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vendor: add github.com/muesli/smartcrop and deps

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21
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The MIT License (MIT)
Copyright (c) 2014 Christian Muehlhaeuser
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.

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vendor/github.com/muesli/smartcrop/README.md generated vendored Normal file
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smartcrop
=========
smartcrop finds good image crops for arbitrary sizes. It is a pure Go implementation, based on Jonas Wagner's [smartcrop.js](https://github.com/jwagner/smartcrop.js)
![Example](./examples/gopher.jpg)
Image: [https://www.flickr.com/photos/usfwspacific/8182486789](https://www.flickr.com/photos/usfwspacific/8182486789) CC BY U.S. Fish & Wildlife
![Example](./examples/goodtimes.jpg)
Image: [https://www.flickr.com/photos/endogamia/5682480447](https://www.flickr.com/photos/endogamia/5682480447) by N. Feans
## Installation
Make sure you have a working Go environment. See the [install instructions](http://golang.org/doc/install.html).
To install smartcrop, simply run:
go get github.com/muesli/smartcrop
To compile it from source:
cd $GOPATH/src/github.com/muesli/smartcrop
go get -u -v
go build && go test -v
## Example
```go
package main
import (
"fmt"
"image"
_ "image/png"
"os"
"github.com/muesli/smartcrop"
)
func main() {
f, _ := os.Open("image.png")
img, _, _ := image.Decode(f)
analyzer := smartcrop.NewAnalyzer()
topCrop, _ := analyzer.FindBestCrop(img, 250, 250)
// The crop will have the requested aspect ratio, but you need to copy/scale it yourself
fmt.Printf("Top crop: %+v\n", topCrop)
type SubImager interface {
SubImage(r image.Rectangle) image.Image
}
croppedimg := img.(SubImager).SubImage(topCrop)
...
}
```
Also see the test cases in smartcrop_test.go for further working examples.
## Sample Data
You can find a bunch of test images for the algorithm [here](https://github.com/muesli/smartcrop-samples).
## Development
API docs can be found [here](http://godoc.org/github.com/muesli/smartcrop).
Join us on IRC: irc.freenode.net/#smartcrop
[![Build Status](https://travis-ci.org/muesli/smartcrop.svg?branch=master)](https://travis-ci.org/muesli/smartcrop)
[![Coverage Status](https://coveralls.io/repos/github/muesli/smartcrop/badge.svg?branch=master)](https://coveralls.io/github/muesli/smartcrop?branch=master)
[![Go ReportCard](http://goreportcard.com/badge/muesli/smartcrop)](http://goreportcard.com/report/muesli/smartcrop)

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/*
* Copyright (c) 2014 Christian Muehlhaeuser
*
* 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.
*
* Authors:
* Christian Muehlhaeuser <muesli@gmail.com>
* Michael Wendland <michael@michiwend.com>
*/
/*
Package smartcrop implements a content aware image cropping library based on
Jonas Wagner's smartcrop.js https://github.com/jwagner/smartcrop.js
*/
package smartcrop
import (
"errors"
"image"
"image/color"
"image/jpeg"
"image/png"
"os"
"path/filepath"
)
func debugOutput(debug bool, img *image.RGBA, debugType string) {
if debug {
writeImage("png", img, "./smartcrop_"+debugType+".png")
}
}
func writeImage(imgtype string, img image.Image, name string) error {
if err := os.MkdirAll(filepath.Dir(name), 0755); err != nil {
panic(err)
}
switch imgtype {
case "png":
return writeImageToPng(img, name)
case "jpeg":
return writeImageToJpeg(img, name)
}
return errors.New("Unknown image type")
}
func writeImageToJpeg(img image.Image, name string) error {
fso, err := os.Create(name)
if err != nil {
return err
}
defer fso.Close()
return jpeg.Encode(fso, img, &jpeg.Options{Quality: 100})
}
func writeImageToPng(img image.Image, name string) error {
fso, err := os.Create(name)
if err != nil {
return err
}
defer fso.Close()
return png.Encode(fso, img)
}
func drawDebugCrop(topCrop Crop, o *image.RGBA) {
width := o.Bounds().Dx()
height := o.Bounds().Dy()
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
r, g, b, _ := o.At(x, y).RGBA()
r8 := float64(r >> 8)
g8 := float64(g >> 8)
b8 := uint8(b >> 8)
imp := importance(topCrop, x, y)
if imp > 0 {
g8 += imp * 32
} else if imp < 0 {
r8 += imp * -64
}
nc := color.RGBA{uint8(bounds(r8)), uint8(bounds(g8)), b8, 255}
o.SetRGBA(x, y, nc)
}
}
}

