Upgrading server dependancies (#6215)

vendor/github.com/disintegration/imaging/.travis.yml

@@ -9,6 +9,7 @@ go:
   - 1.5
   - 1.6
   - 1.7
+  - 1.8
 
 before_install:
   - go get golang.org/x/tools/cmd/cover

vendor/github.com/disintegration/imaging/LICENSE

@@ -1,6 +1,6 @@
 The MIT License (MIT)
 
-Copyright (c) 2012-2014 Grigory Dryapak
+Copyright (c) 2012-2017 Grigory Dryapak
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

vendor/github.com/disintegration/imaging/README.md

@@ -26,17 +26,18 @@ http://godoc.org/github.com/disintegration/imaging
 A few usage examples can be found below. See the documentation for the full list of supported functions. 
 
 ### Image resizing
+
 ```go
-// resize srcImage to size = 128x128px using the Lanczos filter
+// Resize srcImage to size = 128x128px using the Lanczos filter.
 dstImage128 := imaging.Resize(srcImage, 128, 128, imaging.Lanczos)
 
-// resize srcImage to width = 800px preserving the aspect ratio
+// Resize srcImage to width = 800px preserving the aspect ratio.
 dstImage800 := imaging.Resize(srcImage, 800, 0, imaging.Lanczos)
 
-// scale down srcImage to fit the 800x600px bounding box
+// Scale down srcImage to fit the 800x600px bounding box.
 dstImageFit := imaging.Fit(srcImage, 800, 600, imaging.Lanczos)
 
-// resize and crop the srcImage to fill the 100x100px area
+// Resize and crop the srcImage to fill the 100x100px area.
 dstImageFill := imaging.Fill(srcImage, 100, 100, imaging.Center, imaging.Lanczos)
 ```
 
@@ -53,146 +54,138 @@ The full list of supported filters:  NearestNeighbor, Box, Linear, Hermite, Mitc
 
 **Resampling filters comparison**
 
-Original image. Will be resized from 512x512px to 128x128px. 
+The original image.
 
-![srcImage](http://disintegration.github.io/imaging/in_lena_bw_512.png)
+![srcImage](testdata/lena_512.png)
 
-Filter | Resize result
----|---
-`imaging.NearestNeighbor` | ![dstImage](http://disintegration.github.io/imaging/out_resize_down_nearest.png) 
-`imaging.Box` | ![dstImage](http://disintegration.github.io/imaging/out_resize_down_box.png)
-`imaging.Linear` | ![dstImage](http://disintegration.github.io/imaging/out_resize_down_linear.png)
-`imaging.MitchellNetravali` | ![dstImage](http://disintegration.github.io/imaging/out_resize_down_mitchell.png)
-`imaging.CatmullRom` | ![dstImage](http://disintegration.github.io/imaging/out_resize_down_catrom.png)
-`imaging.Gaussian` | ![dstImage](http://disintegration.github.io/imaging/out_resize_down_gaussian.png)
-`imaging.Lanczos` | ![dstImage](http://disintegration.github.io/imaging/out_resize_down_lanczos.png)
+The same image resized from 512x512px to 128x128px using different resampling filters.
+From faster (lower quality) to slower (higher quality):
 
-**Resize functions comparison**
+Filter                    | Resize result
+--------------------------|---------------------------------------------
+`imaging.NearestNeighbor` | ![dstImage](testdata/out_resize_nearest.png) 
+`imaging.Linear`          | ![dstImage](testdata/out_resize_linear.png)
+`imaging.CatmullRom`      | ![dstImage](testdata/out_resize_catrom.png)
+`imaging.Lanczos`         | ![dstImage](testdata/out_resize_lanczos.png)
 
-Original image:
-
-![srcImage](http://disintegration.github.io/imaging/in.jpg)
-
-Resize the image to width=100px and height=100px:
-
-```go
-dstImage := imaging.Resize(srcImage, 100, 100, imaging.Lanczos)
-```
-![dstImage](http://disintegration.github.io/imaging/out-comp-resize.jpg) 
-
-Resize the image to width=100px preserving the aspect ratio:
-
-```go
-dstImage := imaging.Resize(srcImage, 100, 0, imaging.Lanczos)
-```
-![dstImage](http://disintegration.github.io/imaging/out-comp-fit.jpg) 
-
-Resize the image to fit the 100x100px boundng box preserving the aspect ratio:
-
-```go
-dstImage := imaging.Fit(srcImage, 100, 100, imaging.Lanczos)
-```
-![dstImage](http://disintegration.github.io/imaging/out-comp-fit.jpg) 
-
-Resize and crop the image with a center anchor point to fill the 100x100px area:
-
-```go
-dstImage := imaging.Fill(srcImage, 100, 100, imaging.Center, imaging.Lanczos)
-```
-![dstImage](http://disintegration.github.io/imaging/out-comp-fill.jpg) 
 
 ### Gaussian Blur
+
 ```go
 dstImage := imaging.Blur(srcImage, 0.5)
 ```
 
 Sigma parameter allows to control the strength of the blurring effect.
 
-Original image | Sigma = 0.5 | Sigma = 1.5
----|---|---
-![srcImage](http://disintegration.github.io/imaging/in_lena_bw_128.png) | ![dstImage](http://disintegration.github.io/imaging/out_blur_0.5.png) | ![dstImage](http://disintegration.github.io/imaging/out_blur_1.5.png)
+Original image                     | Sigma = 0.5                            | Sigma = 1.5
+-----------------------------------|----------------------------------------|---------------------------------------
+![srcImage](testdata/lena_128.png) | ![dstImage](testdata/out_blur_0.5.png) | ![dstImage](testdata/out_blur_1.5.png)
 
 ### Sharpening
+
 ```go
 dstImage := imaging.Sharpen(srcImage, 0.5)
 ```
 
-Uses gaussian function internally. Sigma parameter allows to control the strength of the sharpening effect.
+`Sharpen` uses gaussian function internally. Sigma parameter allows to control the strength of the sharpening effect.
 
-Original image | Sigma = 0.5 | Sigma = 1.5
----|---|---
-![srcImage](http://disintegration.github.io/imaging/in_lena_bw_128.png) | ![dstImage](http://disintegration.github.io/imaging/out_sharpen_0.5.png) | ![dstImage](http://disintegration.github.io/imaging/out_sharpen_1.5.png)
+Original image                     | Sigma = 0.5                               | Sigma = 1.5
+-----------------------------------|-------------------------------------------|------------------------------------------
+![srcImage](testdata/lena_128.png) | ![dstImage](testdata/out_sharpen_0.5.png) | ![dstImage](testdata/out_sharpen_1.5.png)
 
 ### Gamma correction
+
 ```go
 dstImage := imaging.AdjustGamma(srcImage, 0.75)
 ```
 
-Original image | Gamma = 0.75 | Gamma = 1.25
----|---|---
-![srcImage](http://disintegration.github.io/imaging/in_lena_bw_128.png) | ![dstImage](http://disintegration.github.io/imaging/out_gamma_0.75.png) | ![dstImage](http://disintegration.github.io/imaging/out_gamma_1.25.png)
+Original image                     | Gamma = 0.75                             | Gamma = 1.25
+-----------------------------------|------------------------------------------|-----------------------------------------
+![srcImage](testdata/lena_128.png) | ![dstImage](testdata/out_gamma_0.75.png) | ![dstImage](testdata/out_gamma_1.25.png)
 
