add imaging

Godeps/_workspace/src/github.com/disintegration/imaging/LICENSE

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+The MIT License (MIT)
+
+Copyright (c) 2012-2014 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
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

Godeps/_workspace/src/github.com/disintegration/imaging/README.md

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+# Imaging
+
+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).
+
+## Installation
+
+Imaging requires Go version 1.2 or greater.
+
+    go get -u github.com/disintegration/imaging
+    
+## Documentation
+
+http://godoc.org/github.com/disintegration/imaging
+
+## Usage examples
+
+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
+dstImage128 := imaging.Resize(srcImage, 128, 128, imaging.Lanczos)
+
+// 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
+dstImageFit := imaging.Fit(srcImage, 800, 600, imaging.Lanczos)
+
+// resize and crop the srcImage to make a 100x100px thumbnail
+dstImageThumb := imaging.Thumbnail(srcImage, 100, 100, imaging.Lanczos)
+```
+
+Imaging supports image resizing using various resampling filters. The most notable ones:
+- `NearestNeighbor` - Fastest resampling filter, no antialiasing.
+- `Box` - Simple and fast averaging filter appropriate for downscaling. When upscaling it's similar to NearestNeighbor.
+- `Linear` - Bilinear filter, smooth and reasonably fast.
+- `MitchellNetravali` - А smooth bicubic filter.
+- `CatmullRom` - A sharp bicubic filter. 
+- `Gaussian` - Blurring filter that uses gaussian function, useful for noise removal.
+- `Lanczos` - High-quality resampling filter for photographic images yielding sharp results, but it's slower than cubic filters.
+
+The full list of supported filters:  NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. Custom filters can be created using ResampleFilter struct.
+
+**Resampling filters comparison**
+
+Original image. Will be resized from 512x512px to 128x128px. 
+
+![srcImage](http://disintegration.github.io/imaging/in_lena_bw_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)
+
+### 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)
+
+### Sharpening
+```go
+dstImage := imaging.Sharpen(srcImage, 0.5)
+```
+
+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)
+
+### 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)
+
+### 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)
+
+### 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)
+
+
+### Complete code example
+Here is the code example that loads several images, makes thumbnails of them
+and combines them together side-by-side.
+
+```go
+package main
+
+import (
+    "image"
+    "image/color"
+    
+    "github.com/disintegration/imaging"
+)
+
+func main() {
+
+    // input files
+    files := []string{"01.jpg", "02.jpg", "03.jpg"}
+
+    // 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)
+    }
+
+    // create a new blank image
+    dst := imaging.New(100*len(thumbnails), 100, color.NRGBA{0, 0, 0, 0})
+
+    // paste thumbnails into the new image side by side
+    for i, thumb := range thumbnails {
+        dst = imaging.Paste(dst, thumb, image.Pt(i*100, 0))
+    }
+
+    // save the combined image to file
+    err := imaging.Save(dst, "dst.jpg")
+    if err != nil {
+        panic(err)
+    }
+}
+```

