocr_ui/.env.production
Normal file
6
6_web_app/iocr/ocr_ui/.env.production
Normal file
@ -0,0 +1,6 @@
|
||||
# just a flag
|
||||
ENV = 'production'
|
||||
|
||||
# base api 127.0.0.1
|
||||
VUE_APP_BASE_API = 'http://121.41.167.160:8089'
|
||||
|
||||
8
6_web_app/iocr/ocr_ui/.env.staging
Normal file
8
6_web_app/iocr/ocr_ui/.env.staging
Normal file
@ -0,0 +1,8 @@
|
||||
NODE_ENV = production
|
||||
|
||||
# just a flag
|
||||
ENV = 'staging'
|
||||
|
||||
# base api
|
||||
VUE_APP_BASE_API = '/stage-api'
|
||||
|
||||
4
6_web_app/iocr/ocr_ui/.eslintignore
Normal file
4
6_web_app/iocr/ocr_ui/.eslintignore
Normal file
@ -0,0 +1,4 @@
|
||||
build/*.js
|
||||
src/assets
|
||||
public
|
||||
dist
|
||||
198
6_web_app/iocr/ocr_ui/.eslintrc.js
Normal file
198
6_web_app/iocr/ocr_ui/.eslintrc.js
Normal file
@ -0,0 +1,198 @@
|
||||
module.exports = {
|
||||
root: true,
|
||||
parserOptions: {
|
||||
parser: 'babel-eslint',
|
||||
sourceType: 'module'
|
||||
},
|
||||
env: {
|
||||
browser: true,
|
||||
node: true,
|
||||
es6: true,
|
||||
},
|
||||
extends: ['plugin:vue/recommended', 'eslint:recommended'],
|
||||
|
||||
// add your custom rules here
|
||||
//it is base on https://github.com/vuejs/eslint-config-vue
|
||||
rules: {
|
||||
"vue/max-attributes-per-line": [2, {
|
||||
"singleline": 10,
|
||||
"multiline": {
|
||||
"max": 1,
|
||||
"allowFirstLine": false
|
||||
}
|
||||
}],
|
||||
"vue/singleline-html-element-content-newline": "off",
|
||||
"vue/multiline-html-element-content-newline":"off",
|
||||
"vue/name-property-casing": ["error", "PascalCase"],
|
||||
"vue/no-v-html": "off",
|
||||
'accessor-pairs': 2,
|
||||
'arrow-spacing': [2, {
|
||||
'before': true,
|
||||
'after': true
|
||||
}],
|
||||
'block-spacing': [2, 'always'],
|
||||
'brace-style': [2, '1tbs', {
|
||||
'allowSingleLine': true
|
||||
}],
|
||||
'camelcase': [0, {
|
||||
'properties': 'always'
|
||||
}],
|
||||
'comma-dangle': [2, 'never'],
|
||||
'comma-spacing': [2, {
|
||||
'before': false,
|
||||
'after': true
|
||||
}],
|
||||
'comma-style': [2, 'last'],
|
||||
'constructor-super': 2,
|
||||
'curly': [2, 'multi-line'],
|
||||
'dot-location': [2, 'property'],
|
||||
'eol-last': 2,
|
||||
'eqeqeq': ["error", "always", {"null": "ignore"}],
|
||||
'generator-star-spacing': [2, {
|
||||
'before': true,
|
||||
'after': true
|
||||
}],
|
||||
'handle-callback-err': [2, '^(err|error)$'],
|
||||
'indent': [2, 2, {
|
||||
'SwitchCase': 1
|
||||
}],
|
||||
'jsx-quotes': [2, 'prefer-single'],
|
||||
'key-spacing': [2, {
|
||||
'beforeColon': false,
|
||||
'afterColon': true
|
||||
}],
|
||||
'keyword-spacing': [2, {
|
||||
'before': true,
|
||||
'after': true
|
||||
}],
|
||||
'new-cap': [2, {
|
||||
'newIsCap': true,
|
||||
'capIsNew': false
|
||||
}],
|
||||
'new-parens': 2,
|
||||
'no-array-constructor': 2,
|
||||
'no-caller': 2,
|
||||
'no-console': 'off',
|
||||
'no-class-assign': 2,
|
||||
'no-cond-assign': 2,
|
||||
'no-const-assign': 2,
|
||||
'no-control-regex': 0,
|
||||
'no-delete-var': 2,
|
||||
'no-dupe-args': 2,
|
||||
'no-dupe-class-members': 2,
|
||||
'no-dupe-keys': 2,
|
||||
'no-duplicate-case': 2,
|
||||
'no-empty-character-class': 2,
|
||||
'no-empty-pattern': 2,
|
||||
'no-eval': 2,
|
||||
'no-ex-assign': 2,
|
||||
'no-extend-native': 2,
|
||||
'no-extra-bind': 2,
|
||||
'no-extra-boolean-cast': 2,
|
||||
'no-extra-parens': [2, 'functions'],
|
||||
'no-fallthrough': 2,
|
||||
'no-floating-decimal': 2,
|
||||
'no-func-assign': 2,
|
||||
'no-implied-eval': 2,
|
||||
'no-inner-declarations': [2, 'functions'],
|
||||
'no-invalid-regexp': 2,
|
||||
'no-irregular-whitespace': 2,
|
||||
'no-iterator': 2,
|
||||
'no-label-var': 2,
|
||||
'no-labels': [2, {
|
||||
'allowLoop': false,
|
||||
'allowSwitch': false
|
||||
}],
|
||||
'no-lone-blocks': 2,
|
||||
'no-mixed-spaces-and-tabs': 2,
|
||||
'no-multi-spaces': 2,
|
||||
'no-multi-str': 2,
|
||||
'no-multiple-empty-lines': [2, {
|
||||
'max': 1
|
||||
}],
|
||||
'no-native-reassign': 2,
|
||||
'no-negated-in-lhs': 2,
|
||||
'no-new-object': 2,
|
||||
'no-new-require': 2,
|
||||
'no-new-symbol': 2,
|
||||
'no-new-wrappers': 2,
|
||||
'no-obj-calls': 2,
|
||||
'no-octal': 2,
|
||||
'no-octal-escape': 2,
|
||||
'no-path-concat': 2,
|
||||
'no-proto': 2,
|
||||
'no-redeclare': 2,
|
||||
'no-regex-spaces': 2,
|
||||
'no-return-assign': [2, 'except-parens'],
|
||||
'no-self-assign': 2,
|
||||
'no-self-compare': 2,
|
||||
'no-sequences': 2,
|
||||
'no-shadow-restricted-names': 2,
|
||||
'no-spaced-func': 2,
|
||||
'no-sparse-arrays': 2,
|
||||
'no-this-before-super': 2,
|
||||
'no-throw-literal': 2,
|
||||
'no-trailing-spaces': 2,
|
||||
'no-undef': 2,
|
||||
'no-undef-init': 2,
|
||||
'no-unexpected-multiline': 2,
|
||||
'no-unmodified-loop-condition': 2,
|
||||
'no-unneeded-ternary': [2, {
|
||||
'defaultAssignment': false
|
||||
}],
|
||||
'no-unreachable': 2,
|
||||
'no-unsafe-finally': 2,
|
||||
'no-unused-vars': [2, {
|
||||
'vars': 'all',
|
||||
'args': 'none'
|
||||
}],
|
||||
'no-useless-call': 2,
|
||||
'no-useless-computed-key': 2,
|
||||
'no-useless-constructor': 2,
|
||||
'no-useless-escape': 0,
|
||||
'no-whitespace-before-property': 2,
|
||||
'no-with': 2,
|
||||
'one-var': [2, {
|
||||
'initialized': 'never'
|
||||
}],
|
||||
'operator-linebreak': [2, 'after', {
|
||||
'overrides': {
|
||||
'?': 'before',
|
||||
':': 'before'
|
||||
}
|
||||
}],
|
||||
'padded-blocks': [2, 'never'],
|
||||
'quotes': [2, 'single', {
|
||||
'avoidEscape': true,
|
||||
'allowTemplateLiterals': true
|
||||
}],
|
||||
'semi': [2, 'never'],
|
||||
'semi-spacing': [2, {
|
||||
'before': false,
|
||||
'after': true
|
||||
}],
|
||||
'space-before-blocks': [2, 'always'],
|
||||
'space-before-function-paren': [2, 'never'],
|
||||
'space-in-parens': [2, 'never'],
|
||||
'space-infix-ops': 2,
|
||||
'space-unary-ops': [2, {
|
||||
'words': true,
|
||||
'nonwords': false
|
||||
}],
|
||||
'spaced-comment': [2, 'always', {
|
||||
'markers': ['global', 'globals', 'eslint', 'eslint-disable', '*package', '!', ',']
|
||||
}],
|
||||
'template-curly-spacing': [2, 'never'],
|
||||
'use-isnan': 2,
|
||||
'valid-typeof': 2,
|
||||
'wrap-iife': [2, 'any'],
|
||||
'yield-star-spacing': [2, 'both'],
|
||||
'yoda': [2, 'never'],
|
||||
'prefer-const': 2,
|
||||
'no-debugger': process.env.NODE_ENV === 'production' ? 2 : 0,
|
||||
'object-curly-spacing': [2, 'always', {
|
||||
objectsInObjects: false
|
||||
}],
|
||||
'array-bracket-spacing': [2, 'never']
|
||||
}
|
||||
}
|
||||
5
6_web_app/iocr/ocr_ui/.travis.yml
Normal file
5
6_web_app/iocr/ocr_ui/.travis.yml
Normal file
@ -0,0 +1,5 @@
|
||||
language: node_js
|
||||
node_js: 10
|
||||
script: npm run test
|
||||
notifications:
|
||||
email: false
|
||||
14
6_web_app/iocr/ocr_ui/babel.config.js
Normal file
14
6_web_app/iocr/ocr_ui/babel.config.js
Normal file
@ -0,0 +1,14 @@
|
||||
module.exports = {
|
||||
presets: [
|
||||
// https://github.com/vuejs/vue-cli/tree/master/packages/@vue/babel-preset-app
|
||||
'@vue/cli-plugin-babel/preset'
|
||||
],
|
||||
'env': {
|
||||
'development': {
|
||||
// babel-plugin-dynamic-import-node plugin only does one thing by converting all import() to require().