 ### Contrast adjustment
+
 ```go
 dstImage := imaging.AdjustContrast(srcImage, 20)
 ```
 
-Original image | Contrast = 20 | Contrast = -20
----|---|---
-![srcImage](http://disintegration.github.io/imaging/in_lena_bw_128.png) | ![dstImage](http://disintegration.github.io/imaging/out_contrast_p20.png) | ![dstImage](http://disintegration.github.io/imaging/out_contrast_m20.png)
+Original image                     | Contrast = 10                              | Contrast = -10
+-----------------------------------|--------------------------------------------|-------------------------------------------
+![srcImage](testdata/lena_128.png) | ![dstImage](testdata/out_contrast_p10.png) | ![dstImage](testdata/out_contrast_m10.png)
 
 ### Brightness adjustment
+
 ```go
 dstImage := imaging.AdjustBrightness(srcImage, 20)
 ```
 
-Original image | Brightness = 20 | Brightness = -20
----|---|---
-![srcImage](http://disintegration.github.io/imaging/in_lena_bw_128.png) | ![dstImage](http://disintegration.github.io/imaging/out_brightness_p20.png) | ![dstImage](http://disintegration.github.io/imaging/out_brightness_m20.png)
+Original image                     | Brightness = 10                              | Brightness = -10
+-----------------------------------|----------------------------------------------|---------------------------------------------
+![srcImage](testdata/lena_128.png) | ![dstImage](testdata/out_brightness_p10.png) | ![dstImage](testdata/out_brightness_m10.png)
 
-
-### Complete code example
-Here is the code example that loads several images, makes thumbnails of them
-and combines them together side-by-side.
+## Example code
 
 ```go
 package main
 
 import (
-    "image"
-    "image/color"
-    
-    "github.com/disintegration/imaging"
+	"image"
+	"image/color"
+	"log"
+
+	"github.com/disintegration/imaging"
 )
 
 func main() {
+	// Open the test image.
+	src, err := imaging.Open("testdata/lena_512.png")
+	if err != nil {
+		log.Fatalf("Open failed: %v", err)
+	}
 
-    // input files
-    files := []string{"01.jpg", "02.jpg", "03.jpg"}
+	// Crop the original image to 350x350px size using the center anchor.
+	src = imaging.CropAnchor(src, 350, 350, imaging.Center)
 
-    // load images and make 100x100 thumbnails of them
-    var thumbnails []image.Image
-    for _, file := range files {
-        img, err := imaging.Open(file)
-        if err != nil {
-            panic(err)
-        }
-        thumb := imaging.Thumbnail(img, 100, 100, imaging.CatmullRom)
-        thumbnails = append(thumbnails, thumb)
-    }
+	// Resize the cropped image to width = 256px preserving the aspect ratio.
+	src = imaging.Resize(src, 256, 0, imaging.Lanczos)
 
-    // create a new blank image
-    dst := imaging.New(100*len(thumbnails), 100, color.NRGBA{0, 0, 0, 0})
+	// Create a blurred version of the image.
+	img1 := imaging.Blur(src, 2)
 
-    // paste thumbnails into the new image side by side
-    for i, thumb := range thumbnails {
-        dst = imaging.Paste(dst, thumb, image.Pt(i*100, 0))
-    }
+	// Create a grayscale version of the image with higher contrast and sharpness.
+	img2 := imaging.Grayscale(src)
+	img2 = imaging.AdjustContrast(img2, 20)
+	img2 = imaging.Sharpen(img2, 2)
 
-    // save the combined image to file
-    err := imaging.Save(dst, "dst.jpg")
-    if err != nil {
-        panic(err)
-    }
+	// Create an inverted version of the image.
+	img3 := imaging.Invert(src)
+
+	// Create an embossed version of the image using a convolution filter.
+	img4 := imaging.Convolve3x3(
+		src,
+		[9]float64{
+			-1, -1, 0,
+			-1, 1, 1,
+			0, 1, 1,
+		},
+		nil,
+	)
+
+	// Create a new image and paste the four produced images into it.
+	dst := imaging.New(512, 512, color.NRGBA{0, 0, 0, 0})
+	dst = imaging.Paste(dst, img1, image.Pt(0, 0))
+	dst = imaging.Paste(dst, img2, image.Pt(0, 256))
+	dst = imaging.Paste(dst, img3, image.Pt(256, 0))
+	dst = imaging.Paste(dst, img4, image.Pt(256, 256))
+
+	// Save the resulting image using JPEG format.
+	err = imaging.Save(dst, "testdata/out_example.jpg")
+	if err != nil {
+		log.Fatalf("Save failed: %v", err)
+	}
 }
 ```
+
+Output:
+
+![dstImage](testdata/out_example.jpg)

vendor/github.com/disintegration/imaging/adjust_test.go

@@ -206,6 +206,26 @@ func TestAdjustContrast(t *testing.T) {
 	}
 }
 
+func TestAdjustContrastGolden(t *testing.T) {
+	src, err := Open("testdata/lena_128.png")
+	if err != nil {
+		t.Errorf("Open: %v", err)
+	}
+	for name, p := range map[string]float64{
+		"out_contrast_m10.png": -10,
+		"out_contrast_p10.png": 10,
+	} {
+		got := AdjustContrast(src, p)
+		want, err := Open("testdata/" + name)
+		if err != nil {
+			t.Errorf("Open: %v", err)
+		}
+		if !compareNRGBA(got, toNRGBA(want), 0) {
+			t.Errorf("resulting image differs from golden: %s", name)
+		}
+	}
+}
+
 func TestAdjustBrightness(t *testing.T) {
 	td := []struct {
 		desc string
@@ -333,6 +353,26 @@ func TestAdjustBrightness(t *testing.T) {
 	}
 }
 
+func TestAdjustBrightnessGolden(t *testing.T) {
+	src, err := Open("testdata/lena_128.png")
+	if err != nil {
+		t.Errorf("Open: %v", err)
+	}
+	for name, p := range map[string]float64{
+		"out_brightness_m10.png": -10,
+		"out_brightness_p10.png": 10,
+	} {
+		got := AdjustBrightness(src, p)
+		want, err := Open("testdata/" + name)
+		if err != nil {
+			t.Errorf("Open: %v", err)
+		}
+		if !compareNRGBA(got, toNRGBA(want), 0) {
+			t.Errorf("resulting image differs from golden: %s", name)
+		}
+	}
+}
+
 func TestAdjustGamma(t *testing.T) {
 	td := []struct {
 		desc string
@@ -416,6 +456,26 @@ func TestAdjustGamma(t *testing.T) {
 	}
 }
 