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/*
* Copyright (c) 2014-2017 Christian Muehlhaeuser
*
* 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.
*
* Authors:
* Christian Muehlhaeuser <muesli@gmail.com>
* Michael Wendland <michael@michiwend.com>
*/
/*
Package smartcrop implements a content aware image cropping library based on
Jonas Wagner's smartcrop.js https://github.com/jwagner/smartcrop.js
*/
package smartcrop
import (
"errors"
"image"
"image/color"
"io/ioutil"
"log"
"math"
"time"
"golang.org/x/image/draw"
"github.com/nfnt/resize"
)
var (
// ErrInvalidDimensions gets returned when the supplied dimensions are invalid
ErrInvalidDimensions = errors.New("Expect either a height or width")
skinColor = [3]float64{0.78, 0.57, 0.44}
)
const (
detailWeight = 0.2
skinBias = 0.01
skinBrightnessMin = 0.2
skinBrightnessMax = 1.0
skinThreshold = 0.8
skinWeight = 1.8
saturationBrightnessMin = 0.05
saturationBrightnessMax = 0.9
saturationThreshold = 0.4
saturationBias = 0.2
saturationWeight = 0.3
scoreDownSample = 8 // step * minscale rounded down to the next power of two should be good
step = 8
scaleStep = 0.1
minScale = 0.9
maxScale = 1.0
edgeRadius = 0.4
edgeWeight = -20.0
outsideImportance = -0.5
ruleOfThirds = true
prescale = true
prescaleMin = 400.00
)
// Analyzer interface analyzes its struct and returns the best possible crop with the given
// width and height returns an error if invalid
type Analyzer interface {
FindBestCrop(img image.Image, width, height int) (image.Rectangle, error)
}
// Score contains values that classify matches
type Score struct {
Detail float64
Saturation float64
Skin float64
}
// Crop contains results
type Crop struct {
image.Rectangle
Score Score
}
// CropSettings contains options to change cropping behaviour
type CropSettings struct {
InterpolationType resize.InterpolationFunction
DebugMode bool
Log *log.Logger
}
type smartcropAnalyzer struct {
cropSettings CropSettings
}
// NewAnalyzer returns a new analyzer with default settings
func NewAnalyzer() Analyzer {
cropSettings := CropSettings{
InterpolationType: resize.Bicubic,
DebugMode: false,
}
return NewAnalyzerWithCropSettings(cropSettings)
}
// NewAnalyzerWithCropSettings returns a new analyzer with the given settings
func NewAnalyzerWithCropSettings(cropSettings CropSettings) Analyzer {
if cropSettings.Log == nil {
cropSettings.Log = log.New(ioutil.Discard, "", 0)
}
return &smartcropAnalyzer{cropSettings: cropSettings}
}
func (o smartcropAnalyzer) FindBestCrop(img image.Image, width, height int) (image.Rectangle, error) {
if width == 0 && height == 0 {
return image.Rectangle{}, ErrInvalidDimensions
}
// resize image for faster processing
scale := math.Min(float64(img.Bounds().Dx())/float64(width), float64(img.Bounds().Dy())/float64(height))
var lowimg *image.RGBA
var prescalefactor = 1.0
if prescale {
// if f := 1.0 / scale / minScale; f < 1.0 {
// prescalefactor = f
// }
if f := prescaleMin / math.Min(float64(img.Bounds().Dx()), float64(img.Bounds().Dy())); f < 1.0 {
prescalefactor = f
}
o.cropSettings.Log.Println(prescalefactor)
smallimg := resize.Resize(
uint(float64(img.Bounds().Dx())*prescalefactor),
0,
img,
o.cropSettings.InterpolationType)
lowimg = toRGBA(smallimg)
} else {
lowimg = toRGBA(img)
}
if o.cropSettings.DebugMode {
writeImage("png", lowimg, "./smartcrop_prescale.png")
}
cropWidth, cropHeight := chop(float64(width)*scale*prescalefactor), chop(float64(height)*scale*prescalefactor)
realMinScale := math.Min(maxScale, math.Max(1.0/scale, minScale))
o.cropSettings.Log.Printf("original resolution: %dx%d\n", img.Bounds().Dx(), img.Bounds().Dy())
o.cropSettings.Log.Printf("scale: %f, cropw: %f, croph: %f, minscale: %f\n", scale, cropWidth, cropHeight, realMinScale)
topCrop, err := analyse(o.cropSettings, lowimg, cropWidth, cropHeight, realMinScale)
if err != nil {
return topCrop, err
}
if prescale == true {
topCrop.Min.X = int(chop(float64(topCrop.Min.X) / prescalefactor))
topCrop.Min.Y = int(chop(float64(topCrop.Min.Y) / prescalefactor))
topCrop.Max.X = int(chop(float64(topCrop.Max.X) / prescalefactor))
topCrop.Max.Y = int(chop(float64(topCrop.Max.Y) / prescalefactor))
}
return topCrop.Canon(), nil
}
func (c Crop) totalScore() float64 {
return (c.Score.Detail*detailWeight + c.Score.Skin*skinWeight + c.Score.Saturation*saturationWeight) / float64(c.Dx()) / float64(c.Dy())
}
func chop(x float64) float64 {
if x < 0 {
return math.Ceil(x)
}
return math.Floor(x)
}
func thirds(x float64) float64 {
x = (math.Mod(x-(1.0/3.0)+1.0, 2.0)*0.5 - 0.5) * 16.0
return math.Max(1.0-x*x, 0.0)
}
func bounds(l float64) float64 {
return math.Min(math.Max(l, 0.0), 255)
}
func importance(crop Crop, x, y int) float64 {
if crop.Min.X > x || x >= crop.Max.X || crop.Min.Y > y || y >= crop.Max.Y {
return outsideImportance
}
xf := float64(x-crop.Min.X) / float64(crop.Dx())
yf := float64(y-crop.Min.Y) / float64(crop.Dy())
px := math.Abs(0.5-xf) * 2.0
py := math.Abs(0.5-yf) * 2.0
dx := math.Max(px-1.0+edgeRadius, 0.0)
dy := math.Max(py-1.0+edgeRadius, 0.0)
d := (dx*dx + dy*dy) * edgeWeight
s := 1.41 - math.Sqrt(px*px+py*py)
if ruleOfThirds {
s += (math.Max(0.0, s+d+0.5) * 1.2) * (thirds(px) + thirds(py))
}
return s + d
}
func score(output *image.RGBA, crop Crop) Score {
width := output.Bounds().Dx()
height := output.Bounds().Dy()
score := Score{}
// same loops but with downsampling
//for y := 0; y < height; y++ {
//for x := 0; x < width; x++ {
for y := 0; y <= height-scoreDownSample; y += scoreDownSample {
for x := 0; x <= width-scoreDownSample; x += scoreDownSample {
c := output.RGBAAt(x, y)
r8 := float64(c.R)
g8 := float64(c.G)
b8 := float64(c.B)
imp := importance(crop, int(x), int(y))
det := g8 / 255.0
score.Skin += r8 / 255.0 * (det + skinBias) * imp
score.Detail += det * imp
score.Saturation += b8 / 255.0 * (det + saturationBias) * imp
}
}
return score
}
func analyse(settings CropSettings, img *image.RGBA, cropWidth, cropHeight, realMinScale float64) (image.Rectangle, error) {
o := image.NewRGBA(img.Bounds())
now := time.Now()
edgeDetect(img, o)
settings.Log.Println("Time elapsed edge:", time.Since(now))
debugOutput(settings.DebugMode, o, "edge")
now = time.Now()
skinDetect(img, o)
settings.Log.Println("Time elapsed skin:", time.Since(now))
debugOutput(settings.DebugMode, o, "skin")
now = time.Now()
saturationDetect(img, o)
settings.Log.Println("Time elapsed sat:", time.Since(now))
debugOutput(settings.DebugMode, o, "saturation")
now = time.Now()
var topCrop Crop
topScore := -1.0
cs := crops(o, cropWidth, cropHeight, realMinScale)
settings.Log.Println("Time elapsed crops:", time.Since(now), len(cs))
now = time.Now()
for _, crop := range cs {
nowIn := time.Now()
crop.Score = score(o, crop)
settings.Log.Println("Time elapsed single-score:", time.Since(nowIn))
if crop.totalScore() > topScore {
topCrop = crop
topScore = crop.totalScore()
}
}
settings.Log.Println("Time elapsed score:", time.Since(now))
if settings.DebugMode {
drawDebugCrop(topCrop, o)
debugOutput(true, o, "final")
}
return topCrop.Rectangle, nil
}
func saturation(c color.RGBA) float64 {
cMax, cMin := uint8(0), uint8(255)
if c.R > cMax {
cMax = c.R
}
if c.R < cMin {
cMin = c.R
}
if c.G > cMax {
cMax = c.G
}
if c.G < cMin {
cMin = c.G
}
if c.B > cMax {
cMax = c.B
}
if c.B < cMin {
cMin = c.B
}
if cMax == cMin {
return 0
}
maximum := float64(cMax) / 255.0
minimum := float64(cMin) / 255.0
l := (maximum + minimum) / 2.0
d := maximum - minimum
if l > 0.5 {
return d / (2.0 - maximum - minimum)
}
return d / (maximum + minimum)
}
func cie(c color.RGBA) float64 {
return 0.5126*float64(c.B) + 0.7152*float64(c.G) + 0.0722*float64(c.R)
}
func skinCol(c color.RGBA) float64 {
r8, g8, b8 := float64(c.R), float64(c.G), float64(c.B)
mag := math.Sqrt(r8*r8 + g8*g8 + b8*b8)
rd := r8/mag - skinColor[0]
gd := g8/mag - skinColor[1]
bd := b8/mag - skinColor[2]
d := math.Sqrt(rd*rd + gd*gd + bd*bd)
return 1.0 - d
}
func makeCies(img *image.RGBA) []float64 {
width := img.Bounds().Dx()
height := img.Bounds().Dy()
cies := make([]float64, width*height, width*height)
i := 0
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
cies[i] = cie(img.RGBAAt(x, y))
i++
}
}
return cies
}
func edgeDetect(i *image.RGBA, o *image.RGBA) {
width := i.Bounds().Dx()
height := i.Bounds().Dy()
cies := makeCies(i)
var lightness float64
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
if x == 0 || x >= width-1 || y == 0 || y >= height-1 {
//lightness = cie((*i).At(x, y))
lightness = 0
} else {
lightness = cies[y*width+x]*4.0 -
cies[x+(y-1)*width] -
cies[x-1+y*width] -
cies[x+1+y*width] -
cies[x+(y+1)*width]
}
nc := color.RGBA{0, uint8(bounds(lightness)), 0, 255}
o.SetRGBA(x, y, nc)
}
}
}
func skinDetect(i *image.RGBA, o *image.RGBA) {
width := i.Bounds().Dx()
height := i.Bounds().Dy()
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
lightness := cie(i.RGBAAt(x, y)) / 255.0
skin := skinCol(i.RGBAAt(x, y))
c := o.RGBAAt(x, y)
if skin > skinThreshold && lightness >= skinBrightnessMin && lightness <= skinBrightnessMax {
r := (skin - skinThreshold) * (255.0 / (1.0 - skinThreshold))
nc := color.RGBA{uint8(bounds(r)), c.G, c.B, 255}
o.SetRGBA(x, y, nc)
} else {
nc := color.RGBA{0, c.G, c.B, 255}
o.SetRGBA(x, y, nc)
}
}
}
}
func saturationDetect(i *image.RGBA, o *image.RGBA) {
width := i.Bounds().Dx()
height := i.Bounds().Dy()
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
lightness := cie(i.RGBAAt(x, y)) / 255.0
saturation := saturation(i.RGBAAt(x, y))
c := o.RGBAAt(x, y)
if saturation > saturationThreshold && lightness >= saturationBrightnessMin && lightness <= saturationBrightnessMax {
b := (saturation - saturationThreshold) * (255.0 / (1.0 - saturationThreshold))
nc := color.RGBA{c.R, c.G, uint8(bounds(b)), 255}
o.SetRGBA(x, y, nc)
} else {
nc := color.RGBA{c.R, c.G, 0, 255}
o.SetRGBA(x, y, nc)
}
}
}
}
func crops(i image.Image, cropWidth, cropHeight, realMinScale float64) []Crop {
res := []Crop{}
width := i.Bounds().Dx()
height := i.Bounds().Dy()
minDimension := math.Min(float64(width), float64(height))
var cropW, cropH float64
if cropWidth != 0.0 {
cropW = cropWidth
} else {
cropW = minDimension
}
if cropHeight != 0.0 {
cropH = cropHeight
} else {
cropH = minDimension
}
for scale := maxScale; scale >= realMinScale; scale -= scaleStep {
for y := 0; float64(y)+cropH*scale <= float64(height); y += step {
for x := 0; float64(x)+cropW*scale <= float64(width); x += step {
res = append(res, Crop{
Rectangle: image.Rect(x, y, x+int(cropW*scale), y+int(cropH*scale)),
})
}
}
}
return res
}
// toRGBA converts an image.Image to an image.RGBA
func toRGBA(img image.Image) *image.RGBA {
switch img.(type) {
case *image.RGBA:
return img.(*image.RGBA)
}
out := image.NewRGBA(img.Bounds())
draw.Copy(out, image.Pt(0, 0), img, img.Bounds(), draw.Src, nil)
return out
}
// SmartCrop applies the smartcrop algorithms on the the given image and returns
// the top crop or an error if something went wrong.
// This is still here for legacy/backwards-compat reasons
func SmartCrop(img image.Image, width, height int) (image.Rectangle, error) {
analyzer := NewAnalyzer()
return analyzer.FindBestCrop(img, width, height)
}