Godeps/_workspace/src/github.com/disintegration/imaging/adjust.go

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+package imaging
+
+import (
+	"image"
+	"image/color"
+	"math"
+)
+
+// AdjustFunc applies the fn function to each pixel of the img image and returns the adjusted image.
+//
+// Example:
+//
+// 	dstImage = imaging.AdjustFunc(
+// 		srcImage,
+// 		func(c color.NRGBA) color.NRGBA {
+// 			// shift the red channel by 16
+//			r := int(c.R) + 16
+//			if r > 255 {
+// 				r = 255
+// 			}
+// 			return color.NRGBA{uint8(r), c.G, c.B, c.A}
+// 		}
+// 	)
+//
+func AdjustFunc(img image.Image, fn func(c color.NRGBA) color.NRGBA) *image.NRGBA {
+	src := toNRGBA(img)
+	width := src.Bounds().Max.X
+	height := src.Bounds().Max.Y
+	dst := image.NewNRGBA(image.Rect(0, 0, width, height))
+
+	parallel(height, func(partStart, partEnd int) {
+		for y := partStart; y < partEnd; y++ {
+			for x := 0; x < width; x++ {
+				i := y*src.Stride + x*4
+				j := y*dst.Stride + x*4
+
+				r := src.Pix[i+0]
+				g := src.Pix[i+1]
+				b := src.Pix[i+2]
+				a := src.Pix[i+3]
+
+				c := fn(color.NRGBA{r, g, b, a})
+
+				dst.Pix[j+0] = c.R
+				dst.Pix[j+1] = c.G
+				dst.Pix[j+2] = c.B
+				dst.Pix[j+3] = c.A
+			}
+		}
+	})
+
+	return dst
+}
+
+// AdjustGamma performs a gamma correction on the image and returns the adjusted image.
+// Gamma parameter must be positive. Gamma = 1.0 gives the original image.
+// Gamma less than 1.0 darkens the image and gamma greater than 1.0 lightens it.
+//
+// Example:
+//
+//	dstImage = imaging.AdjustGamma(srcImage, 0.7)
+//
+func AdjustGamma(img image.Image, gamma float64) *image.NRGBA {
+	e := 1.0 / math.Max(gamma, 0.0001)
+	lut := make([]uint8, 256)
+
+	for i := 0; i < 256; i++ {
+		lut[i] = clamp(math.Pow(float64(i)/255.0, e) * 255.0)
+	}
+
+	fn := func(c color.NRGBA) color.NRGBA {
+		return color.NRGBA{lut[c.R], lut[c.G], lut[c.B], c.A}
+	}
+
+	return AdjustFunc(img, fn)
+}
+
+func sigmoid(a, b, x float64) float64 {
+	return 1 / (1 + math.Exp(b*(a-x)))
+}
+
+// AdjustSigmoid changes the contrast of the image using a sigmoidal function and returns the adjusted image.
+// It's a non-linear contrast change useful for photo adjustments as it preserves highlight and shadow detail.
+// The midpoint parameter is the midpoint of contrast that must be between 0 and 1, typically 0.5.
+// The factor parameter indicates how much to increase or decrease the contrast, typically in range (-10, 10).
+// If the factor parameter is positive the image contrast is increased otherwise the contrast is decreased.
+//
+// Examples:
+//
+//	dstImage = imaging.AdjustSigmoid(srcImage, 0.5, 3.0) // increase the contrast
+//	dstImage = imaging.AdjustSigmoid(srcImage, 0.5, -3.0) // decrease the contrast
+//
+func AdjustSigmoid(img image.Image, midpoint, factor float64) *image.NRGBA {
+	if factor == 0 {
+		return Clone(img)
+	}
+
+	lut := make([]uint8, 256)
+	a := math.Min(math.Max(midpoint, 0.0), 1.0)
+	b := math.Abs(factor)
+	sig0 := sigmoid(a, b, 0)
+	sig1 := sigmoid(a, b, 1)
+	e := 1.0e-6
+
+	if factor > 0 {
+		for i := 0; i < 256; i++ {
+			x := float64(i) / 255.0
+			sigX := sigmoid(a, b, x)
+			f := (sigX - sig0) / (sig1 - sig0)
+			lut[i] = clamp(f * 255.0)
+		}
+	} else {
+		for i := 0; i < 256; i++ {
+			x := float64(i) / 255.0
+			arg := math.Min(math.Max((sig1-sig0)*x+sig0, e), 1.0-e)
+			f := a - math.Log(1.0/arg-1.0)/b
+			lut[i] = clamp(f * 255.0)
+		}
+	}
+
+	fn := func(c color.NRGBA) color.NRGBA {
+		return color.NRGBA{lut[c.R], lut[c.G], lut[c.B], c.A}
+	}
+
+	return AdjustFunc(img, fn)
+}
+
+// AdjustContrast changes the contrast of the image using the percentage parameter and returns the adjusted image.
+// The percentage must be in range (-100, 100). The percentage = 0 gives the original image.
+// The percentage = -100 gives solid grey image.
+//
+// Examples:
+//
+//	dstImage = imaging.AdjustContrast(srcImage, -10) // decrease image contrast by 10%
+//	dstImage = imaging.AdjustContrast(srcImage, 20) // increase image contrast by 20%
+//
+func AdjustContrast(img image.Image, percentage float64) *image.NRGBA {
+	percentage = math.Min(math.Max(percentage, -100.0), 100.0)
+	lut := make([]uint8, 256)
+
+	v := (100.0 + percentage) / 100.0
+	for i := 0; i < 256; i++ {
+		if 0 <= v && v <= 1 {
+			lut[i] = clamp((0.5 + (float64(i)/255.0-0.5)*v) * 255.0)
+		} else if 1 < v && v < 2 {
+			lut[i] = clamp((0.5 + (float64(i)/255.0-0.5)*(1/(2.0-v))) * 255.0)
+		} else {
+			lut[i] = uint8(float64(i)/255.0+0.5) * 255
+		}
+	}
+
+	fn := func(c color.NRGBA) color.NRGBA {
+		return color.NRGBA{lut[c.R], lut[c.G], lut[c.B], c.A}
+	}
+
+	return AdjustFunc(img, fn)
+}
+
+// AdjustBrightness changes the brightness of the image using the percentage parameter and returns the adjusted image.
+// The percentage must be in range (-100, 100). The percentage = 0 gives the original image.
+// The percentage = -100 gives solid black image. The percentage = 100 gives solid white image.
+//
+// Examples:
+//
+//	dstImage = imaging.AdjustBrightness(srcImage, -15) // decrease image brightness by 15%
+//	dstImage = imaging.AdjustBrightness(srcImage, 10) // increase image brightness by 10%
+//
+func AdjustBrightness(img image.Image, percentage float64) *image.NRGBA {
+	percentage = math.Min(math.Max(percentage, -100.0), 100.0)
+	lut := make([]uint8, 256)
+
+	shift := 255.0 * percentage / 100.0
+	for i := 0; i < 256; i++ {
+		lut[i] = clamp(float64(i) + shift)
+	}
+
+	fn := func(c color.NRGBA) color.NRGBA {
+		return color.NRGBA{lut[c.R], lut[c.G], lut[c.B], c.A}
+	}
+
+	return AdjustFunc(img, fn)
+}
+
+// Grayscale produces grayscale version of the image.
+func Grayscale(img image.Image) *image.NRGBA {
+	fn := func(c color.NRGBA) color.NRGBA {
+		f := 0.299*float64(c.R) + 0.587*float64(c.G) + 0.114*float64(c.B)
+		y := uint8(f + 0.5)
+		return color.NRGBA{y, y, y, c.A}
+	}
+	return AdjustFunc(img, fn)
+}
+
+// Invert produces inverted (negated) version of the image.
+func Invert(img image.Image) *image.NRGBA {
+	fn := func(c color.NRGBA) color.NRGBA {
+		return color.NRGBA{255 - c.R, 255 - c.G, 255 - c.B, c.A}
+	}
+	return AdjustFunc(img, fn)
+}

