diff options
Diffstat (limited to 'vendor/github.com/disintegration/imaging/convolution.go')
-rw-r--r-- | vendor/github.com/disintegration/imaging/convolution.go | 148 |
1 files changed, 0 insertions, 148 deletions
diff --git a/vendor/github.com/disintegration/imaging/convolution.go b/vendor/github.com/disintegration/imaging/convolution.go deleted file mode 100644 index 11eddc16..00000000 --- a/vendor/github.com/disintegration/imaging/convolution.go +++ /dev/null @@ -1,148 +0,0 @@ -package imaging - -import ( - "image" -) - -// ConvolveOptions are convolution parameters. -type ConvolveOptions struct { - // If Normalize is true the kernel is normalized before convolution. - Normalize bool - - // If Abs is true the absolute value of each color channel is taken after convolution. - Abs bool - - // Bias is added to each color channel value after convolution. - Bias int -} - -// Convolve3x3 convolves the image with the specified 3x3 convolution kernel. -// Default parameters are used if a nil *ConvolveOptions is passed. -func Convolve3x3(img image.Image, kernel [9]float64, options *ConvolveOptions) *image.NRGBA { - return convolve(img, kernel[:], options) -} - -// Convolve5x5 convolves the image with the specified 5x5 convolution kernel. -// Default parameters are used if a nil *ConvolveOptions is passed. -func Convolve5x5(img image.Image, kernel [25]float64, options *ConvolveOptions) *image.NRGBA { - return convolve(img, kernel[:], options) -} - -func convolve(img image.Image, kernel []float64, options *ConvolveOptions) *image.NRGBA { - src := toNRGBA(img) - w := src.Bounds().Max.X - h := src.Bounds().Max.Y - dst := image.NewNRGBA(image.Rect(0, 0, w, h)) - - if w < 1 || h < 1 { - return dst - } - - if options == nil { - options = &ConvolveOptions{} - } - - if options.Normalize { - normalizeKernel(kernel) - } - - type coef struct { - x, y int - k float64 - } - var coefs []coef - var m int - - switch len(kernel) { - case 9: - m = 1 - case 25: - m = 2 - } - - i := 0 - for y := -m; y <= m; y++ { - for x := -m; x <= m; x++ { - if kernel[i] != 0 { - coefs = append(coefs, coef{x: x, y: y, k: kernel[i]}) - } - i++ - } - } - - parallel(0, h, func(ys <-chan int) { - for y := range ys { - for x := 0; x < w; x++ { - var r, g, b float64 - for _, c := range coefs { - ix := x + c.x - if ix < 0 { - ix = 0 - } else if ix >= w { - ix = w - 1 - } - - iy := y + c.y - if iy < 0 { - iy = 0 - } else if iy >= h { - iy = h - 1 - } - - off := iy*src.Stride + ix*4 - s := src.Pix[off : off+3 : off+3] - r += float64(s[0]) * c.k - g += float64(s[1]) * c.k - b += float64(s[2]) * c.k - } - - if options.Abs { - if r < 0 { - r = -r - } - if g < 0 { - g = -g - } - if b < 0 { - b = -b - } - } - - if options.Bias != 0 { - r += float64(options.Bias) - g += float64(options.Bias) - b += float64(options.Bias) - } - - srcOff := y*src.Stride + x*4 - dstOff := y*dst.Stride + x*4 - d := dst.Pix[dstOff : dstOff+4 : dstOff+4] - d[0] = clamp(r) - d[1] = clamp(g) - d[2] = clamp(b) - d[3] = src.Pix[srcOff+3] - } - } - }) - - return dst -} - -func normalizeKernel(kernel []float64) { - var sum, sumpos float64 - for i := range kernel { - sum += kernel[i] - if kernel[i] > 0 { - sumpos += kernel[i] - } - } - if sum != 0 { - for i := range kernel { - kernel[i] /= sum - } - } else if sumpos != 0 { - for i := range kernel { - kernel[i] /= sumpos - } - } -} |