+func TestAdjustGammaGolden(t *testing.T) {
+	src, err := Open("testdata/lena_128.png")
+	if err != nil {
+		t.Errorf("Open: %v", err)
+	}
+	for name, g := range map[string]float64{
+		"out_gamma_0.75.png": 0.75,
+		"out_gamma_1.25.png": 1.25,
+	} {
+		got := AdjustGamma(src, g)
+		want, err := Open("testdata/" + name)
+		if err != nil {
+			t.Errorf("Open: %v", err)
+		}
+		if !compareNRGBA(got, toNRGBA(want), 0) {
+			t.Errorf("resulting image differs from golden: %s", name)
+		}
+	}
+}
+
 func TestAdjustSigmoid(t *testing.T) {
 	td := []struct {
 		desc string

vendor/github.com/disintegration/imaging/convolution.go

@@ -0,0 +1,148 @@
+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
+	default:
+		return dst
+	}
+
+	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(h, func(partStart, partEnd int) {
+		for y := partStart; y < partEnd; y++ {
+			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
+					r += float64(src.Pix[off+0]) * c.k
+					g += float64(src.Pix[off+1]) * c.k
+					b += float64(src.Pix[off+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
+				dst.Pix[dstOff+0] = clamp(r)
+				dst.Pix[dstOff+1] = clamp(g)
+				dst.Pix[dstOff+2] = clamp(b)
+				dst.Pix[dstOff+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
+		}
+	}
+}

vendor/github.com/disintegration/imaging/convolution_test.go

@@ -0,0 +1,275 @@
+package imaging
+
+import (
+	"image"
+	"testing"
+)
+
+func TestConvolve3x3(t *testing.T) {
+	testCases := []struct {
+		desc    string
+		src     image.Image
+		kernel  [9]float64
+		options *ConvolveOptions
+		want    *image.NRGBA
+	}{
+		{
+			"Convolve3x3 0x0",
+			&image.NRGBA{
+				Rect:   image.Rect(0, 0, 0, 0),
+				Stride: 0,
+				Pix:    []uint8{},
+			},
+			[9]float64{
+				0, 0, 0,
+				0, 1, 0,
+				0, 0, 0,
+			},
+			nil,
+			&image.NRGBA{Rect: image.Rect(0, 0, 0, 0)},
+		},
+		{
+			"Convolve3x3 4x4 identity",
+			&image.NRGBA{
+				Rect:   image.Rect(-1, -1, 3, 3),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
+					0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
+					0x20, 0x21, 0x22, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2c, 0x2d, 0x2e, 0x2f,
+					0x30, 0x31, 0x32, 0x33, 0x34, 0x35, 0x36, 0x37, 0x38, 0x39, 0x3a, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+			[9]float64{
+				0, 0, 0,
+				0, 1, 0,
+				0, 0, 0,
+			},
+			nil,
+			&image.NRGBA{
+				Rect:   image.Rect(0, 0, 4, 4),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
+					0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
+					0x20, 0x21, 0x22, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2c, 0x2d, 0x2e, 0x2f,
+					0x30, 0x31, 0x32, 0x33, 0x34, 0x35, 0x36, 0x37, 0x38, 0x39, 0x3a, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+		},
+		{
+			"Convolve3x3 4x4 abs",
+			&image.NRGBA{
+				Rect:   image.Rect(-1, -1, 3, 3),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
+					0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
+					0x20, 0x21, 0x22, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2c, 0x2d, 0x2e, 0x2f,
+					0x30, 0x31, 0x32, 0x33, 0x34, 0x35, 0x36, 0x37, 0x38, 0x39, 0x3a, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+			[9]float64{
+				0, 0, 0,
+				0, -1, 0,
+				0, 0, 0,
+			},
+			&ConvolveOptions{Abs: true},
+			&image.NRGBA{
+				Rect:   image.Rect(0, 0, 4, 4),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
+					0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
+					0x20, 0x21, 0x22, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2c, 0x2d, 0x2e, 0x2f,
+					0x30, 0x31, 0x32, 0x33, 0x34, 0x35, 0x36, 0x37, 0x38, 0x39, 0x3a, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+		},
+		{
+			"Convolve3x3 4x4 bias",
+			&image.NRGBA{
+				Rect:   image.Rect(-1, -1, 3, 3),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
+					0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
+					0x20, 0x21, 0x22, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2c, 0x2d, 0x2e, 0x2f,
+					0x30, 0x31, 0x32, 0x33, 0x34, 0x35, 0x36, 0x37, 0x38, 0x39, 0x3a, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+			[9]float64{
+				0, 0, 0,
+				0, 1, 0,
+				0, 0, 0,
+			},
+			&ConvolveOptions{Bias: 0x10},
+			&image.NRGBA{
+				Rect:   image.Rect(0, 0, 4, 4),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x10, 0x11, 0x12, 0x03, 0x14, 0x15, 0x16, 0x07, 0x18, 0x19, 0x1a, 0x0b, 0x1c, 0x1d, 0x1e, 0x0f,
+					0x20, 0x21, 0x22, 0x13, 0x24, 0x25, 0x26, 0x17, 0x28, 0x29, 0x2a, 0x1b, 0x2c, 0x2d, 0x2e, 0x1f,
+					0x30, 0x31, 0x32, 0x23, 0x34, 0x35, 0x36, 0x27, 0x38, 0x39, 0x3a, 0x2b, 0x3c, 0x3d, 0x3e, 0x2f,
+					0x40, 0x41, 0x42, 0x33, 0x44, 0x45, 0x46, 0x37, 0x48, 0x49, 0x4a, 0x3b, 0x4c, 0x4d, 0x4e, 0x3f,
+				},
+			},
+		},
+		{
+			"Convolve3x3 4x4 norm",
+			&image.NRGBA{
+				Rect:   image.Rect(-1, -1, 3, 3),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
+					0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
+					0x20, 0x21, 0x22, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2c, 0x2d, 0x2e, 0x2f,
+					0x30, 0x31, 0x32, 0x33, 0x34, 0x35, 0x36, 0x37, 0x38, 0x39, 0x3a, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+			[9]float64{
+				1, 1, 1,
+				1, 1, 1,
+				1, 1, 1,
+			},
+			&ConvolveOptions{Normalize: true},
+			&image.NRGBA{
+				Rect:   image.Rect(0, 0, 4, 4),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x07, 0x08, 0x09, 0x03, 0x09, 0x0a, 0x0b, 0x07, 0x0d, 0x0e, 0x0f, 0x0b, 0x10, 0x11, 0x12, 0x0f,
+					0x11, 0x12, 0x13, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1b, 0x1c, 0x1d, 0x1f,
+					0x21, 0x22, 0x23, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2b, 0x2c, 0x2d, 0x2f,
+					0x2c, 0x2d, 0x2e, 0x33, 0x2f, 0x30, 0x31, 0x37, 0x33, 0x34, 0x35, 0x3b, 0x35, 0x36, 0x37, 0x3f,
+				},
+			},
+		},
+		{
+			"Convolve3x3 3x3 laplacian",
+			&image.NRGBA{
+				Rect:   image.Rect(-1, -1, 2, 2),
+				Stride: 3 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x01, 0xff, 0x00, 0x01, 0x02, 0xff, 0x00, 0x01, 0x03, 0xff,
+					0x00, 0x01, 0x04, 0xff, 0x10, 0x10, 0x10, 0xff, 0x00, 0x01, 0x05, 0xff,
+					0x00, 0x01, 0x06, 0xff, 0x00, 0x01, 0x07, 0xff, 0x00, 0x01, 0x08, 0xff,
+				},
+			},
+			[9]float64{
+				-1, -1, -1,
+				-1, 8, -1,
+				-1, -1, -1,
+			},
+			nil,
+			&image.NRGBA{
+				Rect:   image.Rect(0, 0, 3, 3),
+				Stride: 3 * 4,
+				Pix: []uint8{
+					0x00, 0x00, 0x00, 0xff, 0x00, 0x00, 0x00, 0xff, 0x00, 0x00, 0x00, 0xff,
+					0x00, 0x00, 0x00, 0xff, 0x80, 0x78, 0x5c, 0xff, 0x00, 0x00, 0x00, 0xff,
+					0x00, 0x00, 0x00, 0xff, 0x00, 0x00, 0x00, 0xff, 0x00, 0x00, 0x00, 0xff,
+				},
+			},
+		},
+	}
+
+	for _, tc := range testCases {
+		got := Convolve3x3(tc.src, tc.kernel, tc.options)
+		want := tc.want
+		if !compareNRGBA(got, want, 0) {
+			t.Errorf("test [%s] failed: want %#v got %#v", tc.desc, want, got)
+		}
+	}
+}
+
+func TestConvolve5x5(t *testing.T) {
+	testCases := []struct {
+		desc    string
+		src     image.Image
+		kernel  [25]float64
+		options *ConvolveOptions
+		want    *image.NRGBA
+	}{
+		{
+			"Convolve5x5 4x4 translate",
+			&image.NRGBA{
+				Rect:   image.Rect(-1, -1, 3, 3),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
+					0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
+					0x20, 0x21, 0x22, 0x23, 0x24, 0x25, 0x26, 0x27, 0x28, 0x29, 0x2a, 0x2b, 0x2c, 0x2d, 0x2e, 0x2f,
+					0x30, 0x31, 0x32, 0x33, 0x34, 0x35, 0x36, 0x37, 0x38, 0x39, 0x3a, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+			[25]float64{
+				0, 0, 0, 0, 0,
+				0, 0, 0, 0, 0,
+				0, 0, 0, 0, 0,
+				0, 0, 0, 0, 0,
+				0, 0, 0, 0, 1,
+			},
+			nil,
+			&image.NRGBA{
+				Rect:   image.Rect(0, 0, 4, 4),
+				Stride: 4 * 4,
+				Pix: []uint8{
+					0x28, 0x29, 0x2a, 0x03, 0x2c, 0x2d, 0x2e, 0x07, 0x2c, 0x2d, 0x2e, 0x0b, 0x2c, 0x2d, 0x2e, 0x0f,
+					0x38, 0x39, 0x3a, 0x13, 0x3c, 0x3d, 0x3e, 0x17, 0x3c, 0x3d, 0x3e, 0x1b, 0x3c, 0x3d, 0x3e, 0x1f,
+					0x38, 0x39, 0x3a, 0x23, 0x3c, 0x3d, 0x3e, 0x27, 0x3c, 0x3d, 0x3e, 0x2b, 0x3c, 0x3d, 0x3e, 0x2f,
+					0x38, 0x39, 0x3a, 0x33, 0x3c, 0x3d, 0x3e, 0x37, 0x3c, 0x3d, 0x3e, 0x3b, 0x3c, 0x3d, 0x3e, 0x3f,
+				},
+			},
+		},
+	}
+
+	for _, tc := range testCases {
+		got := Convolve5x5(tc.src, tc.kernel, tc.options)
+		want := tc.want
+		if !compareNRGBA(got, want, 0) {
+			t.Errorf("test [%s] failed: want %#v got %#v", tc.desc, want, got)
+		}
+	}
+}
+
+func BenchmarkConvolve3x3(b *testing.B) {
+	b.StopTimer()
+	img, err := Open("testdata/lena_512.png")
+	if err != nil {
+		b.Fatalf("Open: %v", err)
+	}
+	b.StartTimer()
+	for i := 0; i < b.N; i++ {
+		Convolve3x3(
+			img,
+			[9]float64{
+				-1, -1, 0,
+				-1, 0, 1,
+				0, 1, 1,
+			},
+			nil,
+		)
+	}
+}
+
+func BenchmarkConvolve5x5(b *testing.B) {
+	b.StopTimer()
+	img, err := Open("testdata/lena_512.png")
+	if err != nil {
+		b.Fatalf("Open: %v", err)
+	}
+	b.StartTimer()
+	for i := 0; i < b.N; i++ {
+		Convolve5x5(
+			img,
+			[25]float64{
+				-1, -1, -1, -1, 0,
+				-1, -1, -1, 0, 1,
+				-1, -1, 0, 1, 1,
+				-1, 0, 1, 1, 1,
+				0, 1, 1, 1, 1,
+			},
+			nil,
+		)
+	}
+}