Godeps/_workspace/src/github.com/disintegration/imaging/effects.go

@@ -0,0 +1,187 @@
+package imaging
+
+import (
+	"image"
+	"math"
+)
+
+func gaussianBlurKernel(x, sigma float64) float64 {
+	return math.Exp(-(x*x)/(2*sigma*sigma)) / (sigma * math.Sqrt(2*math.Pi))
+}
+
+// Blur produces a blurred version of the image using a Gaussian function.
+// Sigma parameter must be positive and indicates how much the image will be blurred.
+//
+// Usage example:
+//
+//		dstImage := imaging.Blur(srcImage, 3.5)
+//
+func Blur(img image.Image, sigma float64) *image.NRGBA {
+	if sigma <= 0 {
+		// sigma parameter must be positive!
+		return Clone(img)
+	}
+
+	src := toNRGBA(img)
+	radius := int(math.Ceil(sigma * 3.0))
+	kernel := make([]float64, radius+1)
+
+	for i := 0; i <= radius; i++ {
+		kernel[i] = gaussianBlurKernel(float64(i), sigma)
+	}
+
+	var dst *image.NRGBA
+	dst = blurHorizontal(src, kernel)
+	dst = blurVertical(dst, kernel)
+
+	return dst
+}
+
+func blurHorizontal(src *image.NRGBA, kernel []float64) *image.NRGBA {
+	radius := len(kernel) - 1
+	width := src.Bounds().Max.X
+	height := src.Bounds().Max.Y
+
+	dst := image.NewNRGBA(image.Rect(0, 0, width, height))
+
+	parallel(width, func(partStart, partEnd int) {
+		for x := partStart; x < partEnd; x++ {
+			start := x - radius
+			if start < 0 {
+				start = 0
+			}
+
+			end := x + radius
+			if end > width-1 {
+				end = width - 1
+			}
+
+			weightSum := 0.0
+			for ix := start; ix <= end; ix++ {
+				weightSum += kernel[absint(x-ix)]
+			}
+
+			for y := 0; y < height; y++ {
+
+				r, g, b, a := 0.0, 0.0, 0.0, 0.0
+				for ix := start; ix <= end; ix++ {
+					weight := kernel[absint(x-ix)]
+					i := y*src.Stride + ix*4
+					r += float64(src.Pix[i+0]) * weight
+					g += float64(src.Pix[i+1]) * weight
+					b += float64(src.Pix[i+2]) * weight
+					a += float64(src.Pix[i+3]) * weight
+				}
+
+				r = math.Min(math.Max(r/weightSum, 0.0), 255.0)
+				g = math.Min(math.Max(g/weightSum, 0.0), 255.0)
+				b = math.Min(math.Max(b/weightSum, 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)
+
+			}
+		}
+	})
+
+	return dst
+}
+
+func blurVertical(src *image.NRGBA, kernel []float64) *image.NRGBA {
+	radius := len(kernel) - 1
+	width := src.Bounds().Max.X
+	height := src.Bounds().Max.Y
+
+	dst := image.NewNRGBA(image.Rect(0, 0, width, height))
+
+	parallel(height, func(partStart, partEnd int) {
+		for y := partStart; y < partEnd; y++ {
+			start := y - radius
+			if start < 0 {
+				start = 0
+			}
+
+			end := y + radius
+			if end > height-1 {
+				end = height - 1
+			}
+
+			weightSum := 0.0
+			for iy := start; iy <= end; iy++ {
+				weightSum += kernel[absint(y-iy)]
+			}
+
+			for x := 0; x < width; x++ {
+
+				r, g, b, a := 0.0, 0.0, 0.0, 0.0
+				for iy := start; iy <= end; iy++ {
+					weight := kernel[absint(y-iy)]
+					i := iy*src.Stride + x*4
+					r += float64(src.Pix[i+0]) * weight
+					g += float64(src.Pix[i+1]) * weight
+					b += float64(src.Pix[i+2]) * weight
+					a += float64(src.Pix[i+3]) * weight
+				}
+
+				r = math.Min(math.Max(r/weightSum, 0.0), 255.0)
+				g = math.Min(math.Max(g/weightSum, 0.0), 255.0)
+				b = math.Min(math.Max(b/weightSum, 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)
+
+			}
+		}
+	})
+
+	return dst
+}
+
+// Sharpen produces a sharpened version of the image.
+// Sigma parameter must be positive and indicates how much the image will be sharpened.
+//
+// Usage example:
+//
+//		dstImage := imaging.Sharpen(srcImage, 3.5)
+//
+func Sharpen(img image.Image, sigma float64) *image.NRGBA {
+	if sigma <= 0 {
+		// sigma parameter must be positive!
+		return Clone(img)
+	}
+
+	src := toNRGBA(img)
+	blurred := Blur(img, sigma)
+
+	width := src.Bounds().Max.X
+	height := src.Bounds().Max.Y
+	dst := image.NewNRGBA(image.Rect(0, 0, width, height))
+
+	parallel(height, func(partStart, partEnd int) {
+		for y := partStart; y < partEnd; y++ {
+			for x := 0; x < width; x++ {
+				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]))
+					if val < 0 {
+						val = 0
+					} else if val > 255 {
+						val = 255
+					}
+					dst.Pix[k] = uint8(val)
+				}
+			}
+		}
+	})
+
+	return dst
+}