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Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
THIS SOFTWARE.

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Resize
======
Image resizing for the [Go programming language](http://golang.org) with common interpolation methods.
[![Build Status](https://travis-ci.org/nfnt/resize.svg)](https://travis-ci.org/nfnt/resize)
Installation
------------
```bash
$ go get github.com/nfnt/resize
```
It's that easy!
Usage
-----
This package needs at least Go 1.1. Import package with
```go
import "github.com/nfnt/resize"
```
The resize package provides 2 functions:
* `resize.Resize` creates a scaled image with new dimensions (`width`, `height`) using the interpolation function `interp`.
If either `width` or `height` is set to 0, it will be set to an aspect ratio preserving value.
* `resize.Thumbnail` downscales an image preserving its aspect ratio to the maximum dimensions (`maxWidth`, `maxHeight`).
It will return the original image if original sizes are smaller than the provided dimensions.
```go
resize.Resize(width, height uint, img image.Image, interp resize.InterpolationFunction) image.Image
resize.Thumbnail(maxWidth, maxHeight uint, img image.Image, interp resize.InterpolationFunction) image.Image
```
The provided interpolation functions are (from fast to slow execution time)
- `NearestNeighbor`: [Nearest-neighbor interpolation](http://en.wikipedia.org/wiki/Nearest-neighbor_interpolation)
- `Bilinear`: [Bilinear interpolation](http://en.wikipedia.org/wiki/Bilinear_interpolation)
- `Bicubic`: [Bicubic interpolation](http://en.wikipedia.org/wiki/Bicubic_interpolation)
- `MitchellNetravali`: [Mitchell-Netravali interpolation](http://dl.acm.org/citation.cfm?id=378514)
- `Lanczos2`: [Lanczos resampling](http://en.wikipedia.org/wiki/Lanczos_resampling) with a=2
- `Lanczos3`: [Lanczos resampling](http://en.wikipedia.org/wiki/Lanczos_resampling) with a=3
Which of these methods gives the best results depends on your use case.
Sample usage:
```go
package main
import (
"github.com/nfnt/resize"
"image/jpeg"
"log"
"os"
)
func main() {
// open "test.jpg"
file, err := os.Open("test.jpg")
if err != nil {
log.Fatal(err)
}
// decode jpeg into image.Image
img, err := jpeg.Decode(file)
if err != nil {
log.Fatal(err)
}
file.Close()
// resize to width 1000 using Lanczos resampling
// and preserve aspect ratio
m := resize.Resize(1000, 0, img, resize.Lanczos3)
out, err := os.Create("test_resized.jpg")
if err != nil {
log.Fatal(err)
}
defer out.Close()
// write new image to file
jpeg.Encode(out, m, nil)
}
```
Caveats
-------
* Optimized access routines are used for `image.RGBA`, `image.NRGBA`, `image.RGBA64`, `image.NRGBA64`, `image.YCbCr`, `image.Gray`, and `image.Gray16` types. All other image types are accessed in a generic way that will result in slow processing speed.
* JPEG images are stored in `image.YCbCr`. This image format stores data in a way that will decrease processing speed. A resize may be up to 2 times slower than with `image.RGBA`.
Downsizing Samples
-------
Downsizing is not as simple as it might look like. Images have to be filtered before they are scaled down, otherwise aliasing might occur.
Filtering is highly subjective: Applying too much will blur the whole image, too little will make aliasing become apparent.
Resize tries to provide sane defaults that should suffice in most cases.
### Artificial sample
Original image
![Rings](http://nfnt.github.com/img/rings_lg_orig.png)
<table>
<tr>
<th><img src="http://nfnt.github.com/img/rings_300_NearestNeighbor.png" /><br>Nearest-Neighbor</th>
<th><img src="http://nfnt.github.com/img/rings_300_Bilinear.png" /><br>Bilinear</th>
</tr>
<tr>
<th><img src="http://nfnt.github.com/img/rings_300_Bicubic.png" /><br>Bicubic</th>
<th><img src="http://nfnt.github.com/img/rings_300_MitchellNetravali.png" /><br>Mitchell-Netravali</th>
</tr>
<tr>
<th><img src="http://nfnt.github.com/img/rings_300_Lanczos2.png" /><br>Lanczos2</th>
<th><img src="http://nfnt.github.com/img/rings_300_Lanczos3.png" /><br>Lanczos3</th>
</tr>
</table>
### Real-Life sample
Original image
![Original](http://nfnt.github.com/img/IMG_3694_720.jpg)
<table>
<tr>
<th><img src="http://nfnt.github.com/img/IMG_3694_300_NearestNeighbor.png" /><br>Nearest-Neighbor</th>
<th><img src="http://nfnt.github.com/img/IMG_3694_300_Bilinear.png" /><br>Bilinear</th>
</tr>
<tr>
<th><img src="http://nfnt.github.com/img/IMG_3694_300_Bicubic.png" /><br>Bicubic</th>
<th><img src="http://nfnt.github.com/img/IMG_3694_300_MitchellNetravali.png" /><br>Mitchell-Netravali</th>
</tr>
<tr>
<th><img src="http://nfnt.github.com/img/IMG_3694_300_Lanczos2.png" /><br>Lanczos2</th>
<th><img src="http://nfnt.github.com/img/IMG_3694_300_Lanczos3.png" /><br>Lanczos3</th>
</tr>
</table>
License
-------
Copyright (c) 2012 Jan Schlicht <janschlicht@gmail.com>
Resize is released under a MIT style license.