vendor/github.com/disintegration/imaging/effects.go

@@ -62,8 +62,7 @@ func blurHorizontal(src *image.NRGBA, kernel []float64) *image.NRGBA {
 			}
 
 			for y := 0; y < height; y++ {
-
-				r, g, b, a := 0.0, 0.0, 0.0, 0.0
+				var r, g, b, a float64
 				for ix := start; ix <= end; ix++ {
 					weight := kernel[absint(x-ix)]
 					i := y*src.Stride + ix*4
@@ -74,17 +73,11 @@ func blurHorizontal(src *image.NRGBA, kernel []float64) *image.NRGBA {
 					a += wa
 				}
 
-				r = math.Min(math.Max(r/a, 0.0), 255.0)
-				g = math.Min(math.Max(g/a, 0.0), 255.0)
-				b = math.Min(math.Max(b/a, 0.0), 255.0)
-				a = math.Min(math.Max(a/weightSum, 0.0), 255.0)
-
 				j := y*dst.Stride + x*4
-				dst.Pix[j+0] = uint8(r + 0.5)
-				dst.Pix[j+1] = uint8(g + 0.5)
-				dst.Pix[j+2] = uint8(b + 0.5)
-				dst.Pix[j+3] = uint8(a + 0.5)
-
+				dst.Pix[j+0] = clamp(r / a)
+				dst.Pix[j+1] = clamp(g / a)
+				dst.Pix[j+2] = clamp(b / a)
+				dst.Pix[j+3] = clamp(a / weightSum)
 			}
 		}
 	})
@@ -117,8 +110,7 @@ func blurVertical(src *image.NRGBA, kernel []float64) *image.NRGBA {
 			}
 
 			for x := 0; x < width; x++ {
-
-				r, g, b, a := 0.0, 0.0, 0.0, 0.0
+				var r, g, b, a float64
 				for iy := start; iy <= end; iy++ {
 					weight := kernel[absint(y-iy)]
 					i := iy*src.Stride + x*4
@@ -129,17 +121,11 @@ func blurVertical(src *image.NRGBA, kernel []float64) *image.NRGBA {
 					a += wa
 				}
 
-				r = math.Min(math.Max(r/a, 0.0), 255.0)
-				g = math.Min(math.Max(g/a, 0.0), 255.0)
-				b = math.Min(math.Max(b/a, 0.0), 255.0)
-				a = math.Min(math.Max(a/weightSum, 0.0), 255.0)
-
 				j := y*dst.Stride + x*4
-				dst.Pix[j+0] = uint8(r + 0.5)
-				dst.Pix[j+1] = uint8(g + 0.5)
-				dst.Pix[j+2] = uint8(b + 0.5)
-				dst.Pix[j+3] = uint8(a + 0.5)
-
+				dst.Pix[j+0] = clamp(r / a)
+				dst.Pix[j+1] = clamp(g / a)
+				dst.Pix[j+2] = clamp(b / a)
+				dst.Pix[j+3] = clamp(a / weightSum)
 			}
 		}
 	})
@@ -173,7 +159,7 @@ func Sharpen(img image.Image, sigma float64) *image.NRGBA {
 				i := y*src.Stride + x*4
 				for j := 0; j < 4; j++ {
 					k := i + j
-					val := int(src.Pix[k]) + (int(src.Pix[k]) - int(blurred.Pix[k]))
+					val := int(src.Pix[k])<<1 - int(blurred.Pix[k])
 					if val < 0 {
 						val = 0
 					} else if val > 255 {