Godeps/_workspace/src/github.com/disintegration/imaging/helpers.go

@@ -0,0 +1,392 @@
+/*
+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 (
+	"errors"
+	"image"
+	"image/color"
+	"image/gif"
+	"image/jpeg"
+	"image/png"
+	"io"
+	"os"
+	"path/filepath"
+	"strings"
+
+	"golang.org/x/image/bmp"
+	"golang.org/x/image/tiff"
+)
+
+type Format int
+
+const (
+	JPEG Format = iota
+	PNG
+	GIF
+	TIFF
+	BMP
+)
+
+func (f Format) String() string {
+	switch f {
+	case JPEG:
+		return "JPEG"
+	case PNG:
+		return "PNG"
+	case GIF:
+		return "GIF"
+	case TIFF:
+		return "TIFF"
+	case BMP:
+		return "BMP"
+	default:
+		return "Unsupported"
+	}
+}
+
+var (
+	ErrUnsupportedFormat = errors.New("imaging: unsupported image format")
+)
+
+// Decode reads an image from r.
+func Decode(r io.Reader) (image.Image, error) {
+	img, _, err := image.Decode(r)
+	if err != nil {
+		return nil, err
+	}
+	return toNRGBA(img), nil
+}
+
+// Open loads an image from file
+func Open(filename string) (image.Image, error) {
+	file, err := os.Open(filename)
+	if err != nil {
+		return nil, err
+	}
+	defer file.Close()
+	img, err := Decode(file)
+	return img, err
+}
+
+// Encode writes the image img to w in the specified format (JPEG, PNG, GIF, TIFF or BMP).
+func Encode(w io.Writer, img image.Image, format Format) error {
+	var err error
+	switch format {
+	case JPEG:
+		var rgba *image.RGBA
+		if nrgba, ok := img.(*image.NRGBA); ok {
+			if nrgba.Opaque() {
+				rgba = &image.RGBA{
+					Pix:    nrgba.Pix,
+					Stride: nrgba.Stride,
+					Rect:   nrgba.Rect,
+				}
+			}
+		}
+		if rgba != nil {
+			err = jpeg.Encode(w, rgba, &jpeg.Options{Quality: 95})
+		} else {
+			err = jpeg.Encode(w, img, &jpeg.Options{Quality: 95})
+		}
+
+	case PNG:
+		err = png.Encode(w, img)
+	case GIF:
+		err = gif.Encode(w, img, &gif.Options{NumColors: 256})
+	case TIFF:
+		err = tiff.Encode(w, img, &tiff.Options{Compression: tiff.Deflate, Predictor: true})
+	case BMP:
+		err = bmp.Encode(w, img)
+	default:
+		err = ErrUnsupportedFormat
+	}
+	return err
+}
+
+// Save saves the image to file with the specified filename.
+// The format is determined from the filename extension: "jpg" (or "jpeg"), "png", "gif", "tif" (or "tiff") and "bmp" are supported.
+func Save(img image.Image, filename string) (err error) {
+	formats := map[string]Format{
+		".jpg":  JPEG,
+		".jpeg": JPEG,
+		".png":  PNG,
+		".tif":  TIFF,
+		".tiff": TIFF,
+		".bmp":  BMP,
+		".gif":  GIF,
+	}
+
+	ext := strings.ToLower(filepath.Ext(filename))
+	f, ok := formats[ext]
+	if !ok {
+		return ErrUnsupportedFormat
+	}
+
+	file, err := os.Create(filename)
+	if err != nil {
+		return err
+	}
+	defer file.Close()
+
+	return Encode(file, img, f)
+}
+
+// New creates a new image with the specified width and height, and fills it with the specified color.
+func New(width, height int, fillColor color.Color) *image.NRGBA {
+	if width <= 0 || height <= 0 {
+		return &image.NRGBA{}
+	}
+
+	dst := image.NewNRGBA(image.Rect(0, 0, width, height))
+	c := color.NRGBAModel.Convert(fillColor).(color.NRGBA)
+
+	if c.R == 0 && c.G == 0 && c.B == 0 && c.A == 0 {
+		return dst
+	}
+
+	cs := []uint8{c.R, c.G, c.B, c.A}
+
+	// fill the first row
+	for x := 0; x < width; x++ {
+		copy(dst.Pix[x*4:(x+1)*4], cs)
+	}
+	// copy the first row to other rows
+	for y := 1; y < height; y++ {
+		copy(dst.Pix[y*dst.Stride:y*dst.Stride+width*4], dst.Pix[0:width*4])
+	}
+
+	return dst
+}
+
+// Clone returns a copy of the given image.
+func Clone(img image.Image) *image.NRGBA {
+	srcBounds := img.Bounds()
+	srcMinX := srcBounds.Min.X
+	srcMinY := srcBounds.Min.Y
+
+	dstBounds := srcBounds.Sub(srcBounds.Min)
+	dstW := dstBounds.Dx()
+	dstH := dstBounds.Dy()
+	dst := image.NewNRGBA(dstBounds)
+
+	switch src := img.(type) {
+
+	case *image.NRGBA:
+		rowSize := srcBounds.Dx() * 4
+		parallel(dstH, func(partStart, partEnd int) {
+			for dstY := partStart; dstY < partEnd; dstY++ {
+				di := dst.PixOffset(0, dstY)
+				si := src.PixOffset(srcMinX, srcMinY+dstY)
+				copy(dst.Pix[di:di+rowSize], src.Pix[si:si+rowSize])
+			}
+		})
+
+	case *image.NRGBA64:
+		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++ {
+
+					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
+
+				}
+			}
+		})
+
+	case *image.RGBA:
+		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++ {
+
+					a := src.Pix[si+3]
+					dst.Pix[di+3] = a
+					switch a {
+					case 0:
+						dst.Pix[di+0] = 0
+						dst.Pix[di+1] = 0
+						dst.Pix[di+2] = 0
+					case 0xff:
+						dst.Pix[di+0] = src.Pix[si+0]
+						dst.Pix[di+1] = src.Pix[si+1]
+						dst.Pix[di+2] = src.Pix[si+2]
+					default:
+						dst.Pix[di+0] = uint8(uint16(src.Pix[si+0]) * 0xff / uint16(a))
+						dst.Pix[di+1] = uint8(uint16(src.Pix[si+1]) * 0xff / uint16(a))
+						dst.Pix[di+2] = uint8(uint16(src.Pix[si+2]) * 0xff / uint16(a))
+					}
+
+					di += 4
+					si += 4
+
+				}
+			}
+		})
+
+	case *image.RGBA64:
+		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++ {
+
+					a := src.Pix[si+6]
+					dst.Pix[di+3] = a
+					switch a {
+					case 0:
+						dst.Pix[di+0] = 0
+						dst.Pix[di+1] = 0
+						dst.Pix[di+2] = 0
+					case 0xff:
+						dst.Pix[di+0] = src.Pix[si+0]
+						dst.Pix[di+1] = src.Pix[si+2]
+						dst.Pix[di+2] = src.Pix[si+4]
+					default:
+						dst.Pix[di+0] = uint8(uint16(src.Pix[si+0]) * 0xff / uint16(a))
+						dst.Pix[di+1] = uint8(uint16(src.Pix[si+2]) * 0xff / uint16(a))
+						dst.Pix[di+2] = uint8(uint16(src.Pix[si+4]) * 0xff / uint16(a))
+					}
+
+					di += 4
+					si += 8
+
+				}
+			}
+		})
+
+	case *image.Gray:
+		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 := 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
+
+				}
+			}
+		})
+
+	case *image.Gray16:
+		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 := 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
+
+				}
+			}
+		})
+
+	case *image.YCbCr:
+		parallel(dstH, func(partStart, partEnd int) {
+			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)
+					sic := src.COffset(srcX, srcY)
+					r, g, b := color.YCbCrToRGB(src.Y[siy], src.Cb[sic], src.Cr[sic])
+					dst.Pix[di+0] = r
+					dst.Pix[di+1] = g
+					dst.Pix[di+2] = b
+					dst.Pix[di+3] = 0xff
+
+					di += 4
+
+				}
+			}
+		})
+
+	case *image.Paletted:
+		plen := len(src.Palette)
+		pnew := make([]color.NRGBA, plen)
+		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
+
+				}
+			}
+		})
+
+	default:
+		parallel(dstH, func(partStart, partEnd int) {
+			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
+
+				}
+			}
+		})
+
+	}
+
+	return dst
+}
+
+// This function used internally to convert any image type to NRGBA if needed.
+func toNRGBA(img image.Image) *image.NRGBA {
+	srcBounds := img.Bounds()
+	if srcBounds.Min.X == 0 && srcBounds.Min.Y == 0 {
+		if src0, ok := img.(*image.NRGBA); ok {
+			return src0
+		}
+	}
+	return Clone(img)
+}