|
||||
// This plugin can significantly increase the speed of hot updates, when you have a large number of pages.
|
||||
// https://panjiachen.github.io/vue-element-admin-site/guide/advanced/lazy-loading.html
|
||||
'plugins': ['dynamic-import-node']
|
||||
}
|
||||
}
|
||||
}
|
||||
35
6_web_app/iocr/ocr_ui/build/index.js
Normal file
35
6_web_app/iocr/ocr_ui/build/index.js
Normal file
@ -0,0 +1,35 @@
|
||||
const { run } = require('runjs')
|
||||
const chalk = require('chalk')
|
||||
const config = require('../vue.config.js')
|
||||
const rawArgv = process.argv.slice(2)
|
||||
const args = rawArgv.join(' ')
|
||||
|
||||
if (process.env.npm_config_preview || rawArgv.includes('--preview')) {
|
||||
const report = rawArgv.includes('--report')
|
||||
|
||||
run(`vue-cli-service build ${args}`)
|
||||
|
||||
const port = 9526
|
||||
const publicPath = config.publicPath
|
||||
|
||||
var connect = require('connect')
|
||||
var serveStatic = require('serve-static')
|
||||
const app = connect()
|
||||
|
||||
app.use(
|
||||
publicPath,
|
||||
serveStatic('./dist', {
|
||||
index: ['index.html', '/']
|
||||
})
|
||||
)
|
||||
|
||||
app.listen(port, function () {
|
||||
console.log(chalk.green(`> Preview at http://localhost:${port}${publicPath}`))
|
||||
if (report) {
|
||||
console.log(chalk.green(`> Report at http://localhost:${port}${publicPath}report.html`))
|
||||
}
|
||||
|
||||
})
|
||||
} else {
|
||||
run(`vue-cli-service build ${args}`)
|
||||
}
|
||||
24
6_web_app/iocr/ocr_ui/jest.config.js
Normal file
24
6_web_app/iocr/ocr_ui/jest.config.js
Normal file
@ -0,0 +1,24 @@
|
||||
module.exports = {
|
||||
moduleFileExtensions: ['js', 'jsx', 'json', 'vue'],
|
||||
transform: {
|
||||
'^.+\\.vue$': 'vue-jest',
|
||||
'.+\\.(css|styl|less|sass|scss|svg|png|jpg|ttf|woff|woff2)$':
|
||||
'jest-transform-stub',
|
||||
'^.+\\.jsx?$': 'babel-jest'
|
||||
},
|
||||
moduleNameMapper: {
|
||||
'^@/(.*)$': '<rootDir>/src/$1'
|
||||
},
|
||||
snapshotSerializers: ['jest-serializer-vue'],
|
||||
testMatch: [
|
||||
'**/tests/unit/**/*.spec.(js|jsx|ts|tsx)|**/__tests__/*.(js|jsx|ts|tsx)'
|
||||
],
|
||||
collectCoverageFrom: ['src/utils/**/*.{js,vue}', '!src/utils/auth.js', '!src/utils/request.js', 'src/components/**/*.{js,vue}'],
|
||||
coverageDirectory: '<rootDir>/tests/unit/coverage',
|
||||
// 'collectCoverage': true,
|
||||
'coverageReporters': [
|
||||
'lcov',
|
||||
'text-summary'
|
||||
],
|
||||
testURL: 'http://localhost/'
|
||||
}
|
||||
9
6_web_app/iocr/ocr_ui/jsconfig.json
Normal file
9
6_web_app/iocr/ocr_ui/jsconfig.json
Normal file
@ -0,0 +1,9 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"baseUrl": "./",
|
||||
"paths": {
|
||||
"@/*": ["src/*"]
|
||||
}
|
||||
},
|
||||
"exclude": ["node_modules", "dist"]
|
||||
}
|
||||
85
6_web_app/iocr/ocr_ui/nginx.conf
Normal file
85
6_web_app/iocr/ocr_ui/nginx.conf
Normal file
@ -0,0 +1,85 @@
|
||||
user www-data;
|
||||
worker_processes auto;
|
||||
pid /run/nginx.pid;
|
||||
include /etc/nginx/modules-enabled/*.conf;
|
||||
|
||||
events {
|
||||
worker_connections 768;
|
||||
# multi_accept on;
|
||||
}
|
||||
|
||||
http {
|
||||
|
||||
##
|
||||
# Basic Settings
|
||||
##
|
||||
|
||||
sendfile on;
|
||||
tcp_nopush on;
|
||||
tcp_nodelay on;
|
||||
keepalive_timeout 65;
|
||||
types_hash_max_size 2048;
|
||||
# server_tokens off;
|
||||
|
||||
# server_names_hash_bucket_size 64;
|
||||
# server_name_in_redirect off;
|
||||
|
||||
include /etc/nginx/mime.types;
|
||||
default_type application/octet-stream;
|
||||
|
||||
##
|
||||
# SSL Settings
|
||||
##
|
||||
|
||||
ssl_protocols TLSv1 TLSv1.1 TLSv1.2; # Dropping SSLv3, ref: POODLE
|
||||
ssl_prefer_server_ciphers on;
|
||||
|
||||
##
|
||||
# Logging Settings
|
||||
##
|
||||
|
||||
access_log /var/log/nginx/access.log;
|
||||
error_log /var/log/nginx/error.log;
|
||||
|
||||
##
|
||||
# Gzip Settings
|
||||
##
|
||||
|
||||
gzip on;
|
||||
|
||||
# gzip_vary on;
|
||||
# gzip_proxied any;
|
||||
# gzip_comp_level 6;
|
||||
# gzip_buffers 16 8k;
|
||||
# gzip_http_version 1.1;
|
||||
# gzip_types text/plain text/css application/json application/javascript text/xml application/xml application/xml+rss text/javascript;
|
||||
|
||||
##
|
||||
# Virtual Host Configs
|
||||
##
|
||||
|
||||
include /etc/nginx/conf.d/*.conf;
|
||||
include /etc/nginx/sites-enabled/*;
|
||||
}
|
||||
|
||||
|
||||
#mail {
|
||||
# # See sample authentication script at:
|
||||
# # http://wiki.nginx.org/ImapAuthenticateWithApachePhpScript
|
||||
#
|
||||
# # auth_http localhost/auth.php;
|
||||
# # pop3_capabilities "TOP" "USER";
|
||||
# # imap_capabilities "IMAP4rev1" "UIDPLUS";
|
||||
#
|
||||
# server {
|
||||
# listen localhost:110;
|
||||
# protocol pop3;
|
||||
# proxy on;
|
||||
# }
|
||||
#
|
||||
# server {
|
||||
# listen localhost:143;
|
||||
# protocol imap;
|
||||
# proxy on;
|
||||
# }
|
||||
#}
|
||||
65
6_web_app/iocr/ocr_ui/package.json
Normal file
65
6_web_app/iocr/ocr_ui/package.json
Normal file
@ -0,0 +1,65 @@
|
||||
{
|
||||
"name": "iocr-ui",
|
||||
"version": "1.0.0",
|
||||
"description": "IOCR UI",
|
||||
"author": "Calvin <179209347@qq.com>",
|
||||
"scripts": {
|
||||
"dev": "vue-cli-service serve",
|
||||
"build:prod": "vue-cli-service build",
|
||||
"build:stage": "vue-cli-service build --mode staging",
|
||||
"preview": "node build/index.js --preview",
|
||||
"lint": "eslint --ext .js,.vue src",
|
||||
"test:unit": "jest --clearCache && vue-cli-service test:unit",
|
||||
"test:ci": "npm run lint && npm run test:unit"
|
||||
},
|
||||
"dependencies": {
|
||||
"axios": "0.18.1",
|
||||
"core-js": "3.6.5",
|
||||
"easy-circular-progress": "1.0.4",
|
||||
"echarts": "^4.2.1",
|
||||
"element-ui": "2.13.2",
|
||||
"js-base64": "^2.6.4",
|
||||
"js-cookie": "2.2.0",
|
||||
"normalize.css": "7.0.0",
|
||||
"nprogress": "0.2.0",
|
||||
"path-to-regexp": "2.4.0",
|
||||
"vertx3-eventbus-client": "^3.9.4",
|
||||
"vue": "2.6.10",
|
||||
"vue-count-to": "^1.0.13",
|
||||
"vue-json-viewer": "^2.2.18",
|
||||
"vue-router": "3.0.6",
|
||||
"vuex": "3.1.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@vue/cli-plugin-babel": "4.4.4",
|
||||
"@vue/cli-plugin-eslint": "4.4.4",
|
||||
"@vue/cli-plugin-unit-jest": "4.4.4",
|
||||
"@vue/cli-service": "4.4.4",
|
||||
"@vue/test-utils": "1.0.0-beta.29",
|
||||
"autoprefixer": "9.5.1",
