From 64fa922ec013079f8f0c90fc9e93c56db3611d30 Mon Sep 17 00:00:00 2001 From: Tulir Asokan Date: Sun, 22 Apr 2018 21:25:06 +0300 Subject: Switch to dep --- vendor/github.com/disintegration/imaging/README.md | 188 +++++++++++++++++++++ 1 file changed, 188 insertions(+) create mode 100644 vendor/github.com/disintegration/imaging/README.md (limited to 'vendor/github.com/disintegration/imaging/README.md') diff --git a/vendor/github.com/disintegration/imaging/README.md b/vendor/github.com/disintegration/imaging/README.md new file mode 100644 index 0000000..c7ee30f --- /dev/null +++ b/vendor/github.com/disintegration/imaging/README.md @@ -0,0 +1,188 @@ +# Imaging + +[![GoDoc](https://godoc.org/github.com/disintegration/imaging?status.svg)](https://godoc.org/github.com/disintegration/imaging) +[![Build Status](https://travis-ci.org/disintegration/imaging.svg?branch=master)](https://travis-ci.org/disintegration/imaging) +[![Coverage Status](https://coveralls.io/repos/github/disintegration/imaging/badge.svg?branch=master&service=github)](https://coveralls.io/github/disintegration/imaging?branch=master) +[![Go Report Card](https://goreportcard.com/badge/github.com/disintegration/imaging)](https://goreportcard.com/report/github.com/disintegration/imaging) + +Package imaging provides basic image processing functions (resize, rotate, crop, brightness/contrast adjustments, etc.). + +All the image processing functions provided by the package accept 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 + + 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 fill the 100x100px area. +dstImageFill := imaging.Fill(srcImage, 100, 100, imaging.Center, 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, 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: + +![srcImage](testdata/branches.png) + +The same image resized from 600x400px to 150x100px using different resampling filters. +From faster (lower quality) to slower (higher quality): + +Filter | Resize result +--------------------------|--------------------------------------------- +`imaging.NearestNeighbor` | ![dstImage](testdata/out_resize_nearest.png) +`imaging.Linear` | ![dstImage](testdata/out_resize_linear.png) +`imaging.CatmullRom` | ![dstImage](testdata/out_resize_catrom.png) +`imaging.Lanczos` | ![dstImage](testdata/out_resize_lanczos.png) + + +### 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](testdata/flowers_small.png) | ![dstImage](testdata/out_blur_0.5.png) | ![dstImage](testdata/out_blur_1.5.png) + +### Sharpening + +```go +dstImage := imaging.Sharpen(srcImage, 0.5) +``` + +`Sharpen` uses gaussian function internally. Sigma parameter allows to control the strength of the sharpening effect. + +Original image | Sigma = 0.5 | Sigma = 1.5 +-----------------------------------|-------------------------------------------|------------------------------------------ +![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_sharpen_0.5.png) | ![dstImage](testdata/out_sharpen_1.5.png) + +### Gamma correction + +```go +dstImage := imaging.AdjustGamma(srcImage, 0.75) +``` + +Original image | Gamma = 0.75 | Gamma = 1.25 +-----------------------------------|------------------------------------------|----------------------------------------- +![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_gamma_0.75.png) | ![dstImage](testdata/out_gamma_1.25.png) + +### Contrast adjustment + +```go +dstImage := imaging.AdjustContrast(srcImage, 20) +``` + +Original image | Contrast = 15 | Contrast = -15 +-----------------------------------|--------------------------------------------|------------------------------------------- +![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_contrast_p15.png) | ![dstImage](testdata/out_contrast_m15.png) + +### Brightness adjustment + +```go +dstImage := imaging.AdjustBrightness(srcImage, 20) +``` + +Original image | Brightness = 10 | Brightness = -10 +-----------------------------------|----------------------------------------------|--------------------------------------------- +![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_brightness_p10.png) | ![dstImage](testdata/out_brightness_m10.png) + +## Example code + +```go +package main + +import ( + "image" + "image/color" + "log" + + "github.com/disintegration/imaging" +) + +func main() { + // Open a test image. + src, err := imaging.Open("testdata/flowers.png") + if err != nil { + log.Fatalf("failed to open image: %v", err) + } + + // Crop the original image to 300x300px size using the center anchor. + src = imaging.CropAnchor(src, 300, 300, imaging.Center) + + // Resize the cropped image to width = 200px preserving the aspect ratio. + src = imaging.Resize(src, 200, 0, imaging.Lanczos) + + // Create a blurred version of the image. + img1 := imaging.Blur(src, 5) + + // Create a grayscale version of the image with higher contrast and sharpness. + img2 := imaging.Grayscale(src) + img2 = imaging.AdjustContrast(img2, 20) + img2 = imaging.Sharpen(img2, 2) + + // Create an inverted version of the image. + img3 := imaging.Invert(src) + + // Create an embossed version of the image using a convolution filter. + img4 := imaging.Convolve3x3( + src, + [9]float64{ + -1, -1, 0, + -1, 1, 1, + 0, 1, 1, + }, + nil, + ) + + // Create a new image and paste the four produced images into it. + dst := imaging.New(400, 400, color.NRGBA{0, 0, 0, 0}) + dst = imaging.Paste(dst, img1, image.Pt(0, 0)) + dst = imaging.Paste(dst, img2, image.Pt(0, 200)) + dst = imaging.Paste(dst, img3, image.Pt(200, 0)) + dst = imaging.Paste(dst, img4, image.Pt(200, 200)) + + // Save the resulting image as JPEG. + err = imaging.Save(dst, "testdata/out_example.jpg") + if err != nil { + log.Fatalf("failed to save image: %v", err) + } +} +``` + +Output: + +![dstImage](testdata/out_example.jpg) \ No newline at end of file -- cgit v1.2.3