Godeps/_workspace/src/github.com/disintegration/imaging/resize.go

@@ -0,0 +1,564 @@
+package imaging
+
+import (
+	"image"
+	"math"
+)
+
+type iwpair struct {
+	i int
+	w int32
+}
+
+type pweights struct {
+	iwpairs []iwpair
+	wsum    int32
+}
+
+func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights {
+	du := float64(srcSize) / float64(dstSize)
+	scale := du
+	if scale < 1.0 {
+		scale = 1.0
+	}
+	ru := math.Ceil(scale * filter.Support)
+
+	out := make([]pweights, dstSize)
+
+	for v := 0; v < dstSize; v++ {
+		fu := (float64(v)+0.5)*du - 0.5
+
+		startu := int(math.Ceil(fu - ru))
+		if startu < 0 {
+			startu = 0
+		}
+		endu := int(math.Floor(fu + ru))
+		if endu > srcSize-1 {
+			endu = srcSize - 1
+		}
+
+		wsum := int32(0)
+		for u := startu; u <= endu; u++ {
+			w := int32(0xff * filter.Kernel((float64(u)-fu)/scale))
+			if w != 0 {
+				wsum += w
+				out[v].iwpairs = append(out[v].iwpairs, iwpair{u, w})
+			}
+		}
+		out[v].wsum = wsum
+	}
+
+	return out
+}
+
+// Resize resizes the image to the specified width and height using the specified resampling
+// filter and returns the transformed image. If one of width or height is 0, the image aspect
+// ratio is preserved.
+//
+// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali,
+// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.
+//
+// Usage example:
+//
+//		dstImage := imaging.Resize(srcImage, 800, 600, imaging.Lanczos)
+//
+func Resize(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA {
+	dstW, dstH := width, height
+
+	if dstW < 0 || dstH < 0 {
+		return &image.NRGBA{}
+	}
+	if dstW == 0 && dstH == 0 {
+		return &image.NRGBA{}
+	}
+
+	src := toNRGBA(img)
+
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+
+	if srcW <= 0 || srcH <= 0 {
+		return &image.NRGBA{}
+	}
+
+	// if new width or height is 0 then preserve aspect ratio, minimum 1px
+	if dstW == 0 {
+		tmpW := float64(dstH) * float64(srcW) / float64(srcH)
+		dstW = int(math.Max(1.0, math.Floor(tmpW+0.5)))
+	}
+	if dstH == 0 {
+		tmpH := float64(dstW) * float64(srcH) / float64(srcW)
+		dstH = int(math.Max(1.0, math.Floor(tmpH+0.5)))
+	}
+
+	var dst *image.NRGBA
+
+	if filter.Support <= 0.0 {
+		// nearest-neighbor special case
+		dst = resizeNearest(src, dstW, dstH)
+
+	} else {
+		// two-pass resize
+		if srcW != dstW {
+			dst = resizeHorizontal(src, dstW, filter)
+		} else {
+			dst = src
+		}
+
+		if srcH != dstH {
+			dst = resizeVertical(dst, dstH, filter)
+		}
+	}
+
+	return dst
+}
+
+func resizeHorizontal(src *image.NRGBA, width int, filter ResampleFilter) *image.NRGBA {
+	srcBounds := src.Bounds()
+	srcW := srcBounds.Max.X
+	srcH := srcBounds.Max.Y
+
+	dstW := width
+	dstH := srcH
+
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	weights := precomputeWeights(dstW, srcW, filter)
+
+	parallel(dstH, func(partStart, partEnd int) {
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				var c [4]int32
+				for _, iw := range weights[dstX].iwpairs {
+					i := dstY*src.Stride + iw.i*4
+					c[0] += int32(src.Pix[i+0]) * iw.w
+					c[1] += int32(src.Pix[i+1]) * iw.w
+					c[2] += int32(src.Pix[i+2]) * iw.w
+					c[3] += int32(src.Pix[i+3]) * iw.w
+				}
+				j := dstY*dst.Stride + dstX*4
+				sum := weights[dstX].wsum
+				dst.Pix[j+0] = clampint32(int32(float32(c[0])/float32(sum) + 0.5))
+				dst.Pix[j+1] = clampint32(int32(float32(c[1])/float32(sum) + 0.5))
+				dst.Pix[j+2] = clampint32(int32(float32(c[2])/float32(sum) + 0.5))
+				dst.Pix[j+3] = clampint32(int32(float32(c[3])/float32(sum) + 0.5))
+			}
+		}
+	})
+
+	return dst
+}
+
+func resizeVertical(src *image.NRGBA, height int, filter ResampleFilter) *image.NRGBA {
+	srcBounds := src.Bounds()
+	srcW := srcBounds.Max.X
+	srcH := srcBounds.Max.Y
+
+	dstW := srcW
+	dstH := height
+
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	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]int32
+				for _, iw := range weights[dstY].iwpairs {
+					i := iw.i*src.Stride + dstX*4
+					c[0] += int32(src.Pix[i+0]) * iw.w
+					c[1] += int32(src.Pix[i+1]) * iw.w
+					c[2] += int32(src.Pix[i+2]) * iw.w
+					c[3] += int32(src.Pix[i+3]) * iw.w
+				}
+				j := dstY*dst.Stride + dstX*4
+				sum := weights[dstY].wsum
+				dst.Pix[j+0] = clampint32(int32(float32(c[0])/float32(sum) + 0.5))
+				dst.Pix[j+1] = clampint32(int32(float32(c[1])/float32(sum) + 0.5))
+				dst.Pix[j+2] = clampint32(int32(float32(c[2])/float32(sum) + 0.5))
+				dst.Pix[j+3] = clampint32(int32(float32(c[3])/float32(sum) + 0.5))
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// fast nearest-neighbor resize, no filtering
+func resizeNearest(src *image.NRGBA, width, height int) *image.NRGBA {
+	dstW, dstH := width, height
+
+	srcBounds := src.Bounds()
+	srcW := srcBounds.Max.X
+	srcH := srcBounds.Max.Y
+
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	dx := float64(srcW) / float64(dstW)
+	dy := float64(srcH) / float64(dstH)
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			fy := (float64(dstY)+0.5)*dy - 0.5
+
+			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)))
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// Fit scales down the image using the specified resample filter to fit the specified
+// maximum width and height and returns the transformed image.
+//
+// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali,
+// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.
+//
+// Usage example:
+//
+//		dstImage := imaging.Fit(srcImage, 800, 600, imaging.Lanczos)
+//
+func Fit(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA {
+	maxW, maxH := width, height
+
+	if maxW <= 0 || maxH <= 0 {
+		return &image.NRGBA{}
+	}
+
+	srcBounds := img.Bounds()
+	srcW := srcBounds.Dx()
+	srcH := srcBounds.Dy()
+
+	if srcW <= 0 || srcH <= 0 {
+		return &image.NRGBA{}
+	}
+
+	if srcW <= maxW && srcH <= maxH {
+		return Clone(img)
+	}
+
+	srcAspectRatio := float64(srcW) / float64(srcH)
+	maxAspectRatio := float64(maxW) / float64(maxH)
+
+	var newW, newH int
+	if srcAspectRatio > maxAspectRatio {
+		newW = maxW
+		newH = int(float64(newW) / srcAspectRatio)
+	} else {
+		newH = maxH
+		newW = int(float64(newH) * srcAspectRatio)
+	}
+
