mirror of
https://gitee.com/gitea/gitea.git
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621 lines
20 KiB
Go
Vendored
621 lines
20 KiB
Go
Vendored
/*
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Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>
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Permission to use, copy, modify, and/or distribute this software for any purpose
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with or without fee is hereby granted, provided that the above copyright notice
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and this permission notice appear in all copies.
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THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
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REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
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FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
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INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
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OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
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TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
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THIS SOFTWARE.
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*/
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// Package resize implements various image resizing methods.
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//
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// The package works with the Image interface described in the image package.
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// Various interpolation methods are provided and multiple processors may be
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// utilized in the computations.
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//
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// Example:
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// imgResized := resize.Resize(1000, 0, imgOld, resize.MitchellNetravali)
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package resize
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import (
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"image"
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"runtime"
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"sync"
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)
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// An InterpolationFunction provides the parameters that describe an
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// interpolation kernel. It returns the number of samples to take
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// and the kernel function to use for sampling.
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type InterpolationFunction int
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// InterpolationFunction constants
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const (
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// Nearest-neighbor interpolation
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NearestNeighbor InterpolationFunction = iota
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// Bilinear interpolation
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Bilinear
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// Bicubic interpolation (with cubic hermite spline)
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Bicubic
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// Mitchell-Netravali interpolation
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MitchellNetravali
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// Lanczos interpolation (a=2)
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Lanczos2
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// Lanczos interpolation (a=3)
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Lanczos3
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)
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// kernal, returns an InterpolationFunctions taps and kernel.
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func (i InterpolationFunction) kernel() (int, func(float64) float64) {
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switch i {
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case Bilinear:
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return 2, linear
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case Bicubic:
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return 4, cubic
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case MitchellNetravali:
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return 4, mitchellnetravali
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case Lanczos2:
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return 4, lanczos2
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case Lanczos3:
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return 6, lanczos3
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default:
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// Default to NearestNeighbor.
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return 2, nearest
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}
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}
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// values <1 will sharpen the image
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var blur = 1.0
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// Resize scales an image to new width and height using the interpolation function interp.
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// A new image with the given dimensions will be returned.
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// If one of the parameters width or height is set to 0, its size will be calculated so that
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// the aspect ratio is that of the originating image.
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// The resizing algorithm uses channels for parallel computation.
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// If the input image has width or height of 0, it is returned unchanged.
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func Resize(width, height uint, img image.Image, interp InterpolationFunction) image.Image {
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scaleX, scaleY := calcFactors(width, height, float64(img.Bounds().Dx()), float64(img.Bounds().Dy()))
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if width == 0 {
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width = uint(0.7 + float64(img.Bounds().Dx())/scaleX)
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}
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if height == 0 {
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height = uint(0.7 + float64(img.Bounds().Dy())/scaleY)
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}
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// Trivial case: return input image
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if int(width) == img.Bounds().Dx() && int(height) == img.Bounds().Dy() {
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return img
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}
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// Input image has no pixels
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if img.Bounds().Dx() <= 0 || img.Bounds().Dy() <= 0 {
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return img
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}
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if interp == NearestNeighbor {
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return resizeNearest(width, height, scaleX, scaleY, img, interp)
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}
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taps, kernel := interp.kernel()
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cpus := runtime.GOMAXPROCS(0)
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wg := sync.WaitGroup{}
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// Generic access to image.Image is slow in tight loops.
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// The optimal access has to be determined from the concrete image type.
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switch input := img.(type) {
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case *image.RGBA:
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// 8-bit precision
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temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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resizeRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.NRGBA:
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// 8-bit precision
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temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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resizeNRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.YCbCr:
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// 8-bit precision
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// accessing the YCbCr arrays in a tight loop is slow.
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// converting the image to ycc increases performance by 2x.