|
||||
"babel-eslint": "10.1.0",
|
||||
"babel-jest": "23.6.0",
|
||||
"babel-plugin-dynamic-import-node": "2.3.3",
|
||||
"chalk": "2.4.2",
|
||||
"connect": "3.6.6",
|
||||
"eslint": "6.7.2",
|
||||
"eslint-plugin-vue": "6.2.2",
|
||||
"html-webpack-plugin": "3.2.0",
|
||||
"mockjs": "1.0.1-beta3",
|
||||
"runjs": "4.3.2",
|
||||
"sass": "1.26.8",
|
||||
"sass-loader": "8.0.2",
|
||||
"script-ext-html-webpack-plugin": "2.1.3",
|
||||
"serve-static": "1.13.2",
|
||||
"vue-template-compiler": "2.6.10"
|
||||
},
|
||||
"browserslist": [
|
||||
"> 1%",
|
||||
"last 2 versions"
|
||||
],
|
||||
"engines": {
|
||||
"node": ">=8.9",
|
||||
"npm": ">= 3.0.0"
|
||||
},
|
||||
"license": ""
|
||||
}
|
||||
8
6_web_app/iocr/ocr_ui/postcss.config.js
Normal file
8
6_web_app/iocr/ocr_ui/postcss.config.js
Normal file
@ -0,0 +1,8 @@
|
||||
// https://github.com/michael-ciniawsky/postcss-load-config
|
||||
|
||||
module.exports = {
|
||||
'plugins': {
|
||||
// to edit target browsers: use "browserslist" field in package.json
|
||||
'autoprefixer': {}
|
||||
}
|
||||
}
|
||||
BIN
6_web_app/iocr/ocr_ui/public/favicon.ico
Normal file
BIN
6_web_app/iocr/ocr_ui/public/favicon.ico
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 17 KiB |
17
6_web_app/iocr/ocr_ui/public/index.html
Normal file
17
6_web_app/iocr/ocr_ui/public/index.html
Normal file
@ -0,0 +1,17 @@
|
||||
<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, user-scalable=no">
|
||||
<link rel="icon" href="<%= BASE_URL %>favicon.ico">
|
||||
<title><%= webpackConfig.name %></title>
|
||||
</head>
|
||||
<body>
|
||||
<noscript>
|
||||
<strong>We're sorry but <%= webpackConfig.name %> doesn't work properly without JavaScript enabled. Please enable it to continue.</strong>
|
||||
</noscript>
|
||||
<div id="app"></div>
|
||||
<!-- built files will be auto injected -->
|
||||
</body>
|
||||
</html>
|
||||
11
6_web_app/iocr/ocr_ui/src/App.vue
Normal file
11
6_web_app/iocr/ocr_ui/src/App.vue
Normal file
@ -0,0 +1,11 @@
|
||||
<template>
|
||||
<div id="app">
|
||||
<router-view />
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script>
|
||||
export default {
|
||||
name: 'App'
|
||||
}
|
||||
</script>
|
||||
24
6_web_app/iocr/ocr_ui/src/api/inference.js
Normal file
24
6_web_app/iocr/ocr_ui/src/api/inference.js
Normal file
@ -0,0 +1,24 @@
|
||||
import request from '@/utils/request'
|
||||
|
||||
export function generalInfoForImageUrl(data) {
|
||||
return request({
|
||||
url: '/inference/generalInfoForImageUrl',
|
||||
method: 'get',
|
||||
params: {
|
||||
url: data.url
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
export function mlsdForImageUrl(data) {
|
||||
return request({
|
||||
url: '/inference/mlsdForImageUrl',
|
||||
method: 'get',
|
||||
params: {
|
||||
url: data.url
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
export default { generalInfoForImageUrl, mlsdForImageUrl }
|
||||
|
||||
68
6_web_app/iocr/ocr_ui/src/api/template.js
Normal file
68
6_web_app/iocr/ocr_ui/src/api/template.js
Normal file
@ -0,0 +1,68 @@
|
||||
import request from '@/utils/request'
|
||||
|
||||
export function infoForImageUrl(uid, data) {
|
||||
return request({
|
||||
url: '/template/infoForImageUrl',
|
||||
method: 'get',
|
||||
params: {
|
||||
uid: uid,
|
||||
url: data.url
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
export function getTemplate(uid) {
|
||||
return request({
|
||||
url: '/template/getTemplate',
|
||||
method: 'get',
|
||||
params: {
|
||||
uid: uid
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
export function getTemplates() {
|
||||
return request({
|
||||
url: '/template/getTemplates',
|
||||
method: 'get'
|
||||
})
|
||||
}
|
||||
|
||||
export function updateTemplate(data) {
|
||||
return request({
|
||||
url: '/template/updateTemplate',
|
||||
method: 'post',
|
||||
data
|
||||
})
|
||||
}
|
||||
|
||||
export function getLabelData(data) {
|
||||
return request({
|
||||
url: '/template/getLabelData',
|
||||
method: 'post',
|
||||
data
|
||||
})
|
||||
}
|
||||
|
||||
export function addTemplate(name, imageFile) {
|
||||
return request({
|
||||
url: '/template/updateTemplate',
|
||||
method: 'post',
|
||||
params: {
|
||||
name: name,
|
||||
imageFile: imageFile
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
export function removeTemplate(uid) {
|
||||
return request({
|
||||
url: '/template/removeTemplate',
|
||||
method: 'post',
|
||||
params: {
|
||||
uid: uid
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
export default { getTemplate, getTemplates, updateTemplate, getLabelData, addTemplate, removeTemplate }
|
||||
55
6_web_app/iocr/ocr_ui/src/assets/styles/base.scss
Normal file
55
6_web_app/iocr/ocr_ui/src/assets/styles/base.scss
Normal file
@ -0,0 +1,55 @@
|
||||
// flex row
|
||||
@mixin flex-row {
|
||||
display: flex;
|
||||
flex-direction: row;
|
||||
}
|
||||
@mixin flex-row-between {
|
||||
@include flex-row();
|
||||
justify-content: space-between;
|
||||
}
|
||||
|
||||
@mixin flex-row-between-center {
|
||||
@include flex-row-between();
|
||||
align-items: center
|
||||
}
|
||||
|
||||
@mixin flex-row-center {
|
||||
@include flex-row();
|
||||
justify-content: center
|
||||
}
|
||||
|
||||
@mixin flex-row-all-center {
|
||||
@include flex-row-center;
|
||||
align-items: center
|
||||
|
||||
}
|
||||
|
||||
@mixin all-height($height) {
|
||||
height: $height;
|
||||
line-height: $height
|
||||
}
|
||||
|
||||
@mixin ellipsis($width) {
|
||||
width: $width;
|
||||
display: inline-block;
|
||||
overflow: hidden;
|
||||
white-space: nowrap;
|
||||
text-overflow: ellipsis
|
||||
}
|
||||
|
||||
// flex column
|
||||
@mixin flex-column {
|
||||
display: flex;
|
||||
flex-direction: column
|
||||
}
|
||||
|
||||
@mixin flex-column-center {
|
||||
@include flex-column();
|
||||
justify-content: center
|
||||
}
|
||||
|
||||
@mixin flex-column-all-center {
|
||||
@include flex-column-center;
|
||||
align-items: center
|
||||
}
|
||||
|
||||
99
6_web_app/iocr/ocr_ui/src/assets/styles/btn.scss
Normal file
99
6_web_app/iocr/ocr_ui/src/assets/styles/btn.scss
Normal file
@ -0,0 +1,99 @@
|
||||
@import 'variables';
|
||||
|
||||
@mixin colorBtn($color) {
|
||||
background: $color;
|
||||
|
||||
&:hover {
|
||||
color: $color;
|
||||
|
||||
&:before,
|
||||
&:after {
|
||||