vendor/github.com/disintegration/imaging/effects_test.go

@@ -88,6 +88,38 @@ func TestBlur(t *testing.T) {
 	}
 }
 
+func TestBlurGolden(t *testing.T) {
+	src, err := Open("testdata/lena_128.png")
+	if err != nil {
+		t.Errorf("Open: %v", err)
+	}
+	for name, sigma := range map[string]float64{
+		"out_blur_0.5.png": 0.5,
+		"out_blur_1.5.png": 1.5,
+	} {
+		got := Blur(src, sigma)
+		want, err := Open("testdata/" + name)
+		if err != nil {
+			t.Errorf("Open: %v", err)
+		}
+		if !compareNRGBA(got, toNRGBA(want), 0) {
+			t.Errorf("resulting image differs from golden: %s", name)
+		}
+	}
+}
+
+func BenchmarkBlur(b *testing.B) {
+	b.StopTimer()
+	img, err := Open("testdata/lena_512.png")
+	if err != nil {
+		b.Fatalf("Open: %v", err)
+	}
+	b.StartTimer()
+	for i := 0; i < b.N; i++ {
+		Blur(img, 3)
+	}
+}
+
 func TestSharpen(t *testing.T) {
 	td := []struct {
 		desc  string
@@ -188,3 +220,35 @@ func TestSharpen(t *testing.T) {
 		}
 	}
 }
+
+func TestSharpenGolden(t *testing.T) {
+	src, err := Open("testdata/lena_128.png")
+	if err != nil {
+		t.Errorf("Open: %v", err)
+	}
+	for name, sigma := range map[string]float64{
+		"out_sharpen_0.5.png": 0.5,
+		"out_sharpen_1.5.png": 1.5,
+	} {
+		got := Sharpen(src, sigma)
+		want, err := Open("testdata/" + name)
+		if err != nil {
+			t.Errorf("Open: %v", err)
+		}
+		if !compareNRGBA(got, toNRGBA(want), 0) {
+			t.Errorf("resulting image differs from golden: %s", name)
+		}
+	}
+}
+
+func BenchmarkSharpen(b *testing.B) {
+	b.StopTimer()
+	img, err := Open("testdata/lena_512.png")
+	if err != nil {
+		b.Fatalf("Open: %v", err)
+	}
+	b.StartTimer()
+	for i := 0; i < b.N; i++ {
+		Sharpen(img, 3)
+	}
+}

vendor/github.com/disintegration/imaging/example_test.go

@@ -0,0 +1,58 @@
+package imaging_test
+
+import (
+	"image"
+	"image/color"
+	"log"
+
+	"github.com/disintegration/imaging"
+)
+
+func Example() {
+	// Open the test image.
+	src, err := imaging.Open("testdata/lena_512.png")
+	if err != nil {
+		log.Fatalf("Open failed: %v", err)
+	}
+
+	// Crop the original image to 350x350px size using the center anchor.
+	src = imaging.CropAnchor(src, 350, 350, imaging.Center)
+
+	// Resize the cropped image to width = 256px preserving the aspect ratio.
+	src = imaging.Resize(src, 256, 0, imaging.Lanczos)
+
+	// Create a blurred version of the image.
+	img1 := imaging.Blur(src, 2)
+
+	// Create a grayscale version of the image with higher contrast and sharpness.
+	img2 := imaging.Grayscale(src)
+	img2 = imaging.AdjustContrast(img2, 20)
+	img2 = imaging.Sharpen(img2, 2)
+
+	// Create an inverted version of the image.
+	img3 := imaging.Invert(src)
+
+	// Create an embossed version of the image using a convolution filter.
+	img4 := imaging.Convolve3x3(
+		src,
+		[9]float64{
+			-1, -1, 0,
+			-1, 1, 1,
+			0, 1, 1,
+		},
+		nil,
+	)
+
+	// Create a new image and paste the four produced images into it.
+	dst := imaging.New(512, 512, color.NRGBA{0, 0, 0, 0})
+	dst = imaging.Paste(dst, img1, image.Pt(0, 0))
+	dst = imaging.Paste(dst, img2, image.Pt(0, 256))
+	dst = imaging.Paste(dst, img3, image.Pt(256, 0))
+	dst = imaging.Paste(dst, img4, image.Pt(256, 256))
+
+	// Save the resulting image using JPEG format.
+	err = imaging.Save(dst, "testdata/out_example.jpg")
+	if err != nil {
+		log.Fatalf("Save failed: %v", err)
+	}
+}

vendor/github.com/disintegration/imaging/helpers.go

@@ -1,11 +1,9 @@
-/*
-Package imaging provides basic image manipulation functions (resize, rotate, flip, crop, etc.).
-This package is based on the standard Go image package and works best along with it.
-
-Image manipulation functions provided by the package take any image type
-that implements `image.Image` interface as an input, and return a new image of
-`*image.NRGBA` type (32bit RGBA colors, not premultiplied by alpha).
-*/
+// Package imaging provides basic image manipulation functions (resize, rotate, flip, crop, etc.).
+// This package is based on the standard Go image package and works best along with it.
+//
+// Image manipulation functions provided by the package take any image type
+// that implements `image.Image` interface as an input, and return a new image of
+// `*image.NRGBA` type (32bit RGBA colors, not premultiplied by alpha).
 package imaging
 
 import (
@@ -24,8 +22,10 @@ import (
 	"golang.org/x/image/tiff"
 )
 
+// Format is an image file format.
 type Format int
 
+// Image file formats.
 const (
 	JPEG Format = iota
 	PNG
@@ -52,6 +52,7 @@ func (f Format) String() string {
 }
 
 var (
+	// ErrUnsupportedFormat means the given image format (or file extension) is unsupported.
 	ErrUnsupportedFormat = errors.New("imaging: unsupported image format")
 )
 
@@ -194,15 +195,12 @@ func Clone(img image.Image) *image.NRGBA {
 				di := dst.PixOffset(0, dstY)
 				si := src.PixOffset(srcMinX, srcMinY+dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					dst.Pix[di+0] = src.Pix[si+0]
 					dst.Pix[di+1] = src.Pix[si+2]
 					dst.Pix[di+2] = src.Pix[si+4]
 					dst.Pix[di+3] = src.Pix[si+6]
-
 					di += 4
 					si += 8
-
 				}
 			}
 		})
@@ -213,9 +211,9 @@ func Clone(img image.Image) *image.NRGBA {
 				di := dst.PixOffset(0, dstY)
 				si := src.PixOffset(srcMinX, srcMinY+dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					a := src.Pix[si+3]
 					dst.Pix[di+3] = a
+
 					switch a {
 					case 0:
 						dst.Pix[di+0] = 0
@@ -237,7 +235,6 @@ func Clone(img image.Image) *image.NRGBA {
 
 					di += 4
 					si += 4
-
 				}
 			}
 		})
@@ -248,9 +245,9 @@ func Clone(img image.Image) *image.NRGBA {
 				di := dst.PixOffset(0, dstY)
 				si := src.PixOffset(srcMinX, srcMinY+dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					a := src.Pix[si+6]
 					dst.Pix[di+3] = a
+
 					switch a {
 					case 0:
 						dst.Pix[di+0] = 0
@@ -272,7 +269,6 @@ func Clone(img image.Image) *image.NRGBA {
 