438
vendor/github.com/nfnt/resize/converter.go generated vendored Normal file
View file

@ -0,0 +1,438 @@
/*
Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
THIS SOFTWARE.
*/
package resize
import "image"
// Keep value in [0,255] range.
func clampUint8(in int32) uint8 {
// casting a negative int to an uint will result in an overflown
// large uint. this behavior will be exploited here and in other functions
// to achieve a higher performance.
if uint32(in) < 256 {
return uint8(in)
}
if in > 255 {
return 255
}
return 0
}
// Keep value in [0,65535] range.
func clampUint16(in int64) uint16 {
if uint64(in) < 65536 {
return uint16(in)
}
if in > 65535 {
return 65535
}
return 0
}
func resizeGeneric(in image.Image, out *image.RGBA64, scale float64, coeffs []int32, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]int64
var sum int64
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case xi < 0:
xi = 0
case xi >= maxX:
xi = maxX
}
r, g, b, a := in.At(xi+in.Bounds().Min.X, x+in.Bounds().Min.Y).RGBA()
rgba[0] += int64(coeff) * int64(r)
rgba[1] += int64(coeff) * int64(g)
rgba[2] += int64(coeff) * int64(b)
rgba[3] += int64(coeff) * int64(a)
sum += int64(coeff)
}
}
offset := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*8
value := clampUint16(rgba[0] / sum)
out.Pix[offset+0] = uint8(value >> 8)
out.Pix[offset+1] = uint8(value)
value = clampUint16(rgba[1] / sum)
out.Pix[offset+2] = uint8(value >> 8)
out.Pix[offset+3] = uint8(value)
value = clampUint16(rgba[2] / sum)
out.Pix[offset+4] = uint8(value >> 8)
out.Pix[offset+5] = uint8(value)
value = clampUint16(rgba[3] / sum)
out.Pix[offset+6] = uint8(value >> 8)
out.Pix[offset+7] = uint8(value)
}
}
}
func resizeRGBA(in *image.RGBA, out *image.RGBA, scale float64, coeffs []int16, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]int32
var sum int32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 4
case xi >= maxX:
xi = 4 * maxX
default:
xi = 0
}
rgba[0] += int32(coeff) * int32(row[xi+0])
rgba[1] += int32(coeff) * int32(row[xi+1])
rgba[2] += int32(coeff) * int32(row[xi+2])
rgba[3] += int32(coeff) * int32(row[xi+3])
sum += int32(coeff)
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*4
out.Pix[xo+0] = clampUint8(rgba[0] / sum)
out.Pix[xo+1] = clampUint8(rgba[1] / sum)
out.Pix[xo+2] = clampUint8(rgba[2] / sum)
out.Pix[xo+3] = clampUint8(rgba[3] / sum)
}
}
}
func resizeNRGBA(in *image.NRGBA, out *image.RGBA, scale float64, coeffs []int16, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]int32
var sum int32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 4
case xi >= maxX:
xi = 4 * maxX
default:
xi = 0
}
// Forward alpha-premultiplication
a := int32(row[xi+3])
r := int32(row[xi+0]) * a
r /= 0xff
g := int32(row[xi+1]) * a
g /= 0xff
b := int32(row[xi+2]) * a
b /= 0xff
rgba[0] += int32(coeff) * r
rgba[1] += int32(coeff) * g
rgba[2] += int32(coeff) * b
rgba[3] += int32(coeff) * a
sum += int32(coeff)
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*4
out.Pix[xo+0] = clampUint8(rgba[0] / sum)
out.Pix[xo+1] = clampUint8(rgba[1] / sum)
out.Pix[xo+2] = clampUint8(rgba[2] / sum)
out.Pix[xo+3] = clampUint8(rgba[3] / sum)
}
}
}
func resizeRGBA64(in *image.RGBA64, out *image.RGBA64, scale float64, coeffs []int32, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]int64
var sum int64
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 8
case xi >= maxX:
xi = 8 * maxX
default:
xi = 0
}
rgba[0] += int64(coeff) * (int64(row[xi+0])<<8 | int64(row[xi+1]))
rgba[1] += int64(coeff) * (int64(row[xi+2])<<8 | int64(row[xi+3]))
rgba[2] += int64(coeff) * (int64(row[xi+4])<<8 | int64(row[xi+5]))
rgba[3] += int64(coeff) * (int64(row[xi+6])<<8 | int64(row[xi+7]))
sum += int64(coeff)
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*8
value := clampUint16(rgba[0] / sum)
out.Pix[xo+0] = uint8(value >> 8)
out.Pix[xo+1] = uint8(value)
value = clampUint16(rgba[1] / sum)
out.Pix[xo+2] = uint8(value >> 8)
out.Pix[xo+3] = uint8(value)
value = clampUint16(rgba[2] / sum)
out.Pix[xo+4] = uint8(value >> 8)
out.Pix[xo+5] = uint8(value)
value = clampUint16(rgba[3] / sum)
out.Pix[xo+6] = uint8(value >> 8)
out.Pix[xo+7] = uint8(value)
}
}
}
func resizeNRGBA64(in *image.NRGBA64, out *image.RGBA64, scale float64, coeffs []int32, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]int64
var sum int64
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 8
case xi >= maxX:
xi = 8 * maxX
default:
xi = 0
}
// Forward alpha-premultiplication
a := int64(uint16(row[xi+6])<<8 | uint16(row[xi+7]))
r := int64(uint16(row[xi+0])<<8|uint16(row[xi+1])) * a
r /= 0xffff
g := int64(uint16(row[xi+2])<<8|uint16(row[xi+3])) * a
g /= 0xffff
b := int64(uint16(row[xi+4])<<8|uint16(row[xi+5])) * a
b /= 0xffff
rgba[0] += int64(coeff) * r
rgba[1] += int64(coeff) * g
rgba[2] += int64(coeff) * b
rgba[3] += int64(coeff) * a
sum += int64(coeff)
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*8
value := clampUint16(rgba[0] / sum)
out.Pix[xo+0] = uint8(value >> 8)
out.Pix[xo+1] = uint8(value)
value = clampUint16(rgba[1] / sum)
out.Pix[xo+2] = uint8(value >> 8)
out.Pix[xo+3] = uint8(value)
value = clampUint16(rgba[2] / sum)
out.Pix[xo+4] = uint8(value >> 8)
out.Pix[xo+5] = uint8(value)
value = clampUint16(rgba[3] / sum)
out.Pix[xo+6] = uint8(value >> 8)
out.Pix[xo+7] = uint8(value)
}
}
}
func resizeGray(in *image.Gray, out *image.Gray, scale float64, coeffs []int16, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[(x-newBounds.Min.X)*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var gray int32
var sum int32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case xi < 0:
xi = 0
case xi >= maxX:
xi = maxX
}
gray += int32(coeff) * int32(row[xi])
sum += int32(coeff)
}
}
offset := (y-newBounds.Min.Y)*out.Stride + (x - newBounds.Min.X)
out.Pix[offset] = clampUint8(gray / sum)
}
}
}
func resizeGray16(in *image.Gray16, out *image.Gray16, scale float64, coeffs []int32, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var gray int64
var sum int64
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 2
case xi >= maxX:
xi = 2 * maxX
default:
xi = 0
}
gray += int64(coeff) * int64(uint16(row[xi+0])<<8|uint16(row[xi+1]))
sum += int64(coeff)
}
}
offset := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*2
value := clampUint16(gray / sum)
out.Pix[offset+0] = uint8(value >> 8)
out.Pix[offset+1] = uint8(value)
}
}
}
func resizeYCbCr(in *ycc, out *ycc, scale float64, coeffs []int16, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var p [3]int32
var sum int32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
coeff := coeffs[ci+i]
if coeff != 0 {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 3
case xi >= maxX:
xi = 3 * maxX
default:
xi = 0
}
p[0] += int32(coeff) * int32(row[xi+0])
p[1] += int32(coeff) * int32(row[xi+1])
p[2] += int32(coeff) * int32(row[xi+2])
sum += int32(coeff)
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*3
out.Pix[xo+0] = clampUint8(p[0] / sum)
out.Pix[xo+1] = clampUint8(p[1] / sum)
out.Pix[xo+2] = clampUint8(p[2] / sum)
}
}
}
func nearestYCbCr(in *ycc, out *ycc, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var p [3]float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 3
case xi >= maxX:
xi = 3 * maxX
default:
xi = 0
}
p[0] += float32(row[xi+0])
p[1] += float32(row[xi+1])
p[2] += float32(row[xi+2])
sum++
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*3
out.Pix[xo+0] = floatToUint8(p[0] / sum)
out.Pix[xo+1] = floatToUint8(p[1] / sum)
out.Pix[xo+2] = floatToUint8(p[2] / sum)
}
}
}