background: $color;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.blue-btn {
|
||||
@include colorBtn($blue)
|
||||
}
|
||||
|
||||
.light-blue-btn {
|
||||
@include colorBtn($light-blue)
|
||||
}
|
||||
|
||||
.red-btn {
|
||||
@include colorBtn($red)
|
||||
}
|
||||
|
||||
.pink-btn {
|
||||
@include colorBtn($pink)
|
||||
}
|
||||
|
||||
.green-btn {
|
||||
@include colorBtn($green)
|
||||
}
|
||||
|
||||
.tiffany-btn {
|
||||
@include colorBtn($tiffany)
|
||||
}
|
||||
|
||||
.yellow-btn {
|
||||
@include colorBtn($yellow)
|
||||
}
|
||||
|
||||
.pan-btn {
|
||||
font-size: 14px;
|
||||
color: #fff;
|
||||
padding: 14px 36px;
|
||||
border-radius: 8px;
|
||||
border: none;
|
||||
outline: none;
|
||||
transition: 600ms ease all;
|
||||
position: relative;
|
||||
display: inline-block;
|
||||
|
||||
&:hover {
|
||||
background: #fff;
|
||||
|
||||
&:before,
|
||||
&:after {
|
||||
width: 100%;
|
||||
transition: 600ms ease all;
|
||||
}
|
||||
}
|
||||
|
||||
&:before,
|
||||
&:after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
top: 0;
|
||||
right: 0;
|
||||
height: 2px;
|
||||
width: 0;
|
||||
transition: 400ms ease all;
|
||||
}
|
||||
|
||||
&::after {
|
||||
right: inherit;
|
||||
top: inherit;
|
||||
left: 0;
|
||||
bottom: 0;
|
||||
}
|
||||
}
|
||||
|
||||
.custom-button {
|
||||
display: inline-block;
|
||||
line-height: 1;
|
||||
white-space: nowrap;
|
||||
cursor: pointer;
|
||||
background: #fff;
|
||||
color: #fff;
|
||||
-webkit-appearance: none;
|
||||
text-align: center;
|
||||
box-sizing: border-box;
|
||||
outline: 0;
|
||||
margin: 0;
|
||||
padding: 10px 15px;
|
||||
font-size: 14px;
|
||||
border-radius: 4px;
|
||||
}
|
||||
117
6_web_app/iocr/ocr_ui/src/assets/styles/eladmin.scss
Normal file
117
6_web_app/iocr/ocr_ui/src/assets/styles/eladmin.scss
Normal file
@ -0,0 +1,117 @@
|
||||
.head-container {
|
||||
padding-bottom: 10px;
|
||||
.filter-item {
|
||||
display: inline-block;
|
||||
vertical-align: middle;
|
||||
margin: 0 3px 10px 0;
|
||||
input {
|
||||
height: 30.5px;
|
||||
line-height: 30.5px;
|
||||
}
|
||||
}
|
||||
.el-form-item-label {
|
||||
margin: 0 3px 9px 0;
|
||||
display: inline-block;
|
||||
text-align: right;
|
||||
vertical-align: middle;
|
||||
font-size: 14px;
|
||||
color: #606266;
|
||||
line-height: 30.5px;
|
||||
padding: 0 7px 0 7px;
|
||||
}
|
||||
.el-button+.el-button {
|
||||
margin-left: 0 !important;
|
||||
}
|
||||
.el-select__caret.el-input__icon.el-icon-arrow-up{
|
||||
line-height: 30.5px;
|
||||
}
|
||||
.date-item {
|
||||
display: inline-block;
|
||||
vertical-align: middle;
|
||||
margin-bottom: 10px;
|
||||
height: 30.5px !important;
|
||||
width: 230px !important;
|
||||
}
|
||||
}
|
||||
.el-avatar {
|
||||
display: inline-block;
|
||||
text-align: center;
|
||||
background: #ccc;
|
||||
color: #fff;
|
||||
white-space: nowrap;
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
vertical-align: middle;
|
||||
width: 32px;
|
||||
height: 32px;
|
||||
line-height: 32px;
|
||||
border-radius: 16px;
|
||||
}
|
||||
|
||||
.logo-con{
|
||||
height: 60px;
|
||||
padding: 13px 0 0;
|
||||
img{
|
||||
height: 32px;
|
||||
width: 135px;
|
||||
display: block;
|
||||
//margin: 0 auto;
|
||||
}
|
||||
}
|
||||
|
||||
#el-login-footer {
|
||||
height: 40px;
|
||||
line-height: 40px;
|
||||
position: fixed;
|
||||
bottom: 0;
|
||||
width: 100%;
|
||||
text-align: center;
|
||||
color: #fff;
|
||||
font-family: Arial, serif;
|
||||
font-size: 12px;
|
||||
letter-spacing: 1px;
|
||||
}
|
||||
|
||||
#el-main-footer {
|
||||
background: none repeat scroll 0 0 white;
|
||||
border-top: 1px solid #e7eaec;
|
||||
overflow: hidden;
|
||||
padding: 10px 6px 0 6px;
|
||||
height: 33px;
|
||||
font-size: 0.7rem !important;
|
||||
color: #7a8b9a;
|
||||
letter-spacing: 0.8px;
|
||||
font-family: Arial, sans-serif !important;
|
||||
position: fixed;
|
||||
bottom: 0;
|
||||
z-index: 99;
|
||||
width: 100%;
|
||||
}
|
||||
.eladmin-upload {
|
||||
border: 1px dashed #c0ccda;
|
||||
border-radius: 5px;
|
||||
height: 45px;
|
||||
line-height: 45px;
|
||||
width: 368px;
|
||||
}
|
||||
.my-blockquote{
|
||||
margin: 0 0 10px;
|
||||
padding: 15px;
|
||||
line-height: 22px;
|
||||
border-left: 5px solid #00437B;
|
||||
border-radius: 0 2px 2px 0;
|
||||
background-color: #f2f2f2;
|
||||
}
|
||||
.my-code{
|
||||
position: relative;
|
||||
padding: 15px;
|
||||
line-height: 20px;
|
||||
border-left: 5px solid #ddd;
|
||||
color: #333;
|
||||
font-family: Courier New, serif;
|
||||
font-size: 12px
|
||||
}
|
||||
|
||||
.el-tabs{
|
||||
margin-bottom: 25px;
|
||||
}
|
||||
79
6_web_app/iocr/ocr_ui/src/assets/styles/element-ui.scss
Normal file
79
6_web_app/iocr/ocr_ui/src/assets/styles/element-ui.scss
Normal file
@ -0,0 +1,79 @@
|
||||
// cover some element-ui styles
|
||||
|
||||
.el-breadcrumb__inner,
|
||||
.el-breadcrumb__inner a {
|
||||
font-weight: 400 !important;
|
||||
}
|
||||
|
||||
.el-upload {
|
||||
input[type="file"] {
|
||||
display: none !important;
|
||||
}
|
||||
}
|
||||
|
||||
.el-upload__input {
|
||||
display: none;
|
||||
}
|
||||
|
||||
.cell {
|
||||
.el-tag {
|
||||
margin-right: 0;
|
||||
}
|
||||
}
|
||||
|
||||
.small-padding {
|
||||
.cell {
|
||||
padding-left: 5px;
|
||||
padding-right: 5px;
|
||||
}
|
||||
}
|
||||
|
||||
.fixed-width {
|
||||
.el-button--mini {
|
||||
padding: 7px 10px;
|
||||
width: 60px;
|
||||
}
|
||||
}
|
||||
|
||||
.status-col {
|
||||
.cell {
|
||||
padding: 0 10px;
|
||||
text-align: center;
|
||||
|
||||
.el-tag {
|
||||
margin-right: 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// to fixed https://github.com/ElemeFE/element/issues/2461
|
||||
.el-dialog {
|
||||
transform: none;
|
||||
left: 0;
|
||||
position: relative;
|
||||
margin: 0 auto;
|
||||
}
|
||||
|
||||
// refine element ui upload
|
||||
.upload-container {
|
||||
.el-upload {
|
||||
width: 100%;
|
||||
|
||||
.el-upload-dragger {
|
||||
width: 100%;
|
||||
height: 200px;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// dropdown
|
||||
.el-dropdown-menu {
|
||||
a {
|
||||
display: block
|
||||
}
|
||||
}
|
||||
|
||||
// fix date-picker ui bug in filter-item
|
||||
.el-range-editor.el-input__inner {
|
||||
display: inline-flex !important;
|
||||
}
|
||||
@ -0,0 +1,31 @@
|
||||
/**
|
||||
* I think element-ui's default theme color is too light for long-term use.