+	return Resize(img, newW, newH, filter)
+}
+
+// Thumbnail scales the image up or down using the specified resample filter, crops it
+// to the specified width and hight and returns the transformed image.
+//
+// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali,
+// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.
+//
+// Usage example:
+//
+//		dstImage := imaging.Thumbnail(srcImage, 100, 100, imaging.Lanczos)
+//
+func Thumbnail(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA {
+	thumbW, thumbH := width, height
+
+	if thumbW <= 0 || thumbH <= 0 {
+		return &image.NRGBA{}
+	}
+
+	srcBounds := img.Bounds()
+	srcW := srcBounds.Dx()
+	srcH := srcBounds.Dy()
+
+	if srcW <= 0 || srcH <= 0 {
+		return &image.NRGBA{}
+	}
+
+	srcAspectRatio := float64(srcW) / float64(srcH)
+	thumbAspectRatio := float64(thumbW) / float64(thumbH)
+
+	var tmp image.Image
+	if srcAspectRatio > thumbAspectRatio {
+		tmp = Resize(img, 0, thumbH, filter)
+	} else {
+		tmp = Resize(img, thumbW, 0, filter)
+	}
+
+	return CropCenter(tmp, thumbW, thumbH)
+}
+
+// Resample filter struct. It can be used to make custom filters.
+//
+// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali,
+// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.
+//
+//	General filter recommendations:
+//
+//	- Lanczos
+//		Probably the best resampling filter for photographic images yielding sharp results,
+//		but it's slower than cubic filters (see below).
+//
+//	- CatmullRom
+//		A sharp cubic filter. It's a good filter for both upscaling and downscaling if sharp results are needed.
+//
+//	- MitchellNetravali
+//		A high quality cubic filter that produces smoother results with less ringing than CatmullRom.
+//
+//	- BSpline
+//		A good filter if a very smooth output is needed.
+//
+//	- Linear
+//		Bilinear interpolation filter, produces reasonably good, smooth output. It's faster than cubic filters.
+//
+//	- Box
+//		Simple and fast resampling filter appropriate for downscaling.
+//		When upscaling it's similar to NearestNeighbor.
+//
+//	- NearestNeighbor
+//		Fastest resample filter, no antialiasing at all. Rarely used.
+//
+type ResampleFilter struct {
+	Support float64
+	Kernel  func(float64) float64
+}
+
+// Nearest-neighbor filter, no anti-aliasing.
+var NearestNeighbor ResampleFilter
+
+// Box filter (averaging pixels).
+var Box ResampleFilter
+
+// Linear filter.
+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).
+var MitchellNetravali ResampleFilter
+
+// 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).
+var BSpline ResampleFilter
+
+// Gaussian Blurring Filter.
+var Gaussian ResampleFilter
+
+// Bartlett-windowed sinc filter (3 lobes).
+var Bartlett ResampleFilter
+
+// Lanczos filter (3 lobes).
+var Lanczos ResampleFilter
+
+// Hann-windowed sinc filter (3 lobes).
+var Hann ResampleFilter
+
+// Hamming-windowed sinc filter (3 lobes).
+var Hamming ResampleFilter
+
+// Blackman-windowed sinc filter (3 lobes).
+var Blackman ResampleFilter
+
+// Welch-windowed sinc filter (parabolic window, 3 lobes).
+var Welch ResampleFilter
+
+// Cosine-windowed sinc filter (3 lobes).
+var Cosine ResampleFilter
+
+func bcspline(x, b, c float64) float64 {
+	x = math.Abs(x)
+	if x < 1.0 {
+		return ((12-9*b-6*c)*x*x*x + (-18+12*b+6*c)*x*x + (6 - 2*b)) / 6
+	}
+	if x < 2.0 {
+		return ((-b-6*c)*x*x*x + (6*b+30*c)*x*x + (-12*b-48*c)*x + (8*b + 24*c)) / 6
+	}
+	return 0
+}
+
+func sinc(x float64) float64 {
+	if x == 0 {
+		return 1
+	}
+	return math.Sin(math.Pi*x) / (math.Pi * x)
+}
+
+func init() {
+	NearestNeighbor = ResampleFilter{
+		Support: 0.0, // special case - not applying the filter
+	}
+
+	Box = ResampleFilter{
+		Support: 0.5,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x <= 0.5 {
+				return 1.0
+			}
+			return 0
+		},
+	}
+
+	Linear = ResampleFilter{
+		Support: 1.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 1.0 {
+				return 1.0 - x
+			}
+			return 0
+		},
+	}
+
+	Hermite = ResampleFilter{
+		Support: 1.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 1.0 {
+				return bcspline(x, 0.0, 0.0)
+			}
+			return 0
+		},
+	}
+
+	MitchellNetravali = ResampleFilter{
+		Support: 2.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 2.0 {
+				return bcspline(x, 1.0/3.0, 1.0/3.0)
+			}
+			return 0
+		},
+	}
+
+	CatmullRom = ResampleFilter{
+		Support: 2.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 2.0 {
+				return bcspline(x, 0.0, 0.5)
+			}
+			return 0
+		},
+	}
+
+	BSpline = ResampleFilter{
+		Support: 2.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 2.0 {
+				return bcspline(x, 1.0, 0.0)
+			}
+			return 0
+		},
+	}
+
+	Gaussian = ResampleFilter{
+		Support: 2.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 2.0 {
+				return math.Exp(-2 * x * x)
+			}
+			return 0
+		},
+	}
+
+	Bartlett = ResampleFilter{
+		Support: 3.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 3.0 {
+				return sinc(x) * (3.0 - x) / 3.0
+			}
+			return 0
+		},
+	}
+
+	Lanczos = ResampleFilter{
+		Support: 3.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 3.0 {
+				return sinc(x) * sinc(x/3.0)
+			}
+			return 0
+		},
+	}
+
+	Hann = ResampleFilter{
+		Support: 3.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 3.0 {
+				return sinc(x) * (0.5 + 0.5*math.Cos(math.Pi*x/3.0))
+			}
+			return 0
+		},
+	}
+
+	Hamming = ResampleFilter{
+		Support: 3.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 3.0 {
+				return sinc(x) * (0.54 + 0.46*math.Cos(math.Pi*x/3.0))
+			}
+			return 0
+		},
+	}
+
+	Blackman = ResampleFilter{
+		Support: 3.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 3.0 {
+				return sinc(x) * (0.42 - 0.5*math.Cos(math.Pi*x/3.0+math.Pi) + 0.08*math.Cos(2.0*math.Pi*x/3.0))
+			}
+			return 0
+		},
+	}
+
+	Welch = ResampleFilter{
+		Support: 3.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 3.0 {
+				return sinc(x) * (1.0 - (x * x / 9.0))
+			}
+			return 0
+		},
+	}
+
+	Cosine = ResampleFilter{
+		Support: 3.0,
+		Kernel: func(x float64) float64 {
+			x = math.Abs(x)
+			if x < 3.0 {
+				return sinc(x) * math.Cos((math.Pi/2.0)*(x/3.0))
+			}
+			return 0
+		},
+	}
+}