143
vendor/github.com/nfnt/resize/filters.go generated vendored Normal file
View file

@ -0,0 +1,143 @@
/*
Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
THIS SOFTWARE.
*/
package resize
import (
"math"
)
func nearest(in float64) float64 {
if in >= -0.5 && in < 0.5 {
return 1
}
return 0
}
func linear(in float64) float64 {
in = math.Abs(in)
if in <= 1 {
return 1 - in
}
return 0
}
func cubic(in float64) float64 {
in = math.Abs(in)
if in <= 1 {
return in*in*(1.5*in-2.5) + 1.0
}
if in <= 2 {
return in*(in*(2.5-0.5*in)-4.0) + 2.0
}
return 0
}
func mitchellnetravali(in float64) float64 {
in = math.Abs(in)
if in <= 1 {
return (7.0*in*in*in - 12.0*in*in + 5.33333333333) * 0.16666666666
}
if in <= 2 {
return (-2.33333333333*in*in*in + 12.0*in*in - 20.0*in + 10.6666666667) * 0.16666666666
}
return 0
}
func sinc(x float64) float64 {
x = math.Abs(x) * math.Pi
if x >= 1.220703e-4 {
return math.Sin(x) / x
}
return 1
}
func lanczos2(in float64) float64 {
if in > -2 && in < 2 {
return sinc(in) * sinc(in*0.5)
}
return 0
}
func lanczos3(in float64) float64 {
if in > -3 && in < 3 {
return sinc(in) * sinc(in*0.3333333333333333)
}
return 0
}
// range [-256,256]
func createWeights8(dy, filterLength int, blur, scale float64, kernel func(float64) float64) ([]int16, []int, int) {
filterLength = filterLength * int(math.Max(math.Ceil(blur*scale), 1))
filterFactor := math.Min(1./(blur*scale), 1)
coeffs := make([]int16, dy*filterLength)
start := make([]int, dy)
for y := 0; y < dy; y++ {
interpX := scale*(float64(y)+0.5) - 0.5
start[y] = int(interpX) - filterLength/2 + 1
interpX -= float64(start[y])
for i := 0; i < filterLength; i++ {
in := (interpX - float64(i)) * filterFactor
coeffs[y*filterLength+i] = int16(kernel(in) * 256)
}
}
return coeffs, start, filterLength
}
// range [-65536,65536]
func createWeights16(dy, filterLength int, blur, scale float64, kernel func(float64) float64) ([]int32, []int, int) {
filterLength = filterLength * int(math.Max(math.Ceil(blur*scale), 1))
filterFactor := math.Min(1./(blur*scale), 1)
coeffs := make([]int32, dy*filterLength)
start := make([]int, dy)
for y := 0; y < dy; y++ {
interpX := scale*(float64(y)+0.5) - 0.5
start[y] = int(interpX) - filterLength/2 + 1
interpX -= float64(start[y])
for i := 0; i < filterLength; i++ {
in := (interpX - float64(i)) * filterFactor
coeffs[y*filterLength+i] = int32(kernel(in) * 65536)
}
}
return coeffs, start, filterLength
}
func createWeightsNearest(dy, filterLength int, blur, scale float64) ([]bool, []int, int) {
filterLength = filterLength * int(math.Max(math.Ceil(blur*scale), 1))
filterFactor := math.Min(1./(blur*scale), 1)
coeffs := make([]bool, dy*filterLength)
start := make([]int, dy)
for y := 0; y < dy; y++ {
interpX := scale*(float64(y)+0.5) - 0.5
start[y] = int(interpX) - filterLength/2 + 1
interpX -= float64(start[y])
for i := 0; i < filterLength; i++ {
in := (interpX - float64(i)) * filterFactor
if in >= -0.5 && in < 0.5 {
coeffs[y*filterLength+i] = true
} else {
coeffs[y*filterLength+i] = false
}
}
}
return coeffs, start, filterLength
}

318
vendor/github.com/nfnt/resize/nearest.go generated vendored Normal file
View file