 					di += 4
 					si += 8
-
 				}
 			}
 		})
@@ -283,16 +279,13 @@ func Clone(img image.Image) *image.NRGBA {
 				di := dst.PixOffset(0, dstY)
 				si := src.PixOffset(srcMinX, srcMinY+dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					c := src.Pix[si]
 					dst.Pix[di+0] = c
 					dst.Pix[di+1] = c
 					dst.Pix[di+2] = c
 					dst.Pix[di+3] = 0xff
-
 					di += 4
 					si += 1
-
 				}
 			}
 		})
@@ -303,16 +296,13 @@ func Clone(img image.Image) *image.NRGBA {
 				di := dst.PixOffset(0, dstY)
 				si := src.PixOffset(srcMinX, srcMinY+dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					c := src.Pix[si]
 					dst.Pix[di+0] = c
 					dst.Pix[di+1] = c
 					dst.Pix[di+2] = c
 					dst.Pix[di+3] = 0xff
-
 					di += 4
 					si += 2
-
 				}
 			}
 		})
@@ -322,7 +312,6 @@ func Clone(img image.Image) *image.NRGBA {
 			for dstY := partStart; dstY < partEnd; dstY++ {
 				di := dst.PixOffset(0, dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					srcX := srcMinX + dstX
 					srcY := srcMinY + dstY
 					siy := src.YOffset(srcX, srcY)
@@ -332,9 +321,7 @@ func Clone(img image.Image) *image.NRGBA {
 					dst.Pix[di+1] = g
 					dst.Pix[di+2] = b
 					dst.Pix[di+3] = 0xff
-
 					di += 4
-
 				}
 			}
 		})
@@ -345,22 +332,18 @@ func Clone(img image.Image) *image.NRGBA {
 		for i := 0; i < plen; i++ {
 			pnew[i] = color.NRGBAModel.Convert(src.Palette[i]).(color.NRGBA)
 		}
-
 		parallel(dstH, func(partStart, partEnd int) {
 			for dstY := partStart; dstY < partEnd; dstY++ {
 				di := dst.PixOffset(0, dstY)
 				si := src.PixOffset(srcMinX, srcMinY+dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					c := pnew[src.Pix[si]]
 					dst.Pix[di+0] = c.R
 					dst.Pix[di+1] = c.G
 					dst.Pix[di+2] = c.B
 					dst.Pix[di+3] = c.A
-
 					di += 4
 					si += 1
-
 				}
 			}
 		})
@@ -370,15 +353,12 @@ func Clone(img image.Image) *image.NRGBA {
 			for dstY := partStart; dstY < partEnd; dstY++ {
 				di := dst.PixOffset(0, dstY)
 				for dstX := 0; dstX < dstW; dstX++ {
-
 					c := color.NRGBAModel.Convert(img.At(srcMinX+dstX, srcMinY+dstY)).(color.NRGBA)
 					dst.Pix[di+0] = c.R
 					dst.Pix[di+1] = c.G
 					dst.Pix[di+2] = c.B
 					dst.Pix[di+3] = c.A
-
 					di += 4
-
 				}
 			}
 		})
@@ -388,7 +368,7 @@ func Clone(img image.Image) *image.NRGBA {
 	return dst
 }
 
-// This function used internally to convert any image type to NRGBA if needed.
+// toNRGBA converts any image type to *image.NRGBA with min-point at (0, 0).
 func toNRGBA(img image.Image) *image.NRGBA {
 	srcBounds := img.Bounds()
 	if srcBounds.Min.X == 0 && srcBounds.Min.Y == 0 {

vendor/github.com/disintegration/imaging/histogram.go

@@ -17,7 +17,7 @@ func Histogram(img image.Image) [256]float64 {
 	var total float64
 
 	if width == 0 || height == 0 {
-		return histogram		
+		return histogram
 	}
 
 	for y := 0; y < height; y++ {

vendor/github.com/disintegration/imaging/histogram_test.go

@@ -36,7 +36,7 @@ func TestHistogram(t *testing.T) {
 	for _, val := range h {
 		if val != 0 {
 			t.Errorf("Histogram for an empty image should be a zero histogram.")
-			return 
+			return
 		}
 	}
 }

vendor/github.com/disintegration/imaging/resize.go

@@ -5,17 +5,12 @@ import (
 	"math"
 )
 
-type iwpair struct {
-	i int
-	w int32
+type indexWeight struct {
+	index  int
+	weight float64
 }
 
-type pweights struct {
-	iwpairs []iwpair
-	wsum    int32
-}
-
-func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights {
+func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) [][]indexWeight {
 	du := float64(srcSize) / float64(dstSize)
 	scale := du
 	if scale < 1.0 {
@@ -23,7 +18,7 @@ func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights {
 	}
 	ru := math.Ceil(scale * filter.Support)
 
-	out := make([]pweights, dstSize)
+	out := make([][]indexWeight, dstSize)
 
 	for v := 0; v < dstSize; v++ {
 		fu := (float64(v)+0.5)*du - 0.5
@@ -37,15 +32,19 @@ func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights {
 			endu = srcSize - 1
 		}
 
-		wsum := int32(0)
+		var sum float64
 		for u := startu; u <= endu; u++ {
-			w := int32(0xff * filter.Kernel((float64(u)-fu)/scale))
+			w := filter.Kernel((float64(u) - fu) / scale)
 			if w != 0 {
-				wsum += w
-				out[v].iwpairs = append(out[v].iwpairs, iwpair{u, w})
+				sum += w
+				out[v] = append(out[v], indexWeight{index: u, weight: w})
+			}
+		}
+		if sum != 0 {
+			for i := range out[v] {
+				out[v][i].weight /= sum
 			}
 		}
-		out[v].wsum = wsum
 	}
 
 	return out
@@ -127,22 +126,26 @@ func resizeHorizontal(src *image.NRGBA, width int, filter ResampleFilter) *image
 
 	parallel(dstH, func(partStart, partEnd int) {
 		for dstY := partStart; dstY < partEnd; dstY++ {
+			i0 := dstY * src.Stride
+			j0 := dstY * dst.Stride
 			for dstX := 0; dstX < dstW; dstX++ {
-				var c [4]int64
-				for _, iw := range weights[dstX].iwpairs {
-					i := dstY*src.Stride + iw.i*4
-					a := int64(src.Pix[i+3]) * int64(iw.w)
-					c[0] += int64(src.Pix[i+0]) * a
-					c[1] += int64(src.Pix[i+1]) * a
-					c[2] += int64(src.Pix[i+2]) * a
-					c[3] += a
+				var r, g, b, a float64
+				for _, w := range weights[dstX] {
+					i := i0 + w.index*4
+					aw := float64(src.Pix[i+3]) * w.weight
+					r += float64(src.Pix[i+0]) * aw
+					g += float64(src.Pix[i+1]) * aw
+					b += float64(src.Pix[i+2]) * aw
+					a += aw
+				}
+				if a != 0 {
+					aInv := 1 / a
+					j := j0 + dstX*4
+					dst.Pix[j+0] = clamp(r * aInv)
+					dst.Pix[j+1] = clamp(g * aInv)
+					dst.Pix[j+2] = clamp(b * aInv)
+					dst.Pix[j+3] = clamp(a)
 				}
-				j := dstY*dst.Stride + dstX*4
-				sum := weights[dstX].wsum
-				dst.Pix[j+0] = clampint32(int32(float64(c[0])/float64(c[3]) + 0.5))
-				dst.Pix[j+1] = clampint32(int32(float64(c[1])/float64(c[3]) + 0.5))
-				dst.Pix[j+2] = clampint32(int32(float64(c[2])/float64(c[3]) + 0.5))
-				dst.Pix[j+3] = clampint32(int32(float64(c[3])/float64(sum) + 0.5))
 			}
 		}
 	})
@@ -163,33 +166,33 @@ func resizeVertical(src *image.NRGBA, height int, filter ResampleFilter) *image.
 	weights := precomputeWeights(dstH, srcH, filter)
 