Godeps/_workspace/src/github.com/disintegration/imaging/tools.go

@@ -0,0 +1,182 @@
+package imaging
+
+import (
+	"image"
+	"math"
+)
+
+// Anchor is the anchor point for image alignment.
+type Anchor int
+
+const (
+	Center Anchor = iota
+	TopLeft
+	Top
+	TopRight
+	Left
+	Right
+	BottomLeft
+	Bottom
+	BottomRight
+)
+
+func anchorPt(b image.Rectangle, w, h int, anchor Anchor) image.Point {
+	var x, y int
+	switch anchor {
+	case TopLeft:
+		x = b.Min.X
+		y = b.Min.Y
+	case Top:
+		x = b.Min.X + (b.Dx()-w)/2
+		y = b.Min.Y
+	case TopRight:
+		x = b.Max.X - w
+		y = b.Min.Y
+	case Left:
+		x = b.Min.X
+		y = b.Min.Y + (b.Dy()-h)/2
+	case Right:
+		x = b.Max.X - w
+		y = b.Min.Y + (b.Dy()-h)/2
+	case BottomLeft:
+		x = b.Min.X
+		y = b.Max.Y - h
+	case Bottom:
+		x = b.Min.X + (b.Dx()-w)/2
+		y = b.Max.Y - h
+	case BottomRight:
+		x = b.Max.X - w
+		y = b.Max.Y - h
+	default:
+		x = b.Min.X + (b.Dx()-w)/2
+		y = b.Min.Y + (b.Dy()-h)/2
+	}
+	return image.Pt(x, y)
+}
+
+// Crop cuts out a rectangular region with the specified bounds
+// from the image and returns the cropped image.
+func Crop(img image.Image, rect image.Rectangle) *image.NRGBA {
+	src := toNRGBA(img)
+	srcRect := rect.Sub(img.Bounds().Min)
+	sub := src.SubImage(srcRect)
+	return Clone(sub) // New image Bounds().Min point will be (0, 0)
+}
+
+// CropAnchor cuts out a rectangular region with the specified size
+// from the image using the specified anchor point and returns the cropped image.
+func CropAnchor(img image.Image, width, height int, anchor Anchor) *image.NRGBA {
+	srcBounds := img.Bounds()
+	pt := anchorPt(srcBounds, width, height, anchor)
+	r := image.Rect(0, 0, width, height).Add(pt)
+	b := srcBounds.Intersect(r)
+	return Crop(img, b)
+}
+
+// CropCenter cuts out a rectangular region with the specified size
+// from the center of the image and returns the cropped image.
+func CropCenter(img image.Image, width, height int) *image.NRGBA {
+	return CropAnchor(img, width, height, Center)
+}
+
+// Paste pastes the img image to the background image at the specified position and returns the combined image.
+func Paste(background, img image.Image, pos image.Point) *image.NRGBA {
+	src := toNRGBA(img)
+	dst := Clone(background)                    // cloned image bounds start at (0, 0)
+	startPt := pos.Sub(background.Bounds().Min) // so we should translate start point
+	endPt := startPt.Add(src.Bounds().Size())
+	pasteBounds := image.Rectangle{startPt, endPt}
+
+	if dst.Bounds().Overlaps(pasteBounds) {
+		intersectBounds := dst.Bounds().Intersect(pasteBounds)
+
+		rowSize := intersectBounds.Dx() * 4
+		numRows := intersectBounds.Dy()
+
+		srcStartX := intersectBounds.Min.X - pasteBounds.Min.X
+		srcStartY := intersectBounds.Min.Y - pasteBounds.Min.Y
+
+		i0 := dst.PixOffset(intersectBounds.Min.X, intersectBounds.Min.Y)
+		j0 := src.PixOffset(srcStartX, srcStartY)
+
+		di := dst.Stride
+		dj := src.Stride
+
+		for row := 0; row < numRows; row++ {
+			copy(dst.Pix[i0:i0+rowSize], src.Pix[j0:j0+rowSize])
+			i0 += di
+			j0 += dj
+		}
+	}
+
+	return dst
+}
+
+// PasteCenter pastes the img image to the center of the background image and returns the combined image.
+func PasteCenter(background, img image.Image) *image.NRGBA {
+	bgBounds := background.Bounds()
+	bgW := bgBounds.Dx()
+	bgH := bgBounds.Dy()
+	bgMinX := bgBounds.Min.X
+	bgMinY := bgBounds.Min.Y
+
+	centerX := bgMinX + bgW/2
+	centerY := bgMinY + bgH/2
+
+	x0 := centerX - img.Bounds().Dx()/2
+	y0 := centerY - img.Bounds().Dy()/2
+
+	return Paste(background, img, image.Pt(x0, y0))
+}
+
+// Overlay draws the img image over the background image at given position
+// and returns the combined image. Opacity parameter is the opacity of the img
+// image layer, used to compose the images, it must be from 0.0 to 1.0.
+//
+// Usage examples:
+//
+//		// draw the sprite over the background at position (50, 50)
+//		dstImage := imaging.Overlay(backgroundImage, spriteImage, image.Pt(50, 50), 1.0)
+//
+//		// blend two opaque images of the same size
+//		dstImage := imaging.Overlay(imageOne, imageTwo, image.Pt(0, 0), 0.5)
+//
+func Overlay(background, img image.Image, pos image.Point, opacity float64) *image.NRGBA {
+	opacity = math.Min(math.Max(opacity, 0.0), 1.0) // check: 0.0 <= opacity <= 1.0
+
+	src := toNRGBA(img)
+	dst := Clone(background)                    // cloned image bounds start at (0, 0)
+	startPt := pos.Sub(background.Bounds().Min) // so we should translate start point
+	endPt := startPt.Add(src.Bounds().Size())
+	pasteBounds := image.Rectangle{startPt, endPt}
+
+	if dst.Bounds().Overlaps(pasteBounds) {
+		intersectBounds := dst.Bounds().Intersect(pasteBounds)
+
+		for y := intersectBounds.Min.Y; y < intersectBounds.Max.Y; y++ {
+			for x := intersectBounds.Min.X; x < intersectBounds.Max.X; x++ {
+				i := y*dst.Stride + x*4
+
+				srcX := x - pasteBounds.Min.X
+				srcY := y - pasteBounds.Min.Y
+				j := srcY*src.Stride + srcX*4
+
+				a1 := float64(dst.Pix[i+3])
+				a2 := float64(src.Pix[j+3])
+
+				coef2 := opacity * a2 / 255.0
+				coef1 := (1 - coef2) * a1 / 255.0
+				coefSum := coef1 + coef2
+				coef1 /= coefSum
+				coef2 /= coefSum
+
+				dst.Pix[i+0] = uint8(float64(dst.Pix[i+0])*coef1 + float64(src.Pix[j+0])*coef2)
+				dst.Pix[i+1] = uint8(float64(dst.Pix[i+1])*coef1 + float64(src.Pix[j+1])*coef2)
+				dst.Pix[i+2] = uint8(float64(dst.Pix[i+2])*coef1 + float64(src.Pix[j+2])*coef2)
+				dst.Pix[i+3] = uint8(math.Min(a1+a2*opacity*(255.0-a1)/255.0, 255.0))
+			}
+		}
+	}
+
+	return dst
+}