|
||||
* So I modified the default color and you can modify it to your liking.
|
||||
**/
|
||||
|
||||
/* theme color */
|
||||
$--color-primary: #1890ff;
|
||||
$--color-success: #13ce66;
|
||||
$--color-warning: #FFBA00;
|
||||
$--color-danger: #ff4949;
|
||||
// $--color-info: #1E1E1E;
|
||||
|
||||
$--button-font-weight: 400;
|
||||
|
||||
// $--color-text-regular: #1f2d3d;
|
||||
|
||||
$--border-color-light: #dfe4ed;
|
||||
$--border-color-lighter: #e6ebf5;
|
||||
|
||||
$--table-border:1px solid#dfe6ec;
|
||||
|
||||
/* icon font path, required */
|
||||
$--font-path: '~element-ui/lib/theme-chalk/fonts';
|
||||
|
||||
@import "../../../node_modules/element-ui/packages/theme-chalk/src/index";
|
||||
|
||||
// the :export directive is the magic sauce for webpack
|
||||
// https://www.bluematador.com/blog/how-to-share-variables-between-js-and-sass
|
||||
:export {
|
||||
theme: $--color-primary;
|
||||
}
|
||||
182
6_web_app/iocr/ocr_ui/src/assets/styles/index.scss
Normal file
182
6_web_app/iocr/ocr_ui/src/assets/styles/index.scss
Normal file
@ -0,0 +1,182 @@
|
||||
@import 'variables';
|
||||
@import 'mixin';
|
||||
@import 'transition';
|
||||
@import 'element-ui';
|
||||
@import 'sidebar';
|
||||
@import 'btn';
|
||||
@import 'eladmin';
|
||||
|
||||
body {
|
||||
height: 100%;
|
||||
-moz-osx-font-smoothing: grayscale;
|
||||
-webkit-font-smoothing: antialiased;
|
||||
text-rendering: optimizeLegibility;
|
||||
font-family: Helvetica Neue, Helvetica, PingFang SC, Hiragino Sans GB, Microsoft YaHei, Arial, sans-serif;
|
||||
}
|
||||
|
||||
label {
|
||||
font-weight: 700;
|
||||
}
|
||||
|
||||
html {
|
||||
height: 100%;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
#app {
|
||||
height: 100%;
|
||||
}
|
||||
|
||||
*,
|
||||
*:before,
|
||||
*:after {
|
||||
box-sizing: inherit;
|
||||
}
|
||||
|
||||
.no-padding {
|
||||
padding: 0 !important;
|
||||
}
|
||||
|
||||
.padding-content {
|
||||
padding: 4px 0;
|
||||
}
|
||||
|
||||
a:focus,
|
||||
a:active {
|
||||
outline: none;
|
||||
}
|
||||
|
||||
a,
|
||||
a:focus,
|
||||
a:hover {
|
||||
cursor: pointer;
|
||||
color: inherit;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
div:focus {
|
||||
outline: none;
|
||||
}
|
||||
|
||||
.fr {
|
||||
float: right;
|
||||
}
|
||||
|
||||
.fl {
|
||||
float: left;
|
||||
}
|
||||
|
||||
.pr-5 {
|
||||
padding-right: 5px;
|
||||
}
|
||||
|
||||
.pl-5 {
|
||||
padding-left: 5px;
|
||||
}
|
||||
|
||||
.block {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.pointer {
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.inlineBlock {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.clearfix {
|
||||
&:after {
|
||||
visibility: hidden;
|
||||
display: block;
|
||||
font-size: 0;
|
||||
content: " ";
|
||||
clear: both;
|
||||
height: 0;
|
||||
}
|
||||
}
|
||||
|
||||
aside {
|
||||
background: #eef1f6;
|
||||
padding: 8px 24px;
|
||||
margin-bottom: 20px;
|
||||
border-radius: 2px;
|
||||
display: block;
|
||||
line-height: 32px;
|
||||
font-size: 16px;
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Fira Sans", "Droid Sans", "Helvetica Neue", sans-serif;
|
||||
color: #2c3e50;
|
||||
-webkit-font-smoothing: antialiased;
|
||||
-moz-osx-font-smoothing: grayscale;
|
||||
|
||||
a {
|
||||
color: #337ab7;
|
||||
cursor: pointer;
|
||||
|
||||
&:hover {
|
||||
color: rgb(32, 160, 255);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//main-container全局样式
|
||||
.app-container {
|
||||
padding: 20px 20px 45px 20px;
|
||||
}
|
||||
|
||||
.components-container {
|
||||
margin: 30px 50px;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.pagination-container {
|
||||
margin-top: 30px;
|
||||
}
|
||||
|
||||
.text-center {
|
||||
text-align: center
|
||||
}
|
||||
|
||||
.sub-navbar {
|
||||
height: 50px;
|
||||
line-height: 50px;
|
||||
position: relative;
|
||||
width: 100%;
|
||||
text-align: right;
|
||||
padding-right: 20px;
|
||||
transition: 600ms ease position;
|
||||
background: linear-gradient(90deg, rgba(32, 182, 249, 1) 0%, rgba(32, 182, 249, 1) 0%, rgba(33, 120, 241, 1) 100%, rgba(33, 120, 241, 1) 100%);
|
||||
|
||||
.subtitle {
|
||||
font-size: 20px;
|
||||
color: #fff;
|
||||
}
|
||||
|
||||
&.draft {
|
||||
background: #d0d0d0;
|
||||
}
|
||||
|
||||
&.deleted {
|
||||
background: #d0d0d0;
|
||||
}
|
||||
}
|
||||
|
||||
.link-type,
|
||||
.link-type:focus {
|
||||
color: #337ab7;
|
||||
cursor: pointer;
|
||||
|
||||
&:hover {
|
||||
color: rgb(32, 160, 255);
|
||||
}
|
||||
}
|
||||
|
||||
//refine vue-multiselect plugin
|
||||
.multiselect {
|
||||
line-height: 16px;
|
||||
}
|
||||
|
||||
.multiselect--active {
|
||||
z-index: 1000 !important;
|
||||
}
|
||||
66
6_web_app/iocr/ocr_ui/src/assets/styles/mixin.scss
Normal file
66
6_web_app/iocr/ocr_ui/src/assets/styles/mixin.scss
Normal file
@ -0,0 +1,66 @@
|
||||
@mixin clearfix {
|
||||
&:after {
|
||||
content: "";
|
||||
display: table;
|
||||
clear: both;
|
||||
}
|
||||
}
|
||||
|
||||
@mixin scrollBar {
|
||||
&::-webkit-scrollbar-track-piece {
|
||||
background: #d3dce6;
|
||||
}
|
||||
|
||||
&::-webkit-scrollbar {
|
||||
width: 6px;
|
||||
}
|
||||
|
||||
&::-webkit-scrollbar-thumb {
|
||||
background: #99a9bf;
|
||||
border-radius: 20px;
|
||||
}
|
||||
}
|
||||
|
||||
@mixin relative {
|
||||
position: relative;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
}
|
||||
|
||||
@mixin pct($pct) {
|
||||
width: #{$pct};
|
||||
position: relative;
|
||||
margin: 0 auto;
|
||||
}
|
||||
|
||||
@mixin triangle($width, $height, $color, $direction) {
|
||||
$width: $width/2;
|
||||
$color-border-style: $height solid $color;
|
||||
$transparent-border-style: $width solid transparent;
|
||||
height: 0;
|
||||
width: 0;
|
||||
|
||||
@if $direction==up {
|
||||
border-bottom: $color-border-style;
|
||||
border-left: $transparent-border-style;
|
||||
border-right: $transparent-border-style;
|
||||
}
|
||||
|
||||
@else if $direction==right {
|
||||
border-left: $color-border-style;
|
||||
border-top: $transparent-border-style;
|
||||
border-bottom: $transparent-border-style;
|
||||
}
|
||||
|
||||
@else if $direction==down {
|
||||
border-top: $color-border-style;
|
||||
border-left: $transparent-border-style;
|
||||
border-right: $transparent-border-style;
|
||||
}
|
||||
|
||||
@else if $direction==left {
