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chromium / external / github.com / disintegration / imaging / v1.4.0
commitb039796423f87e7caca7f8eaace36878f2cce73d[log] [tgz]
authorGrigory Dryapak <grigory.dryapak@gmail.com>Thu Mar 08 13:13:05 2018
committerGrigory Dryapak <grigory.dryapak@gmail.com>Thu Mar 08 13:13:05 2018
tree7da0e2d7c1f6a1a183a0c2b4a068eed5ceb6967e
parentce9939250c91cf0172b16ee9933e881cf7557baf [diff]
add gif encode options
2 files changed
tree: 7da0e2d7c1f6a1a183a0c2b4a068eed5ceb6967e
  1. testdata/
  2. .travis.yml
  3. adjust.go
  4. adjust_test.go
  5. convolution.go
  6. convolution_test.go
  7. doc.go
  8. effects.go
  9. effects_test.go
  10. example_test.go
  11. helpers.go
  12. helpers_test.go
  13. histogram.go
  14. histogram_test.go
  15. LICENSE
  16. README.md
  17. resize.go
  18. resize_test.go
  19. scanner.go
  20. scanner_test.go
  21. tools.go
  22. tools_test.go
  23. transform.go
  24. transform_test.go
  25. utils.go
  26. utils_test.go
README.md

Imaging

GoDoc Build Status Coverage Status

Package imaging provides basic imaging 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

// 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

The same image resized from 600x400px to 150x100px using different resampling filters. From faster (lower quality) to slower (higher quality):

FilterResize result
imaging.NearestNeighbordstImage
imaging.LineardstImage
imaging.CatmullRomdstImage
imaging.LanczosdstImage

Gaussian Blur

dstImage := imaging.Blur(srcImage, 0.5)

Sigma parameter allows to control the strength of the blurring effect.

Original imageSigma = 0.5Sigma = 1.5
srcImagedstImagedstImage

Sharpening

dstImage := imaging.Sharpen(srcImage, 0.5)

Sharpen uses gaussian function internally. Sigma parameter allows to control the strength of the sharpening effect.

Original imageSigma = 0.5Sigma = 1.5
srcImagedstImagedstImage

Gamma correction

dstImage := imaging.AdjustGamma(srcImage, 0.75)
Original imageGamma = 0.75Gamma = 1.25
srcImagedstImagedstImage

Contrast adjustment

dstImage := imaging.AdjustContrast(srcImage, 20)
Original imageContrast = 15Contrast = -15
srcImagedstImagedstImage

Brightness adjustment

dstImage := imaging.AdjustBrightness(srcImage, 20)
Original imageBrightness = 10Brightness = -10
srcImagedstImagedstImage

Example code

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