@ -0,0 +1,318 @@
/*
Copyright (c) 2014, Charlie Vieth <charlie.vieth@gmail.com>
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
THIS SOFTWARE.
*/
package resize
import "image"
func floatToUint8(x float32) uint8 {
// Nearest-neighbor values are always
// positive no need to check lower-bound.
if x > 0xfe {
return 0xff
}
return uint8(x)
}
func floatToUint16(x float32) uint16 {
if x > 0xfffe {
return 0xffff
}
return uint16(x)
}
func nearestGeneric(in image.Image, out *image.RGBA64, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case xi < 0:
xi = 0
case xi >= maxX:
xi = maxX
}
r, g, b, a := in.At(xi+in.Bounds().Min.X, x+in.Bounds().Min.Y).RGBA()
rgba[0] += float32(r)
rgba[1] += float32(g)
rgba[2] += float32(b)
rgba[3] += float32(a)
sum++
}
}
offset := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*8
value := floatToUint16(rgba[0] / sum)
out.Pix[offset+0] = uint8(value >> 8)
out.Pix[offset+1] = uint8(value)
value = floatToUint16(rgba[1] / sum)
out.Pix[offset+2] = uint8(value >> 8)
out.Pix[offset+3] = uint8(value)
value = floatToUint16(rgba[2] / sum)
out.Pix[offset+4] = uint8(value >> 8)
out.Pix[offset+5] = uint8(value)
value = floatToUint16(rgba[3] / sum)
out.Pix[offset+6] = uint8(value >> 8)
out.Pix[offset+7] = uint8(value)
}
}
}
func nearestRGBA(in *image.RGBA, out *image.RGBA, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 4
case xi >= maxX:
xi = 4 * maxX
default:
xi = 0
}
rgba[0] += float32(row[xi+0])
rgba[1] += float32(row[xi+1])
rgba[2] += float32(row[xi+2])
rgba[3] += float32(row[xi+3])
sum++
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*4
out.Pix[xo+0] = floatToUint8(rgba[0] / sum)
out.Pix[xo+1] = floatToUint8(rgba[1] / sum)
out.Pix[xo+2] = floatToUint8(rgba[2] / sum)
out.Pix[xo+3] = floatToUint8(rgba[3] / sum)
}
}
}
func nearestNRGBA(in *image.NRGBA, out *image.NRGBA, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 4
case xi >= maxX:
xi = 4 * maxX
default:
xi = 0
}
rgba[0] += float32(row[xi+0])
rgba[1] += float32(row[xi+1])
rgba[2] += float32(row[xi+2])
rgba[3] += float32(row[xi+3])
sum++
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*4
out.Pix[xo+0] = floatToUint8(rgba[0] / sum)
out.Pix[xo+1] = floatToUint8(rgba[1] / sum)
out.Pix[xo+2] = floatToUint8(rgba[2] / sum)
out.Pix[xo+3] = floatToUint8(rgba[3] / sum)
}
}
}
func nearestRGBA64(in *image.RGBA64, out *image.RGBA64, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 8
case xi >= maxX:
xi = 8 * maxX
default:
xi = 0
}
rgba[0] += float32(uint16(row[xi+0])<<8 | uint16(row[xi+1]))
rgba[1] += float32(uint16(row[xi+2])<<8 | uint16(row[xi+3]))
rgba[2] += float32(uint16(row[xi+4])<<8 | uint16(row[xi+5]))
rgba[3] += float32(uint16(row[xi+6])<<8 | uint16(row[xi+7]))
sum++
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*8
value := floatToUint16(rgba[0] / sum)
out.Pix[xo+0] = uint8(value >> 8)
out.Pix[xo+1] = uint8(value)
value = floatToUint16(rgba[1] / sum)
out.Pix[xo+2] = uint8(value >> 8)
out.Pix[xo+3] = uint8(value)
value = floatToUint16(rgba[2] / sum)
out.Pix[xo+4] = uint8(value >> 8)
out.Pix[xo+5] = uint8(value)
value = floatToUint16(rgba[3] / sum)
out.Pix[xo+6] = uint8(value >> 8)
out.Pix[xo+7] = uint8(value)
}
}
}
func nearestNRGBA64(in *image.NRGBA64, out *image.NRGBA64, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var rgba [4]float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 8
case xi >= maxX:
xi = 8 * maxX
default:
xi = 0
}
rgba[0] += float32(uint16(row[xi+0])<<8 | uint16(row[xi+1]))
rgba[1] += float32(uint16(row[xi+2])<<8 | uint16(row[xi+3]))
rgba[2] += float32(uint16(row[xi+4])<<8 | uint16(row[xi+5]))
rgba[3] += float32(uint16(row[xi+6])<<8 | uint16(row[xi+7]))
sum++
}
}
xo := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*8
value := floatToUint16(rgba[0] / sum)
out.Pix[xo+0] = uint8(value >> 8)
out.Pix[xo+1] = uint8(value)
value = floatToUint16(rgba[1] / sum)
out.Pix[xo+2] = uint8(value >> 8)
out.Pix[xo+3] = uint8(value)
value = floatToUint16(rgba[2] / sum)
out.Pix[xo+4] = uint8(value >> 8)
out.Pix[xo+5] = uint8(value)
value = floatToUint16(rgba[3] / sum)
out.Pix[xo+6] = uint8(value >> 8)
out.Pix[xo+7] = uint8(value)
}
}
}
func nearestGray(in *image.Gray, out *image.Gray, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var gray float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case xi < 0:
xi = 0
case xi >= maxX:
xi = maxX
}
gray += float32(row[xi])
sum++
}
}
offset := (y-newBounds.Min.Y)*out.Stride + (x - newBounds.Min.X)
out.Pix[offset] = floatToUint8(gray / sum)
}
}
}
func nearestGray16(in *image.Gray16, out *image.Gray16, scale float64, coeffs []bool, offset []int, filterLength int) {
newBounds := out.Bounds()
maxX := in.Bounds().Dx() - 1
for x := newBounds.Min.X; x < newBounds.Max.X; x++ {
row := in.Pix[x*in.Stride:]
for y := newBounds.Min.Y; y < newBounds.Max.Y; y++ {
var gray float32
var sum float32
start := offset[y]
ci := y * filterLength
for i := 0; i < filterLength; i++ {
if coeffs[ci+i] {
xi := start + i
switch {
case uint(xi) < uint(maxX):
xi *= 2
case xi >= maxX:
xi = 2 * maxX
default:
xi = 0
}
gray += float32(uint16(row[xi+0])<<8 | uint16(row[xi+1]))
sum++
}
}
offset := (y-newBounds.Min.Y)*out.Stride + (x-newBounds.Min.X)*2
value := floatToUint16(gray / sum)
out.Pix[offset+0] = uint8(value >> 8)
out.Pix[offset+1] = uint8(value)
}
}
}

614
vendor/github.com/nfnt/resize/resize.go generated vendored Normal file
View file