|
||||
border-right: $color-border-style;
|
||||
border-top: $transparent-border-style;
|
||||
border-bottom: $transparent-border-style;
|
||||
}
|
||||
}
|
||||
209
6_web_app/iocr/ocr_ui/src/assets/styles/sidebar.scss
Normal file
209
6_web_app/iocr/ocr_ui/src/assets/styles/sidebar.scss
Normal file
@ -0,0 +1,209 @@
|
||||
#app {
|
||||
|
||||
.main-container {
|
||||
min-height: 100%;
|
||||
transition: margin-left .28s;
|
||||
margin-left: $sideBarWidth;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.sidebar-container {
|
||||
transition: width 0.28s;
|
||||
width: $sideBarWidth !important;
|
||||
background-color: $menuBg;
|
||||
height: 100%;
|
||||
position: fixed;
|
||||
font-size: 0;
|
||||
top: 0;
|
||||
bottom: 0;
|
||||
left: 0;
|
||||
z-index: 1001;
|
||||
overflow: hidden;
|
||||
|
||||
// reset element-ui css
|
||||
.horizontal-collapse-transition {
|
||||
transition: 0s width ease-in-out, 0s padding-left ease-in-out, 0s padding-right ease-in-out;
|
||||
}
|
||||
|
||||
.scrollbar-wrapper {
|
||||
overflow-x: hidden !important;
|
||||
}
|
||||
|
||||
.el-scrollbar__bar.is-vertical {
|
||||
right: 0;
|
||||
}
|
||||
|
||||
.el-scrollbar {
|
||||
height: 100%;
|
||||
}
|
||||
|
||||
&.has-logo {
|
||||
.el-scrollbar {
|
||||
height: calc(100% - 50px);
|
||||
}
|
||||
}
|
||||
|
||||
.is-horizontal {
|
||||
display: none;
|
||||
}
|
||||
|
||||
a {
|
||||
display: inline-block;
|
||||
width: 100%;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.svg-icon {
|
||||
margin-right: 16px;
|
||||
}
|
||||
|
||||
.el-menu {
|
||||
border: none;
|
||||
height: 100%;
|
||||
width: 100% !important;
|
||||
}
|
||||
|
||||
// menu hover
|
||||
.submenu-title-noDropdown,
|
||||
.el-submenu__title {
|
||||
&:hover {
|
||||
background-color: $menuHover !important;
|
||||
}
|
||||
}
|
||||
|
||||
.is-active>.el-submenu__title {
|
||||
color: $subMenuActiveText !important;
|
||||
}
|
||||
|
||||
& .nest-menu .el-submenu>.el-submenu__title,
|
||||
& .el-submenu .el-menu-item {
|
||||
min-width: $sideBarWidth !important;
|
||||
background-color: $subMenuBg !important;
|
||||
|
||||
&:hover {
|
||||
background-color: $subMenuHover !important;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.hideSidebar {
|
||||
.sidebar-container {
|
||||
width: 54px !important;
|
||||
}
|
||||
|
||||
.main-container {
|
||||
margin-left: 54px;
|
||||
}
|
||||
|
||||
.submenu-title-noDropdown {
|
||||
padding: 0 !important;
|
||||
position: relative;
|
||||
|
||||
.el-tooltip {
|
||||
padding: 0 !important;
|
||||
|
||||
.svg-icon {
|
||||
margin-left: 20px;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.el-submenu {
|
||||
overflow: hidden;
|
||||
|
||||
&>.el-submenu__title {
|
||||
padding: 0 !important;
|
||||
|
||||
.svg-icon {
|
||||
margin-left: 20px;
|
||||
}
|
||||
|
||||
.el-submenu__icon-arrow {
|
||||
display: none;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.el-menu--collapse {
|
||||
.el-submenu {
|
||||
&>.el-submenu__title {
|
||||
&>span {
|
||||
height: 0;
|
||||
width: 0;
|
||||
overflow: hidden;
|
||||
visibility: hidden;
|
||||
display: inline-block;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.el-menu--collapse .el-menu .el-submenu {
|
||||
min-width: $sideBarWidth !important;
|
||||
}
|
||||
|
||||
// mobile responsive
|
||||
.mobile {
|
||||
.main-container {
|
||||
margin-left: 0;
|
||||
}
|
||||
|
||||
.sidebar-container {
|
||||
transition: transform .28s;
|
||||
width: $sideBarWidth !important;
|
||||
}
|
||||
|
||||
&.hideSidebar {
|
||||
.sidebar-container {
|
||||
pointer-events: none;
|
||||
transition-duration: 0.3s;
|
||||
transform: translate3d(-$sideBarWidth, 0, 0);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.withoutAnimation {
|
||||
|
||||
.main-container,
|
||||
.sidebar-container {
|
||||
transition: none;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// when menu collapsed
|
||||
.el-menu--vertical {
|
||||
&>.el-menu {
|
||||
.svg-icon {
|
||||
margin-right: 16px;
|
||||
}
|
||||
}
|
||||
|
||||
.nest-menu .el-submenu>.el-submenu__title,
|
||||
.el-menu-item {
|
||||
&:hover {
|
||||
// you can use $subMenuHover
|
||||
background-color: $menuHover !important;
|
||||
}
|
||||
}
|
||||
|
||||
// the scroll bar appears when the subMenu is too long
|
||||
>.el-menu--popup {
|
||||
max-height: 100vh;
|
||||
overflow-y: auto;
|
||||
|
||||
&::-webkit-scrollbar-track-piece {
|
||||
background: #d3dce6;
|
||||
}
|
||||
|
||||
&::-webkit-scrollbar {
|
||||
width: 6px;
|
||||
}
|
||||
|
||||
&::-webkit-scrollbar-thumb {
|
||||
background: #99a9bf;
|
||||
border-radius: 20px;
|
||||
}
|
||||
}
|
||||
}
|
||||
48
6_web_app/iocr/ocr_ui/src/assets/styles/transition.scss
Normal file
48
6_web_app/iocr/ocr_ui/src/assets/styles/transition.scss
Normal file
@ -0,0 +1,48 @@
|
||||
// global transition css
|
||||
|
||||
/* fade */
|
||||
.fade-enter-active,
|
||||
.fade-leave-active {
|
||||
transition: opacity 0.28s;
|
||||
}
|
||||
|
||||
.fade-enter,
|
||||
.fade-leave-active {
|
||||
opacity: 0;
|
||||
}
|
||||
|
||||
/* fade-transform */
|
||||
.fade-transform-leave-active,
|
||||
.fade-transform-enter-active {
|
||||
transition: all .5s;
|
||||
}
|
||||
|
||||
.fade-transform-enter {
|
||||
opacity: 0;
|
||||
transform: translateX(-30px);
|
||||
}
|
||||
|
||||
.fade-transform-leave-to {
|
||||
opacity: 0;
|
||||
transform: translateX(30px);
|
||||
}
|
||||
|
||||
/* breadcrumb transition */
|
||||
.breadcrumb-enter-active,
|
||||
.breadcrumb-leave-active {
|
||||
transition: all .5s;
|
||||
}
|
||||
|
||||
.breadcrumb-enter,
|
||||
.breadcrumb-leave-active {
|
||||
opacity: 0;
|
||||
transform: translateX(20px);
|
||||
}
|
||||
|
||||
.breadcrumb-move {
|
||||
transition: all .5s;
|
||||
}
|
||||
|
||||
.breadcrumb-leave-active {
|
||||
position: absolute;
|
||||
}
|
||||
35
6_web_app/iocr/ocr_ui/src/assets/styles/variables.scss
Normal file
35
6_web_app/iocr/ocr_ui/src/assets/styles/variables.scss
Normal file
@ -0,0 +1,35 @@
|
||||
// base color
|
||||
$blue:#324157;
|
||||
$light-blue:#3A71A8;
|
||||
$red:#C03639;
|
||||
$pink: #E65D6E;
|
||||
$green: #30B08F;
|
||||
$tiffany: #4AB7BD;
|
||||
$yellow:#FEC171;
|
||||
$panGreen: #30B08F;
|
||||
|
||||
// sidebar
|
||||
$menuText:#bfcbd9;
|
||||
$menuActiveText:#409EFF;
|
||||