 	parallel(dstW, func(partStart, partEnd int) {
-
 		for dstX := partStart; dstX < partEnd; dstX++ {
 			for dstY := 0; dstY < dstH; dstY++ {
-				var c [4]int64
-				for _, iw := range weights[dstY].iwpairs {
-					i := iw.i*src.Stride + dstX*4
-					a := int64(src.Pix[i+3]) * int64(iw.w)
-					c[0] += int64(src.Pix[i+0]) * a
-					c[1] += int64(src.Pix[i+1]) * a
-					c[2] += int64(src.Pix[i+2]) * a
-					c[3] += a
+				var r, g, b, a float64
+				for _, w := range weights[dstY] {
+					i := w.index*src.Stride + dstX*4
+					aw := float64(src.Pix[i+3]) * w.weight
+					r += float64(src.Pix[i+0]) * aw
+					g += float64(src.Pix[i+1]) * aw
+					b += float64(src.Pix[i+2]) * aw
+					a += aw
+				}
+				if a != 0 {
+					aInv := 1 / a
+					j := dstY*dst.Stride + dstX*4
+					dst.Pix[j+0] = clamp(r * aInv)
+					dst.Pix[j+1] = clamp(g * aInv)
+					dst.Pix[j+2] = clamp(b * aInv)
+					dst.Pix[j+3] = clamp(a)
 				}
-				j := dstY*dst.Stride + dstX*4
-				sum := weights[dstY].wsum
-				dst.Pix[j+0] = clampint32(int32(float64(c[0])/float64(c[3]) + 0.5))
-				dst.Pix[j+1] = clampint32(int32(float64(c[1])/float64(c[3]) + 0.5))
-				dst.Pix[j+2] = clampint32(int32(float64(c[2])/float64(c[3]) + 0.5))
-				dst.Pix[j+3] = clampint32(int32(float64(c[3])/float64(sum) + 0.5))
 			}
 		}
-
 	})
 
 	return dst
 }
 
-// fast nearest-neighbor resize, no filtering
+// resizeNearest is a fast nearest-neighbor resize, no filtering.
 func resizeNearest(src *image.NRGBA, width, height int) *image.NRGBA {
 	dstW, dstH := width, height
 
@@ -205,13 +208,16 @@ func resizeNearest(src *image.NRGBA, width, height int) *image.NRGBA {
 	parallel(dstH, func(partStart, partEnd int) {
 
 		for dstY := partStart; dstY < partEnd; dstY++ {
-			fy := (float64(dstY)+0.5)*dy - 0.5
+			srcY := int((float64(dstY) + 0.5) * dy)
+			if srcY > srcH-1 {
+				srcY = srcH - 1
+			}
 
 			for dstX := 0; dstX < dstW; dstX++ {
-				fx := (float64(dstX)+0.5)*dx - 0.5
-
-				srcX := int(math.Min(math.Max(math.Floor(fx+0.5), 0.0), float64(srcW)))
-				srcY := int(math.Min(math.Max(math.Floor(fy+0.5), 0.0), float64(srcH)))
+				srcX := int((float64(dstX) + 0.5) * dx)
+				if srcX > srcW-1 {
+					srcX = srcW - 1
+				}
 
 				srcOff := srcY*src.Stride + srcX*4
 				dstOff := dstY*dst.Stride + dstX*4
@@ -326,7 +332,7 @@ func Thumbnail(img image.Image, width, height int, filter ResampleFilter) *image
 	return Fill(img, width, height, Center, filter)
 }
 
-// Resample filter struct. It can be used to make custom filters.
+// ResampleFilter is a resampling filter struct. It can be used to define custom filters.
 //
 // Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali,
 // CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.
@@ -361,7 +367,7 @@ type ResampleFilter struct {
 	Kernel  func(float64) float64
 }
 
-// Nearest-neighbor filter, no anti-aliasing.
+// NearestNeighbor is a nearest-neighbor filter (no anti-aliasing).
 var NearestNeighbor ResampleFilter
 
 // Box filter (averaging pixels).
@@ -373,37 +379,37 @@ var Linear ResampleFilter
 // Hermite cubic spline filter (BC-spline; B=0; C=0).
 var Hermite ResampleFilter
 
-// Mitchell-Netravali cubic filter (BC-spline; B=1/3; C=1/3).
+// MitchellNetravali is Mitchell-Netravali cubic filter (BC-spline; B=1/3; C=1/3).
 var MitchellNetravali ResampleFilter
 
-// Catmull-Rom - sharp cubic filter (BC-spline; B=0; C=0.5).
+// CatmullRom is a Catmull-Rom - sharp cubic filter (BC-spline; B=0; C=0.5).
 var CatmullRom ResampleFilter
 
-// Cubic B-spline - smooth cubic filter (BC-spline; B=1; C=0).
+// BSpline is a smooth cubic filter (BC-spline; B=1; C=0).
 var BSpline ResampleFilter
 
-// Gaussian Blurring Filter.
+// Gaussian is a Gaussian blurring Filter.
 var Gaussian ResampleFilter
 
-// Bartlett-windowed sinc filter (3 lobes).
+// Bartlett is a Bartlett-windowed sinc filter (3 lobes).
 var Bartlett ResampleFilter
 
 // Lanczos filter (3 lobes).
 var Lanczos ResampleFilter
 
-// Hann-windowed sinc filter (3 lobes).
+// Hann is a Hann-windowed sinc filter (3 lobes).
 var Hann ResampleFilter
 
-// Hamming-windowed sinc filter (3 lobes).
+// Hamming is a Hamming-windowed sinc filter (3 lobes).
 var Hamming ResampleFilter
 
-// Blackman-windowed sinc filter (3 lobes).
+// Blackman is a Blackman-windowed sinc filter (3 lobes).
 var Blackman ResampleFilter
 
-// Welch-windowed sinc filter (parabolic window, 3 lobes).
+// Welch is a Welch-windowed sinc filter (parabolic window, 3 lobes).
 var Welch ResampleFilter
 
-// Cosine-windowed sinc filter (3 lobes).
+// Cosine is a Cosine-windowed sinc filter (3 lobes).
 var Cosine ResampleFilter
 
 func bcspline(x, b, c float64) float64 {

vendor/github.com/disintegration/imaging/resize_test.go

@@ -108,10 +108,10 @@ func TestResize(t *testing.T) {
 				Rect:   image.Rect(0, 0, 4, 4),
 				Stride: 4 * 4,
 				Pix: []uint8{
-					0x00, 0x00, 0x00, 0x00, 0xff, 0x00, 0x00, 0x3f, 0xff, 0x00, 0x00, 0xc0, 0xff, 0x00, 0x00, 0xff,
-					0x00, 0xff, 0x00, 0x3f, 0x6d, 0x6e, 0x24, 0x6f, 0xb1, 0x13, 0x3a, 0xd0, 0xc0, 0x00, 0x3f, 0xff,
-					0x00, 0xff, 0x00, 0xc0, 0x13, 0xb2, 0x3a, 0xcf, 0x33, 0x32, 0x9a, 0xef, 0x3f, 0x00, 0xc0, 0xff,
-					0x00, 0xff, 0x00, 0xff, 0x00, 0xc0, 0x3f, 0xff, 0x00, 0x3f, 0xc0, 0xff, 0x00, 0x00, 0xff, 0xff,
+					0x00, 0x00, 0x00, 0x00, 0xff, 0x00, 0x00, 0x40, 0xff, 0x00, 0x00, 0xbf, 0xff, 0x00, 0x00, 0xff,
+					0x00, 0xff, 0x00, 0x40, 0x6e, 0x6d, 0x25, 0x70, 0xb0, 0x14, 0x3b, 0xcf, 0xbf, 0x00, 0x40, 0xff,
+					0x00, 0xff, 0x00, 0xbf, 0x14, 0xb0, 0x3b, 0xcf, 0x33, 0x33, 0x99, 0xef, 0x40, 0x00, 0xbf, 0xff,
+					0x00, 0xff, 0x00, 0xff, 0x00, 0xbf, 0x40, 0xff, 0x00, 0x40, 0xbf, 0xff, 0x00, 0x00, 0xff, 0xff,
 				},
 			},
 		},
@@ -158,7 +158,7 @@ func TestResize(t *testing.T) {
 	for _, d := range td {
 		got := Resize(d.src, d.w, d.h, d.f)
 		want := d.want
-		if !compareNRGBA(got, want, 1) {
+		if !compareNRGBA(got, want, 0) {
 			t.Errorf("test [%s] failed: %#v", d.desc, got)
 		}
 	}
@@ -201,6 +201,28 @@ func TestResize(t *testing.T) {
 	}
 }
 