@ -0,0 +1,614 @@
/*
Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
THIS SOFTWARE.
*/
// Package resize implements various image resizing methods.
//
// The package works with the Image interface described in the image package.
// Various interpolation methods are provided and multiple processors may be
// utilized in the computations.
//
// Example:
// imgResized := resize.Resize(1000, 0, imgOld, resize.MitchellNetravali)
package resize
import (
"image"
"runtime"
"sync"
)
// An InterpolationFunction provides the parameters that describe an
// interpolation kernel. It returns the number of samples to take
// and the kernel function to use for sampling.
type InterpolationFunction int
// InterpolationFunction constants
const (
// Nearest-neighbor interpolation
NearestNeighbor InterpolationFunction = iota
// Bilinear interpolation
Bilinear
// Bicubic interpolation (with cubic hermite spline)
Bicubic
// Mitchell-Netravali interpolation
MitchellNetravali
// Lanczos interpolation (a=2)
Lanczos2
// Lanczos interpolation (a=3)
Lanczos3
)
// kernal, returns an InterpolationFunctions taps and kernel.
func (i InterpolationFunction) kernel() (int, func(float64) float64) {
switch i {
case Bilinear:
return 2, linear
case Bicubic:
return 4, cubic
case MitchellNetravali:
return 4, mitchellnetravali
case Lanczos2:
return 4, lanczos2
case Lanczos3:
return 6, lanczos3
default:
// Default to NearestNeighbor.
return 2, nearest
}
}
// values <1 will sharpen the image
var blur = 1.0
// Resize scales an image to new width and height using the interpolation function interp.
// A new image with the given dimensions will be returned.
// If one of the parameters width or height is set to 0, its size will be calculated so that
// the aspect ratio is that of the originating image.
// The resizing algorithm uses channels for parallel computation.
func Resize(width, height uint, img image.Image, interp InterpolationFunction) image.Image {
scaleX, scaleY := calcFactors(width, height, float64(img.Bounds().Dx()), float64(img.Bounds().Dy()))
if width == 0 {
width = uint(0.7 + float64(img.Bounds().Dx())/scaleX)
}
if height == 0 {
height = uint(0.7 + float64(img.Bounds().Dy())/scaleY)
}
// Trivial case: return input image
if int(width) == img.Bounds().Dx() && int(height) == img.Bounds().Dy() {
return img
}
if interp == NearestNeighbor {
return resizeNearest(width, height, scaleX, scaleY, img, interp)
}
taps, kernel := interp.kernel()
cpus := runtime.GOMAXPROCS(0)
wg := sync.WaitGroup{}
// Generic access to image.Image is slow in tight loops.
// The optimal access has to be determined from the concrete image type.
switch input := img.(type) {
case *image.RGBA:
// 8-bit precision
temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA)
go func() {
defer wg.Done()
resizeRGBA(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA)
go func() {
defer wg.Done()
resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.NRGBA:
// 8-bit precision
temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA)
go func() {
defer wg.Done()
resizeNRGBA(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA)
go func() {
defer wg.Done()
resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.YCbCr:
// 8-bit precision
// accessing the YCbCr arrays in a tight loop is slow.
// converting the image to ycc increases performance by 2x.
temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)
result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)
coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
in := imageYCbCrToYCC(input)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*ycc)
go func() {
defer wg.Done()
resizeYCbCr(in, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*ycc)
go func() {
defer wg.Done()
resizeYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result.YCbCr()
case *image.RGBA64:
// 16-bit precision
temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
resizeRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.NRGBA64:
// 16-bit precision
temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
resizeNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.Gray:
// 8-bit precision
temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewGray(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.Gray)
go func() {
defer wg.Done()
resizeGray(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.Gray)
go func() {
defer wg.Done()
resizeGray(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.Gray16:
// 16-bit precision
temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.Gray16)
go func() {
defer wg.Done()
resizeGray16(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.Gray16)
go func() {
defer wg.Done()
resizeGray16(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
default:
// 16-bit precision
temp := image.NewRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
resizeGeneric(img, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
}
}
func resizeNearest(width, height uint, scaleX, scaleY float64, img image.Image, interp InterpolationFunction) image.Image {
taps, _ := interp.kernel()
cpus := runtime.GOMAXPROCS(0)
wg := sync.WaitGroup{}
switch input := img.(type) {
case *image.RGBA:
// 8-bit precision
temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA)
go func() {
defer wg.Done()
nearestRGBA(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA)
go func() {
defer wg.Done()
nearestRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.NRGBA:
// 8-bit precision
temp := image.NewNRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewNRGBA(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.NRGBA)
go func() {
defer wg.Done()
nearestNRGBA(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.NRGBA)
go func() {
defer wg.Done()
nearestNRGBA(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.YCbCr:
// 8-bit precision
// accessing the YCbCr arrays in a tight loop is slow.
// converting the image to ycc increases performance by 2x.
temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)
result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
in := imageYCbCrToYCC(input)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*ycc)
go func() {
defer wg.Done()
nearestYCbCr(in, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*ycc)
go func() {
defer wg.Done()
nearestYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result.YCbCr()
case *image.RGBA64:
// 16-bit precision
temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
nearestRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.NRGBA64:
// 16-bit precision
temp := image.NewNRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewNRGBA64(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.NRGBA64)
go func() {
defer wg.Done()
nearestNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.NRGBA64)
go func() {
defer wg.Done()
nearestNRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.Gray:
// 8-bit precision
temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewGray(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.Gray)
go func() {
defer wg.Done()
nearestGray(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.Gray)
go func() {
defer wg.Done()
nearestGray(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
case *image.Gray16:
// 16-bit precision
temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))
result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.Gray16)
go func() {
defer wg.Done()
nearestGray16(input, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.Gray16)
go func() {
defer wg.Done()
nearestGray16(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
default:
// 16-bit precision
temp := image.NewRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))
result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))
// horizontal filter, results in transposed temporary image
coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(temp, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
nearestGeneric(img, slice, scaleX, coeffs, offset, filterLength)
}()
}
wg.Wait()
// horizontal filter on transposed image, result is not transposed
coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)
wg.Add(cpus)
for i := 0; i < cpus; i++ {
slice := makeSlice(result, i, cpus).(*image.RGBA64)
go func() {
defer wg.Done()
nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)
}()
}
wg.Wait()
return result
}
}
// Calculates scaling factors using old and new image dimensions.
func calcFactors(width, height uint, oldWidth, oldHeight float64) (scaleX, scaleY float64) {
if width == 0 {
if height == 0 {
scaleX = 1.0
scaleY = 1.0
} else {
scaleY = oldHeight / float64(height)
scaleX = scaleY
}
} else {
scaleX = oldWidth / float64(width)
if height == 0 {
scaleY = scaleX
} else {
scaleY = oldHeight / float64(height)
}
}
return
}
type imageWithSubImage interface {
image.Image
SubImage(image.Rectangle) image.Image
}
func makeSlice(img imageWithSubImage, i, n int) image.Image {
return img.SubImage(image.Rect(img.Bounds().Min.X, img.Bounds().Min.Y+i*img.Bounds().Dy()/n, img.Bounds().Max.X, img.Bounds().Min.Y+(i+1)*img.Bounds().Dy()/n))
}

55
vendor/github.com/nfnt/resize/thumbnail.go generated vendored Normal file
View file

@ -0,0 +1,55 @@
/*
Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
THIS SOFTWARE.
*/
package resize
import (
"image"
)
// Thumbnail will downscale provided image to max width and height preserving
// original aspect ratio and using the interpolation function interp.
// It will return original image, without processing it, if original sizes
// are already smaller than provided constraints.
func Thumbnail(maxWidth, maxHeight uint, img image.Image, interp InterpolationFunction) image.Image {
origBounds := img.Bounds()
origWidth := uint(origBounds.Dx())
origHeight := uint(origBounds.Dy())
newWidth, newHeight := origWidth, origHeight
// Return original image if it have same or smaller size as constraints
if maxWidth >= origWidth && maxHeight >= origHeight {
return img
}
// Preserve aspect ratio
if origWidth > maxWidth {
newHeight = uint(origHeight * maxWidth / origWidth)
if newHeight < 1 {
newHeight = 1
}
newWidth = maxWidth
}
if newHeight > maxHeight {
newWidth = uint(newWidth * maxHeight / newHeight)
if newWidth < 1 {
newWidth = 1
}
newHeight = maxHeight
}
return Resize(newWidth, newHeight, img, interp)
}

227
vendor/github.com/nfnt/resize/ycc.go generated vendored Normal file
View file

