Giter Site home page Giter Site logo

gift's Introduction

GO IMAGE FILTERING TOOLKIT (GIFT)

GoDoc Build Status Coverage Status Go Report Card

Package gift provides a set of useful image processing filters.

Pure Go. No external dependencies outside of the Go standard library.

INSTALLATION / UPDATING

go get -u github.com/disintegration/gift

DOCUMENTATION

http://godoc.org/github.com/disintegration/gift

QUICK START

// 1. Create a new filter list and add some filters.
g := gift.New(
	gift.Resize(800, 0, gift.LanczosResampling),
	gift.UnsharpMask(1, 1, 0),
)

// 2. Create a new image of the corresponding size.
// dst is a new target image, src is the original image.
dst := image.NewRGBA(g.Bounds(src.Bounds()))

// 3. Use the Draw func to apply the filters to src and store the result in dst.
g.Draw(dst, src)

USAGE

To create a sequence of filters, the New function is used:

g := gift.New(
	gift.Grayscale(),
	gift.Contrast(10),
)

Filters also can be added using the Add method:

g.Add(GaussianBlur(2))

The Bounds method takes the bounds of the source image and returns appropriate bounds for the destination image to fit the result (for example, after using Resize or Rotate filters).

dst := image.NewRGBA(g.Bounds(src.Bounds()))

There are two methods available to apply these filters to an image:

  • Draw applies all the added filters to the src image and outputs the result to the dst image starting from the top-left corner (Min point).
g.Draw(dst, src)
  • DrawAt provides more control. It outputs the filtered src image to the dst image at the specified position using the specified image composition operator. This example is equivalent to the previous:
g.DrawAt(dst, src, dst.Bounds().Min, gift.CopyOperator)

Two image composition operators are supported by now:

  • CopyOperator - Replaces pixels of the dst image with pixels of the filtered src image. This mode is used by the Draw method.
  • OverOperator - Places the filtered src image on top of the dst image. This mode makes sence if the filtered src image has transparent areas.

Empty filter list can be used to create a copy of an image or to paste one image to another. For example:

// Create a new image with dimensions of the bgImage.
dstImage := image.NewRGBA(bgImage.Bounds())
// Copy the bgImage to the dstImage.
gift.New().Draw(dstImage, bgImage)
// Draw the fgImage over the dstImage at the (100, 100) position.
gift.New().DrawAt(dstImage, fgImage, image.Pt(100, 100), gift.OverOperator)

SUPPORTED FILTERS

  • Transformations

    • Crop(rect image.Rectangle)
    • CropToSize(width, height int, anchor Anchor)
    • FlipHorizontal()
    • FlipVertical()
    • Resize(width, height int, resampling Resampling)
    • ResizeToFill(width, height int, resampling Resampling, anchor Anchor)
    • ResizeToFit(width, height int, resampling Resampling)
    • Rotate(angle float32, backgroundColor color.Color, interpolation Interpolation)
    • Rotate180()
    • Rotate270()
    • Rotate90()
    • Transpose()
    • Transverse()
  • Adjustments & effects

    • Brightness(percentage float32)
    • ColorBalance(percentageRed, percentageGreen, percentageBlue float32)
    • ColorFunc(fn func(r0, g0, b0, a0 float32) (r, g, b, a float32))
    • Colorize(hue, saturation, percentage float32)
    • ColorspaceLinearToSRGB()
    • ColorspaceSRGBToLinear()
    • Contrast(percentage float32)
    • Convolution(kernel []float32, normalize, alpha, abs bool, delta float32)
    • Gamma(gamma float32)
    • GaussianBlur(sigma float32)
    • Grayscale()
    • Hue(shift float32)
    • Invert()
    • Maximum(ksize int, disk bool)
    • Mean(ksize int, disk bool)
    • Median(ksize int, disk bool)
    • Minimum(ksize int, disk bool)
    • Pixelate(size int)
    • Saturation(percentage float32)
    • Sepia(percentage float32)
    • Sigmoid(midpoint, factor float32)
    • Sobel()
    • Threshold(percentage float32)
    • UnsharpMask(sigma, amount, threshold float32)