+func TestResizeGolden(t *testing.T) {
+	src, err := Open("testdata/lena_512.png")
+	if err != nil {
+		t.Errorf("Open: %v", err)
+	}
+	for name, filter := range map[string]ResampleFilter{
+		"out_resize_nearest.png": NearestNeighbor,
+		"out_resize_linear.png":  Linear,
+		"out_resize_catrom.png":  CatmullRom,
+		"out_resize_lanczos.png": Lanczos,
+	} {
+		got := Resize(src, 128, 0, filter)
+		want, err := Open("testdata/" + name)
+		if err != nil {
+			t.Errorf("Open: %v", err)
+		}
+		if !compareNRGBA(got, toNRGBA(want), 0) {
+			t.Errorf("resulting image differs from golden: %s", name)
+		}
+	}
+}
+
 func TestFit(t *testing.T) {
 	td := []struct {
 		desc string
@@ -568,3 +590,39 @@ func TestThumbnail(t *testing.T) {
 		}
 	}
 }
+
+func BenchmarkResizeLanczosUp(b *testing.B) {
+	benchmarkResize(b, "testdata/lena_128.png", 512, Lanczos)
+}
+
+func BenchmarkResizeLinearUp(b *testing.B) {
+	benchmarkResize(b, "testdata/lena_128.png", 512, Linear)
+}
+
+func BenchmarkResizeNearestNeighborUp(b *testing.B) {
+	benchmarkResize(b, "testdata/lena_128.png", 512, NearestNeighbor)
+}
+
+func BenchmarkResizeLanczosDown(b *testing.B) {
+	benchmarkResize(b, "testdata/lena_512.png", 128, Lanczos)
+}
+
+func BenchmarkResizeLinearDown(b *testing.B) {
+	benchmarkResize(b, "testdata/lena_512.png", 128, Linear)
+}
+
+func BenchmarkResizeNearestNeighborDown(b *testing.B) {
+	benchmarkResize(b, "testdata/lena_512.png", 128, NearestNeighbor)
+}
+
+func benchmarkResize(b *testing.B, filename string, size int, f ResampleFilter) {
+	b.StopTimer()
+	img, err := Open(filename)
+	if err != nil {
+		b.Fatalf("Open: %v", err)
+	}
+	b.StartTimer()
+	for i := 0; i < b.N; i++ {
+		Resize(img, size, size, f)
+	}
+}

vendor/github.com/disintegration/imaging/tools.go

@@ -8,6 +8,7 @@ import (
 // Anchor is the anchor point for image alignment.
 type Anchor int
 
+// Anchor point positions.
 const (
 	Center Anchor = iota
 	TopLeft

vendor/github.com/disintegration/imaging/tools_test.go

@@ -598,7 +598,7 @@ func TestOverlay(t *testing.T) {
 	for _, d := range td {
 		got := Overlay(d.src1, d.src2, d.p, d.a)
 		want := d.want
-		if !compareNRGBA(got, want, 1) {
+		if !compareNRGBA(got, want, 0) {
 			t.Errorf("test [%s] failed: %#v", d.desc, got)
 		}
 	}

vendor/github.com/disintegration/imaging/utils.go

@@ -1,28 +1,24 @@
 package imaging
 
 import (
-	"math"
 	"runtime"
 	"sync"
 	"sync/atomic"
 )
 
-var parallelizationEnabled = true
-
-// if GOMAXPROCS = 1: no goroutines used
-// if GOMAXPROCS > 1: spawn N=GOMAXPROCS workers in separate goroutines
+// parallel starts parallel image processing based on the current GOMAXPROCS value.
+// If GOMAXPROCS = 1 it uses no parallelization.
+// If GOMAXPROCS > 1 it spawns N=GOMAXPROCS workers in separate goroutines.
 func parallel(dataSize int, fn func(partStart, partEnd int)) {
 	numGoroutines := 1
 	partSize := dataSize
 
-	if parallelizationEnabled {
-		numProcs := runtime.GOMAXPROCS(0)
-		if numProcs > 1 {
-			numGoroutines = numProcs
-			partSize = dataSize / (numGoroutines * 10)
-			if partSize < 1 {
-				partSize = 1
-			}
+	numProcs := runtime.GOMAXPROCS(0)
+	if numProcs > 1 {
+		numGoroutines = numProcs
+		partSize = dataSize / (numGoroutines * 10)
+		if partSize < 1 {
+			partSize = 1
 		}
 	}
 
@@ -54,6 +50,7 @@ func parallel(dataSize int, fn func(partStart, partEnd int)) {
 	}
 }
 
+// absint returns the absolute value of i.
 func absint(i int) int {
 	if i < 0 {
 		return -i
@@ -61,17 +58,14 @@ func absint(i int) int {
 	return i
 }
 
-// clamp & round float64 to uint8 (0..255)
-func clamp(v float64) uint8 {
-	return uint8(math.Min(math.Max(v, 0.0), 255.0) + 0.5)
-}
-
-// clamp int32 to uint8 (0..255)
-func clampint32(v int32) uint8 {
-	if v < 0 {
-		return 0
-	} else if v > 255 {
+// clamp rounds and clamps float64 value to fit into uint8.
+func clamp(x float64) uint8 {
+	v := int64(x + 0.5)
+	if v > 255 {
 		return 255
 	}
-	return uint8(v)
+	if v > 0 {
+		return uint8(v)
+	}
+	return 0
 }

vendor/github.com/disintegration/imaging/utils_test.go

@@ -15,7 +15,7 @@ func testParallelN(enabled bool, n, procs int) bool {
 		}
 	})
 	for i := 0; i < n; i++ {
-		if data[i] != true {
+		if !data[i] {
 			return false
 		}
 	}
@@ -27,7 +27,7 @@ func TestParallel(t *testing.T) {
 	for _, e := range []bool{true, false} {
 		for _, n := range []int{1, 10, 100, 1000} {
 			for _, p := range []int{1, 2, 4, 8, 16, 100} {
-				if testParallelN(e, n, p) != true {
+				if !testParallelN(e, n, p) {
 					t.Errorf("test [parallel %v %d %d] failed", e, n, p)
 				}
 			}
@@ -59,23 +59,3 @@ func TestClamp(t *testing.T) {
 		}
 	}
 }
-
-func TestClampint32(t *testing.T) {
-	td := []struct {
-		i int32
-		u uint8
-	}{
-		{0, 0},
-		{255, 255},
-		{128, 128},
-		{256, 255},
-		{2500, 255},
-		{-10, 0},
-	}
-
-	for _, d := range td {
-		if clampint32(d.i) != d.u {
-			t.Errorf("test [clampint32 %v %v] failed: %v", d.i, d.u, clampint32(d.i))
-		}
-	}
-}