$subMenuActiveText:#f4f4f5; // https://github.com/ElemeFE/element/issues/12951
|
||||
|
||||
$menuBg:#304156;
|
||||
$menuHover:#263445;
|
||||
|
||||
$subMenuBg:#1f2d3d;
|
||||
$subMenuHover:#001528;
|
||||
|
||||
$sideBarWidth: 205px;
|
||||
|
||||
// the :export directive is the magic sauce for webpack
|
||||
// https://www.bluematador.com/blog/how-to-share-variables-between-js-and-sass
|
||||
:export {
|
||||
menuText: $menuText;
|
||||
menuActiveText: $menuActiveText;
|
||||
subMenuActiveText: $subMenuActiveText;
|
||||
menuBg: $menuBg;
|
||||
menuHover: $menuHover;
|
||||
subMenuBg: $subMenuBg;
|
||||
subMenuHover: $subMenuHover;
|
||||
sideBarWidth: $sideBarWidth;
|
||||
}
|
||||
40
6_web_app/iocr/ocr_ui/src/common/mixin/table-mixin.js
Normal file
40
6_web_app/iocr/ocr_ui/src/common/mixin/table-mixin.js
Normal file
@ -0,0 +1,40 @@
|
||||
export default {
|
||||
data () {
|
||||
return {
|
||||
tableInit: false,
|
||||
emptyTable: false,
|
||||
page: {
|
||||
pageNum: 1,
|
||||
pageSize: 8,
|
||||
total: 0,
|
||||
},
|
||||
}
|
||||
},
|
||||
mounted () {
|
||||
},
|
||||
computed: {
|
||||
// emptyTable () {
|
||||
// return this.page.total === 0 && this.page.pageNum === 1 && this.emptyParam
|
||||
// },
|
||||
},
|
||||
watch: {
|
||||
'page.total' () {
|
||||
if (this.page.total > 0) {
|
||||
this.emptyTable = false
|
||||
}
|
||||
},
|
||||
},
|
||||
methods: {
|
||||
isObjectEmpty (data = {}) {
|
||||
return Object.values(data).filter(a => !!a).length === 0
|
||||
},
|
||||
setEmptyTable () {
|
||||
this.tableInit = true
|
||||
console.log(this.page.total, this.page.total == 0)
|
||||
this.emptyTable = this.page.total == 0
|
||||
},
|
||||
clearPage () {
|
||||
this.page.pageNum = 1
|
||||
},
|
||||
},
|
||||
}
|
||||
78
6_web_app/iocr/ocr_ui/src/components/Breadcrumb/index.vue
Normal file
78
6_web_app/iocr/ocr_ui/src/components/Breadcrumb/index.vue
Normal file
@ -0,0 +1,78 @@
|
||||
<template>
|
||||
<el-breadcrumb class="app-breadcrumb" separator="/">
|
||||
<transition-group name="breadcrumb">
|
||||
<el-breadcrumb-item v-for="(item,index) in levelList" :key="item.path">
|
||||
<span v-if="item.redirect==='noRedirect'||index==levelList.length-1" class="no-redirect">{{ item.meta.title }}</span>
|
||||
<a v-else @click.prevent="handleLink(item)">{{ item.meta.title }}</a>
|
||||
</el-breadcrumb-item>
|
||||
</transition-group>
|
||||
</el-breadcrumb>
|
||||
</template>
|
||||
|
||||
<script>
|
||||
import pathToRegexp from 'path-to-regexp'
|
||||
|
||||
export default {
|
||||
data() {
|
||||
return {
|
||||
levelList: null
|
||||
}
|
||||
},
|
||||
watch: {
|
||||
$route() {
|
||||
this.getBreadcrumb()
|
||||
}
|
||||
},
|
||||
created() {
|
||||
this.getBreadcrumb()
|
||||
},
|
||||
methods: {
|
||||
getBreadcrumb() {
|
||||
// only show routes with meta.title
|
||||
let matched = this.$route.matched.filter(item => item.meta && item.meta.title)
|
||||
const first = matched[0]
|
||||
|
||||
if (!this.isDashboard(first)) {
|
||||
matched = [{ path: '/dashboard', meta: { title: 'Dashboard' }}].concat(matched)
|
||||
}
|
||||
|
||||
this.levelList = matched.filter(item => item.meta && item.meta.title && item.meta.breadcrumb !== false)
|
||||
},
|
||||
isDashboard(route) {
|
||||
const name = route && route.name
|
||||
if (!name) {
|
||||
return false
|
||||
}
|
||||
return name.trim().toLocaleLowerCase() === 'Dashboard'.toLocaleLowerCase()
|
||||
},
|
||||
pathCompile(path) {
|
||||
// To solve this problem https://github.com/PanJiaChen/vue-element-admin/issues/561
|
||||
const { params } = this.$route
|
||||
var toPath = pathToRegexp.compile(path)
|
||||
return toPath(params)
|
||||
},
|
||||
handleLink(item) {
|
||||
const { redirect, path } = item
|
||||
if (redirect) {
|
||||
this.$router.push(redirect)
|
||||
return
|
||||
}
|
||||
this.$router.push(this.pathCompile(path))
|
||||
}
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.app-breadcrumb.el-breadcrumb {
|
||||
display: inline-block;
|
||||
font-size: 14px;
|
||||
line-height: 50px;
|
||||
margin-left: 8px;
|
||||
|
||||
.no-redirect {
|
||||
color: #97a8be;
|
||||
cursor: text;
|
||||
}
|
||||
}
|
||||
</style>
|
||||
44
6_web_app/iocr/ocr_ui/src/components/Hamburger/index.vue
Normal file
44
6_web_app/iocr/ocr_ui/src/components/Hamburger/index.vue
Normal file
@ -0,0 +1,44 @@
|
||||
<template>
|
||||
<div style="padding: 0 15px;" @click="toggleClick">
|
||||
<svg
|
||||
:class="{'is-active':isActive}"
|
||||
class="hamburger"
|
||||
viewBox="0 0 1024 1024"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
width="64"
|
||||
height="64"
|
||||
>
|
||||
<path d="M408 442h480c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8H408c-4.4 0-8 3.6-8 8v56c0 4.4 3.6 8 8 8zm-8 204c0 4.4 3.6 8 8 8h480c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8H408c-4.4 0-8 3.6-8 8v56zm504-486H120c-4.4 0-8 3.6-8 8v56c0 4.4 3.6 8 8 8h784c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8zm0 632H120c-4.4 0-8 3.6-8 8v56c0 4.4 3.6 8 8 8h784c4.4 0 8-3.6 8-8v-56c0-4.4-3.6-8-8-8zM142.4 642.1L298.7 519a8.84 8.84 0 0 0 0-13.9L142.4 381.9c-5.8-4.6-14.4-.5-14.4 6.9v246.3a8.9 8.9 0 0 0 14.4 7z" />
|
||||
</svg>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script>
|
||||
export default {
|
||||
name: 'Hamburger',
|
||||
props: {
|
||||
isActive: {
|
||||
type: Boolean,
|
||||
default: false
|
||||
}
|
||||
},
|
||||
methods: {
|
||||
toggleClick() {
|
||||
this.$emit('toggleClick')
|
||||
}
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.hamburger {
|
||||
display: inline-block;
|
||||
vertical-align: middle;
|
||||
width: 20px;
|
||||
height: 20px;
|
||||
}
|
||||
|
||||
.hamburger.is-active {
|
||||
transform: rotate(180deg);
|
||||
}
|
||||
</style>
|
||||
62
6_web_app/iocr/ocr_ui/src/components/SvgIcon/index.vue
Normal file
62
6_web_app/iocr/ocr_ui/src/components/SvgIcon/index.vue
Normal file
@ -0,0 +1,62 @@
|
||||
<template>
|
||||
<div v-if="isExternal" :style="styleExternalIcon" class="svg-external-icon svg-icon" v-on="$listeners" />
|
||||
<svg v-else :class="svgClass" aria-hidden="true" v-on="$listeners">
|
||||
<use :xlink:href="iconName" />
|
||||
</svg>
|
||||
</template>
|
||||
|
||||
<script>
|
||||
// doc: https://panjiachen.github.io/vue-element-admin-site/feature/component/svg-icon.html#usage
|
||||
import { isExternal } from '@/utils/validate'