FILTER EXAMPLES

The original image:

Resulting images after applying some of the filters:

name / result name / result name / result name / result
resize crop_to_size rotate_180 rotate_30
brightness_increase brightness_decrease contrast_increase contrast_decrease
saturation_increase saturation_decrease gamma_1.5 gamma_0.5
gaussian_blur unsharp_mask sigmoid pixelate
colorize grayscale sepia invert
mean median minimum maximum
hue_rotate color_balance color_func convolution_emboss

Here's the code that produces the above images:

package main

import (
	"image"
	"image/color"
	"image/png"
	"log"
	"os"

	"github.com/disintegration/gift"
)

func main() {
	src := loadImage("testdata/src.png")

	filters := map[string]gift.Filter{
		"resize":               gift.Resize(100, 0, gift.LanczosResampling),
		"crop_to_size":         gift.CropToSize(100, 100, gift.LeftAnchor),
		"rotate_180":           gift.Rotate180(),
		"rotate_30":            gift.Rotate(30, color.Transparent, gift.CubicInterpolation),
		"brightness_increase":  gift.Brightness(30),
		"brightness_decrease":  gift.Brightness(-30),
		"contrast_increase":    gift.Contrast(30),
		"contrast_decrease":    gift.Contrast(-30),
		"saturation_increase":  gift.Saturation(50),
		"saturation_decrease":  gift.Saturation(-50),
		"gamma_1.5":            gift.Gamma(1.5),
		"gamma_0.5":            gift.Gamma(0.5),
		"gaussian_blur":        gift.GaussianBlur(1),
		"unsharp_mask":         gift.UnsharpMask(1, 1, 0),
		"sigmoid":              gift.Sigmoid(0.5, 7),
		"pixelate":             gift.Pixelate(5),
		"colorize":             gift.Colorize(240, 50, 100),
		"grayscale":            gift.Grayscale(),
		"sepia":                gift.Sepia(100),
		"invert":               gift.Invert(),
		"mean":                 gift.Mean(5, true),
		"median":               gift.Median(5, true),
		"minimum":              gift.Minimum(5, true),
		"maximum":              gift.Maximum(5, true),
		"hue_rotate":           gift.Hue(45),
		"color_balance":        gift.ColorBalance(10, -10, -10),
		"color_func": gift.ColorFunc(
			func(r0, g0, b0, a0 float32) (r, g, b, a float32) {
				r = 1 - r0   // invert the red channel
				g = g0 + 0.1 // shift the green channel by 0.1
				b = 0        // set the blue channel to 0
				a = a0       // preserve the alpha channel
				return r, g, b, a
			},
		),
		"convolution_emboss": gift.Convolution(
			[]float32{
				-1, -1, 0,
				-1, 1, 1,
				0, 1, 1,
			},
			false, false, false, 0.0,
		),
	}

	for name, filter := range filters {
		g := gift.New(filter)
		dst := image.NewNRGBA(g.Bounds(src.Bounds()))
		g.Draw(dst, src)
		saveImage("testdata/dst_"+name+".png", dst)
	}
}

func loadImage(filename string) image.Image {
	f, err := os.Open(filename)
	if err != nil {
		log.Fatalf("os.Open failed: %v", err)
	}
	img, _, err := image.Decode(f)
	if err != nil {
		log.Fatalf("image.Decode failed: %v", err)
	}
	return img
}

func saveImage(filename string, img image.Image) {
	f, err := os.Create(filename)
	if err != nil {
		log.Fatalf("os.Create failed: %v", err)
	}
	err = png.Encode(f, img)
	if err != nil {
		log.Fatalf("png.Encode failed: %v", err)
	}
}

gift's People

Contributors

disintegration avatar nixterrimus avatar

Watchers

James Cloos avatar  avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.