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temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)
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result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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in := imageYCbCrToYCC(input)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*ycc)
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go func() {
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defer wg.Done()
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resizeYCbCr(in, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*ycc)
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go func() {
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defer wg.Done()
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resizeYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result.YCbCr()
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case *image.RGBA64:
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// 16-bit precision
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temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA64)
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go func() {
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defer wg.Done()
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resizeRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.RGBA64)
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go func() {
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defer wg.Done()
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resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.NRGBA64:
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// 16-bit precision
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temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA64)
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go func() {
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defer wg.Done()
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resizeNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.RGBA64)
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go func() {
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defer wg.Done()
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resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.Gray:
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// 8-bit precision
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temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewGray(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.Gray)
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go func() {
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defer wg.Done()
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resizeGray(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.Gray)
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go func() {
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defer wg.Done()
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resizeGray(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.Gray16:
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// 16-bit precision
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temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.Gray16)
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go func() {
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defer wg.Done()
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resizeGray16(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.Gray16)
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go func() {
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defer wg.Done()
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resizeGray16(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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default:
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// 16-bit precision
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temp := image.NewRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))
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result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA64)
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go func() {
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defer wg.Done()
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resizeGeneric(img, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.RGBA64)
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go func() {
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defer wg.Done()
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resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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}
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}
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func resizeNearest(width, height uint, scaleX, scaleY float64, img image.Image, interp InterpolationFunction) image.Image {
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taps, _ := interp.kernel()
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cpus := runtime.GOMAXPROCS(0)
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wg := sync.WaitGroup{}
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switch input := img.(type) {
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case *image.RGBA:
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// 8-bit precision
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temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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nearestRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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// horizontal filter on transposed image, result is not transposed
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coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
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wg.Add(cpus)
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for i := 0; i < cpus; i++ {
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slice := makeSlice(result, i, cpus).(*image.RGBA)
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go func() {
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defer wg.Done()
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nearestRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
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}
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wg.Wait()
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return result
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case *image.NRGBA:
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// 8-bit precision
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temp := image.NewNRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
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result := image.NewNRGBA(image.Rect(0, 0, int(width), int(height)))
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|
|
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// horizontal filter, results in transposed temporary image
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coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
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wg.Add(cpus)
|
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for i := 0; i < cpus; i++ {
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slice := makeSlice(temp, i, cpus).(*image.NRGBA)
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go func() {
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defer wg.Done()
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nearestNRGBA(input, slice, scaleX, coeffs, offset, filterLength)
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}()
|
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}
|
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wg.Wait()
|
|
|
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// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
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wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
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slice := makeSlice(result, i, cpus).(*image.NRGBA)
|
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go func() {
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defer wg.Done()
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nearestNRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
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}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
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case *image.YCbCr:
|
|
// 8-bit precision
|
|
// accessing the YCbCr arrays in a tight loop is slow.
|
|
// converting the image to ycc increases performance by 2x.
|
|
temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)
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result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)
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coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
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in := imageYCbCrToYCC(input)
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|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
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slice := makeSlice(temp, i, cpus).(*ycc)
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|
go func() {
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defer wg.Done()
|
|
nearestYCbCr(in, slice, scaleX, coeffs, offset, filterLength)
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|
}()
|
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}
|
|
wg.Wait()
|
|
|
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coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*ycc)
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go func() {
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defer wg.Done()
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nearestYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)
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|
}()
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}
|
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wg.Wait()
|
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return result.YCbCr()
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|
case *image.RGBA64:
|
|
// 16-bit precision
|
|
temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
|
|
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
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|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.RGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
case *image.NRGBA64:
|
|
// 16-bit precision
|
|
temp := image.NewNRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
|
|
result := image.NewNRGBA64(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.NRGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.NRGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestNRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
case *image.Gray:
|
|
// 8-bit precision
|
|
temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
|
|
result := image.NewGray(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.Gray)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray(input, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.Gray)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
case *image.Gray16:
|
|
// 16-bit precision
|
|
temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
|
|
result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.Gray16)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray16(input, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.Gray16)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGray16(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
default:
|
|
// 16-bit precision
|
|
temp := image.NewRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))
|
|
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
|
|
|
|
// horizontal filter, results in transposed temporary image
|
|
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestGeneric(img, slice, scaleX, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
|
|
// horizontal filter on transposed image, result is not transposed
|
|
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
|
|
wg.Add(cpus)
|
|
for i := 0; i < cpus; i++ {
|
|
slice := makeSlice(result, i, cpus).(*image.RGBA64)
|
|
go func() {
|
|
defer wg.Done()
|
|
nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
|
|
}()
|
|
}
|
|
wg.Wait()
|
|
return result
|
|
}
|
|
|
|
}
|
|
|
|
// Calculates scaling factors using old and new image dimensions.
|
|
func calcFactors(width, height uint, oldWidth, oldHeight float64) (scaleX, scaleY float64) {
|
|
if width == 0 {
|
|
if height == 0 {
|
|
scaleX = 1.0
|
|
scaleY = 1.0
|
|
} else {
|
|
scaleY = oldHeight / float64(height)
|
|
scaleX = scaleY
|
|
}
|
|
} else {
|
|
scaleX = oldWidth / float64(width)
|
|
if height == 0 {
|
|
scaleY = scaleX
|
|
} else {
|
|
scaleY = oldHeight / float64(height)
|
|
}
|
|
}
|
|
return
|
|
}
|
|
|
|
type imageWithSubImage interface {
|
|
image.Image
|
|
SubImage(image.Rectangle) image.Image
|
|
}
|
|
|
|
func makeSlice(img imageWithSubImage, i, n int) image.Image {
|
|
return img.SubImage(image.Rect(img.Bounds().Min.X, img.Bounds().Min.Y+i*img.Bounds().Dy()/n, img.Bounds().Max.X, img.Bounds().Min.Y+(i+1)*img.Bounds().Dy()/n))
|
|
}
|