|
||||
|
||||
export default {
|
||||
name: 'SvgIcon',
|
||||
props: {
|
||||
iconClass: {
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
className: {
|
||||
type: String,
|
||||
default: ''
|
||||
}
|
||||
},
|
||||
computed: {
|
||||
isExternal() {
|
||||
return isExternal(this.iconClass)
|
||||
},
|
||||
iconName() {
|
||||
return `#icon-${this.iconClass}`
|
||||
},
|
||||
svgClass() {
|
||||
if (this.className) {
|
||||
return 'svg-icon ' + this.className
|
||||
} else {
|
||||
return 'svg-icon'
|
||||
}
|
||||
},
|
||||
styleExternalIcon() {
|
||||
return {
|
||||
mask: `url(${this.iconClass}) no-repeat 50% 50%`,
|
||||
'-webkit-mask': `url(${this.iconClass}) no-repeat 50% 50%`
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.svg-icon {
|
||||
width: 1em;
|
||||
height: 1em;
|
||||
vertical-align: -0.15em;
|
||||
fill: currentColor;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.svg-external-icon {
|
||||
background-color: currentColor;
|
||||
mask-size: cover!important;
|
||||
display: inline-block;
|
||||
}
|
||||
</style>
|
||||
40
6_web_app/iocr/ocr_ui/src/layout/components/AppMain.vue
Normal file
40
6_web_app/iocr/ocr_ui/src/layout/components/AppMain.vue
Normal file
@ -0,0 +1,40 @@
|
||||
<template>
|
||||
<section class="app-main">
|
||||
<transition name="fade-transform" mode="out-in">
|
||||
<router-view :key="key" />
|
||||
</transition>
|
||||
</section>
|
||||
</template>
|
||||
|
||||
<script>
|
||||
export default {
|
||||
name: 'AppMain',
|
||||
computed: {
|
||||
key() {
|
||||
return this.$route.path
|
||||
}
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.app-main {
|
||||
/*50 = navbar */
|
||||
min-height: calc(100vh - 50px);
|
||||
width: 100%;
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
}
|
||||
.fixed-header+.app-main {
|
||||
padding-top: 50px;
|
||||
}
|
||||
</style>
|
||||
|
||||
<style lang="scss">
|
||||
// fix css style bug in open el-dialog
|
||||
.el-popup-parent--hidden {
|
||||
.fixed-header {
|
||||
padding-right: 15px;
|
||||
}
|
||||
}
|
||||
</style>
|
||||
111
6_web_app/iocr/ocr_ui/src/layout/components/Navbar.vue
Normal file
111
6_web_app/iocr/ocr_ui/src/layout/components/Navbar.vue
Normal file
@ -0,0 +1,111 @@
|
||||
<template>
|
||||
<div class="navbar">
|
||||
<hamburger :is-active="sidebar.opened" class="hamburger-container" @toggleClick="toggleSideBar" />
|
||||
|
||||
<breadcrumb class="breadcrumb-container" />
|
||||
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script>
|
||||
import { mapGetters } from 'vuex'
|
||||
import Breadcrumb from '@/components/Breadcrumb'
|
||||
import Hamburger from '@/components/Hamburger'
|
||||
|
||||
export default {
|
||||
components: {
|
||||
Breadcrumb,
|
||||
Hamburger
|
||||
},
|
||||
computed: {
|
||||
...mapGetters([
|
||||
'sidebar',
|
||||
'avatar'
|
||||
])
|
||||
},
|
||||
methods: {
|
||||
toggleSideBar() {
|
||||
this.$store.dispatch('app/toggleSideBar')
|
||||
}
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.navbar {
|
||||
height: 50px;
|
||||
overflow: hidden;
|
||||
position: relative;
|
||||
background: #fff;
|
||||
box-shadow: 0 1px 4px rgba(0,21,41,.08);
|
||||
|
||||
.hamburger-container {
|
||||
line-height: 46px;
|
||||
height: 100%;
|
||||
float: left;
|
||||
cursor: pointer;
|
||||
transition: background .3s;
|
||||
-webkit-tap-highlight-color:transparent;
|
||||
|
||||
&:hover {
|
||||
background: rgba(0, 0, 0, .025)
|
||||
}
|
||||
}
|
||||
|
||||
.breadcrumb-container {
|
||||
float: left;
|
||||
}
|
||||
|
||||
.right-menu {
|
||||
float: right;
|
||||
height: 100%;
|
||||
line-height: 50px;
|
||||
|
||||
&:focus {
|
||||
outline: none;
|
||||
}
|
||||
|
||||
.right-menu-item {
|
||||
display: inline-block;
|
||||
padding: 0 8px;
|
||||
height: 100%;
|
||||
font-size: 18px;
|
||||
color: #5a5e66;
|
||||
vertical-align: text-bottom;
|
||||
|
||||
&.hover-effect {
|
||||
cursor: pointer;
|
||||
transition: background .3s;
|
||||
|
||||
&:hover {
|
||||
background: rgba(0, 0, 0, .025)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.avatar-container {
|
||||
margin-right: 30px;
|
||||
|
||||
.avatar-wrapper {
|
||||
margin-top: 5px;
|
||||
position: relative;
|
||||
|
||||
.user-avatar {
|
||||
cursor: pointer;
|
||||
width: 40px;
|
||||
height: 40px;
|
||||
border-radius: 10px;
|
||||
}
|
||||
|
||||
.el-icon-caret-bottom {
|
||||
cursor: pointer;
|
||||
position: absolute;
|
||||
right: -20px;
|
||||
top: 25px;
|
||||
font-size: 12px;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
</style>
|
||||
@ -0,0 +1,26 @@
|
||||
export default {
|
||||
computed: {
|
||||
device() {
|
||||
return this.$store.state.app.device
|
||||
}
|
||||
},
|
||||
mounted() {
|
||||
// In order to fix the click on menu on the ios device will trigger the mouseleave bug
|
||||
// https://github.com/PanJiaChen/vue-element-admin/issues/1135
|
||||
this.fixBugIniOS()
|
||||
},
|
||||
methods: {
|
||||
fixBugIniOS() {
|
||||
const $subMenu = this.$refs.subMenu
|
||||
if ($subMenu) {
|
||||
const handleMouseleave = $subMenu.handleMouseleave
|
||||
$subMenu.handleMouseleave = (e) => {
|
||||
if (this.device === 'mobile') {
|
||||
return
|
||||
}
|
||||
handleMouseleave(e)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
41
6_web_app/iocr/ocr_ui/src/layout/components/Sidebar/Item.vue
Normal file
41
6_web_app/iocr/ocr_ui/src/layout/components/Sidebar/Item.vue
Normal file
@ -0,0 +1,41 @@
|
||||
<script>
|
||||
export default {
|
||||
name: 'MenuItem',
|
||||
functional: true,
|
||||
props: {
|
||||
icon: {
|
||||
type: String,
|
||||
default: ''
|
||||
},
|
||||
title: {
|
||||
type: String,
|
||||
default: ''
|
||||
}
|
||||
},
|
||||
render(h, context) {
|
||||
const { icon, title } = context.props
|
||||
const vnodes = []
|
||||
|
||||
if (icon) {
|
||||
if (icon.includes('el-icon')) {
|
||||
vnodes.push(<i class={[icon, 'sub-el-icon']} />)
|
||||
} else {
|
||||
vnodes.push(<svg-icon icon-class={icon}/>)
|
||||
}
|
||||
}
|
||||
|
||||
if (title) {
|
||||
vnodes.push(<span slot='title'>{(title)}</span>)
|
||||
}
|
||||
return vnodes
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.sub-el-icon {
|
||||
color: currentColor;
|
||||
width: 1em;
|
||||
height: 1em;
|
||||
}
|
||||
</style>
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user