@ -0,0 +1,227 @@
/*
Copyright (c) 2014, Charlie Vieth <charlie.vieth@gmail.com>
Permission to use, copy, modify, and/or distribute this software for any purpose
with or without fee is hereby granted, provided that the above copyright notice
and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
THIS SOFTWARE.
*/
package resize
import (
"image"
"image/color"
)
// ycc is an in memory YCbCr image. The Y, Cb and Cr samples are held in a
// single slice to increase resizing performance.
type ycc struct {
// Pix holds the image's pixels, in Y, Cb, Cr order. The pixel at
// (x, y) starts at Pix[(y-Rect.Min.Y)*Stride + (x-Rect.Min.X)*3].
Pix []uint8
// Stride is the Pix stride (in bytes) between vertically adjacent pixels.
Stride int
// Rect is the image's bounds.
Rect image.Rectangle
// SubsampleRatio is the subsample ratio of the original YCbCr image.
SubsampleRatio image.YCbCrSubsampleRatio
}
// PixOffset returns the index of the first element of Pix that corresponds to
// the pixel at (x, y).
func (p *ycc) PixOffset(x, y int) int {
return (y-p.Rect.Min.Y)*p.Stride + (x-p.Rect.Min.X)*3
}
func (p *ycc) Bounds() image.Rectangle {
return p.Rect
}
func (p *ycc) ColorModel() color.Model {
return color.YCbCrModel
}
func (p *ycc) At(x, y int) color.Color {
if !(image.Point{x, y}.In(p.Rect)) {
return color.YCbCr{}
}
i := p.PixOffset(x, y)
return color.YCbCr{
p.Pix[i+0],
p.Pix[i+1],
p.Pix[i+2],
}
}
func (p *ycc) Opaque() bool {
return true
}
// SubImage returns an image representing the portion of the image p visible
// through r. The returned value shares pixels with the original image.
func (p *ycc) SubImage(r image.Rectangle) image.Image {
r = r.Intersect(p.Rect)
if r.Empty() {
return &ycc{SubsampleRatio: p.SubsampleRatio}
}
i := p.PixOffset(r.Min.X, r.Min.Y)
return &ycc{
Pix: p.Pix[i:],
Stride: p.Stride,
Rect: r,
SubsampleRatio: p.SubsampleRatio,
}
}
// newYCC returns a new ycc with the given bounds and subsample ratio.
func newYCC(r image.Rectangle, s image.YCbCrSubsampleRatio) *ycc {
w, h := r.Dx(), r.Dy()
buf := make([]uint8, 3*w*h)
return &ycc{Pix: buf, Stride: 3 * w, Rect: r, SubsampleRatio: s}
}
// YCbCr converts ycc to a YCbCr image with the same subsample ratio
// as the YCbCr image that ycc was generated from.
func (p *ycc) YCbCr() *image.YCbCr {
ycbcr := image.NewYCbCr(p.Rect, p.SubsampleRatio)
var off int
switch ycbcr.SubsampleRatio {
case image.YCbCrSubsampleRatio422:
for y := ycbcr.Rect.Min.Y; y < ycbcr.Rect.Max.Y; y++ {
yy := (y - ycbcr.Rect.Min.Y) * ycbcr.YStride
cy := (y - ycbcr.Rect.Min.Y) * ycbcr.CStride
for x := ycbcr.Rect.Min.X; x < ycbcr.Rect.Max.X; x++ {
xx := (x - ycbcr.Rect.Min.X)
yi := yy + xx
ci := cy + xx/2
ycbcr.Y[yi] = p.Pix[off+0]
ycbcr.Cb[ci] = p.Pix[off+1]
ycbcr.Cr[ci] = p.Pix[off+2]
off += 3
}
}
case image.YCbCrSubsampleRatio420:
for y := ycbcr.Rect.Min.Y; y < ycbcr.Rect.Max.Y; y++ {
yy := (y - ycbcr.Rect.Min.Y) * ycbcr.YStride
cy := (y/2 - ycbcr.Rect.Min.Y/2) * ycbcr.CStride
for x := ycbcr.Rect.Min.X; x < ycbcr.Rect.Max.X; x++ {
xx := (x - ycbcr.Rect.Min.X)
yi := yy + xx
ci := cy + xx/2
ycbcr.Y[yi] = p.Pix[off+0]
ycbcr.Cb[ci] = p.Pix[off+1]
ycbcr.Cr[ci] = p.Pix[off+2]
off += 3
}
}
case image.YCbCrSubsampleRatio440:
for y := ycbcr.Rect.Min.Y; y < ycbcr.Rect.Max.Y; y++ {
yy := (y - ycbcr.Rect.Min.Y) * ycbcr.YStride
cy := (y/2 - ycbcr.Rect.Min.Y/2) * ycbcr.CStride
for x := ycbcr.Rect.Min.X; x < ycbcr.Rect.Max.X; x++ {
xx := (x - ycbcr.Rect.Min.X)
yi := yy + xx
ci := cy + xx
ycbcr.Y[yi] = p.Pix[off+0]
ycbcr.Cb[ci] = p.Pix[off+1]
ycbcr.Cr[ci] = p.Pix[off+2]
off += 3
}
}
default:
// Default to 4:4:4 subsampling.
for y := ycbcr.Rect.Min.Y; y < ycbcr.Rect.Max.Y; y++ {
yy := (y - ycbcr.Rect.Min.Y) * ycbcr.YStride
cy := (y - ycbcr.Rect.Min.Y) * ycbcr.CStride
for x := ycbcr.Rect.Min.X; x < ycbcr.Rect.Max.X; x++ {
xx := (x - ycbcr.Rect.Min.X)
yi := yy + xx
ci := cy + xx
ycbcr.Y[yi] = p.Pix[off+0]
ycbcr.Cb[ci] = p.Pix[off+1]
ycbcr.Cr[ci] = p.Pix[off+2]
off += 3
}
}
}
return ycbcr
}
// imageYCbCrToYCC converts a YCbCr image to a ycc image for resizing.
func imageYCbCrToYCC(in *image.YCbCr) *ycc {
w, h := in.Rect.Dx(), in.Rect.Dy()
r := image.Rect(0, 0, w, h)
buf := make([]uint8, 3*w*h)
p := ycc{Pix: buf, Stride: 3 * w, Rect: r, SubsampleRatio: in.SubsampleRatio}
var off int
switch in.SubsampleRatio {
case image.YCbCrSubsampleRatio422:
for y := in.Rect.Min.Y; y < in.Rect.Max.Y; y++ {
yy := (y - in.Rect.Min.Y) * in.YStride
cy := (y - in.Rect.Min.Y) * in.CStride
for x := in.Rect.Min.X; x < in.Rect.Max.X; x++ {
xx := (x - in.Rect.Min.X)
yi := yy + xx
ci := cy + xx/2
p.Pix[off+0] = in.Y[yi]
p.Pix[off+1] = in.Cb[ci]
p.Pix[off+2] = in.Cr[ci]
off += 3
}
}
case image.YCbCrSubsampleRatio420:
for y := in.Rect.Min.Y; y < in.Rect.Max.Y; y++ {
yy := (y - in.Rect.Min.Y) * in.YStride
cy := (y/2 - in.Rect.Min.Y/2) * in.CStride
for x := in.Rect.Min.X; x < in.Rect.Max.X; x++ {
xx := (x - in.Rect.Min.X)
yi := yy + xx
ci := cy + xx/2
p.Pix[off+0] = in.Y[yi]
p.Pix[off+1] = in.Cb[ci]
p.Pix[off+2] = in.Cr[ci]
off += 3
}
}
case image.YCbCrSubsampleRatio440:
for y := in.Rect.Min.Y; y < in.Rect.Max.Y; y++ {
yy := (y - in.Rect.Min.Y) * in.YStride
cy := (y/2 - in.Rect.Min.Y/2) * in.CStride
for x := in.Rect.Min.X; x < in.Rect.Max.X; x++ {
xx := (x - in.Rect.Min.X)
yi := yy + xx
ci := cy + xx
p.Pix[off+0] = in.Y[yi]
p.Pix[off+1] = in.Cb[ci]
p.Pix[off+2] = in.Cr[ci]
off += 3
}
}
default:
// Default to 4:4:4 subsampling.
for y := in.Rect.Min.Y; y < in.Rect.Max.Y; y++ {
yy := (y - in.Rect.Min.Y) * in.YStride
cy := (y - in.Rect.Min.Y) * in.CStride
for x := in.Rect.Min.X; x < in.Rect.Max.X; x++ {
xx := (x - in.Rect.Min.X)
yi := yy + xx
ci := cy + xx
p.Pix[off+0] = in.Y[yi]
p.Pix[off+1] = in.Cb[ci]
p.Pix[off+2] = in.Cr[ci]
off += 3
}
}
}
return &p
}