Update dependencies (#1610)

* Update dependencies

* Update module to go 1.17

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
-		}
-	}
-}