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33 lines
1.9 KiB
Markdown
33 lines
1.9 KiB
Markdown
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### Download the model and place it in the /models directory
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- Link: https://github.com/mymagicpower/AIAS/releases/download/apps/pedestrian.zip
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### Pedestrian Detection SDK
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Pedestrian detection is the use of computer vision technology to determine whether there are pedestrians in the image and to provide accurate positioning, generally represented by a rectangular box. Pedestrian detection technology has strong practical value. It can be combined with pedestrian tracking, pedestrian re-identification, and other technologies, and applied to autonomous driving systems for cars, intelligent video surveillance, human behavior analysis, passenger flow statistics system, intelligent transportation and other fields.
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### SDK Functionality
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- Pedestrian detection, providing detection boxes and confidence
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#### Running Example- PedestrianDetectExample
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- Test image
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After successful operation, the command line should see the following information:
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```text
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[INFO ] - [
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class: "pedestrian", probability: 0.97251, bounds: [x=0.284, y=0.451, width=0.101, height=0.394]
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class: "pedestrian", probability: 0.97015, bounds: [x=0.418, y=0.448, width=0.082, height=0.377]
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class: "pedestrian", probability: 0.96476, bounds: [x=0.568, y=0.423, width=0.105, height=0.411]
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class: "pedestrian", probability: 0.95523, bounds: [x=0.811, y=0.401, width=0.104, height=0.436]
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class: "pedestrian", probability: 0.93908, bounds: [x=0.680, y=0.433, width=0.074, height=0.352]
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]
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```
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### Open Source Algorithms
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#### 1. Open source algorithms used by SDK
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- [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)
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#### 2. How is the model exported?
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- [export_model](https://github.com/PaddlePaddle/PaddleDetection/blob/release%2F2.4/tools/export_model.py)
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- [how_to_create_paddlepaddle_model](http://docs.djl.ai/docs/paddlepaddle/how_to_create_paddlepaddle_model_zh.html)
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