Godeps/_workspace/src/github.com/disintegration/imaging/transform.go

@@ -0,0 +1,201 @@
+package imaging
+
+import (
+	"image"
+)
+
+// Rotate90 rotates the image 90 degrees counterclockwise and returns the transformed image.
+func Rotate90(img image.Image) *image.NRGBA {
+	src := toNRGBA(img)
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+	dstW := srcH
+	dstH := srcW
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				srcX := dstH - dstY - 1
+				srcY := dstX
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// Rotate180 rotates the image 180 degrees counterclockwise and returns the transformed image.
+func Rotate180(img image.Image) *image.NRGBA {
+	src := toNRGBA(img)
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+	dstW := srcW
+	dstH := srcH
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				srcX := dstW - dstX - 1
+				srcY := dstH - dstY - 1
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// Rotate270 rotates the image 270 degrees counterclockwise and returns the transformed image.
+func Rotate270(img image.Image) *image.NRGBA {
+	src := toNRGBA(img)
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+	dstW := srcH
+	dstH := srcW
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				srcX := dstY
+				srcY := dstW - dstX - 1
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// FlipH flips the image horizontally (from left to right) and returns the transformed image.
+func FlipH(img image.Image) *image.NRGBA {
+	src := toNRGBA(img)
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+	dstW := srcW
+	dstH := srcH
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				srcX := dstW - dstX - 1
+				srcY := dstY
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// FlipV flips the image vertically (from top to bottom) and returns the transformed image.
+func FlipV(img image.Image) *image.NRGBA {
+	src := toNRGBA(img)
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+	dstW := srcW
+	dstH := srcH
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				srcX := dstX
+				srcY := dstH - dstY - 1
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// Transpose flips the image horizontally and rotates 90 degrees counter-clockwise.
+func Transpose(img image.Image) *image.NRGBA {
+	src := toNRGBA(img)
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+	dstW := srcH
+	dstH := srcW
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				srcX := dstY
+				srcY := dstX
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}
+
+// Transverse flips the image vertically and rotates 90 degrees counter-clockwise.
+func Transverse(img image.Image) *image.NRGBA {
+	src := toNRGBA(img)
+	srcW := src.Bounds().Max.X
+	srcH := src.Bounds().Max.Y
+	dstW := srcH
+	dstH := srcW
+	dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH))
+
+	parallel(dstH, func(partStart, partEnd int) {
+
+		for dstY := partStart; dstY < partEnd; dstY++ {
+			for dstX := 0; dstX < dstW; dstX++ {
+				srcX := dstH - dstY - 1
+				srcY := dstW - dstX - 1
+
+				srcOff := srcY*src.Stride + srcX*4
+				dstOff := dstY*dst.Stride + dstX*4
+
+				copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+			}
+		}
+
+	})
+
+	return dst
+}

Godeps/_workspace/src/github.com/disintegration/imaging/utils.go

@@ -0,0 +1,77 @@
+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
+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
+			}
+		}
+	}
+
+	if numGoroutines == 1 {
+		fn(0, dataSize)
+	} else {
+		var wg sync.WaitGroup
+		wg.Add(numGoroutines)
+		idx := uint64(0)
+
+		for p := 0; p < numGoroutines; p++ {
+			go func() {
+				defer wg.Done()
+				for {
+					partStart := int(atomic.AddUint64(&idx, uint64(partSize))) - partSize
+					if partStart >= dataSize {
+						break
+					}
+					partEnd := partStart + partSize
+					if partEnd > dataSize {
+						partEnd = dataSize
+					}
+					fn(partStart, partEnd)
+				}
+			}()
+		}
+
+		wg.Wait()
+	}
+}
+
+func absint(i int) int {
+	if i < 0 {
+		return -i
+	}
+	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 {
+		return 255
+	}
+	return uint8(v)
+}