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A collection of parallel image processing algorithms in pure Go

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bild

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MIT License GoDoc Build Status Go Report Card

A collection of parallel image processing algorithms in pure Go.

The aim of this project is simplicity in use and development over high performance, but most algorithms are designed to be efficient and make use of parallelism when available. It is based on standard Go packages to reduce dependency use and development abstractions.

Notice: This package is under heavy development and the API might change at any time until a 1.0 version is reached.

Documentation

http://godoc.org/github.com/anthonynsimon/bild

Install

bild requires Go version 1.4 or greater.

go get -u github.com/anthonynsimon/bild/...

Notice the '...' at the end, this is to signify that you want all the packages on the repo. In your code, simply import the specific package that you want to use (see example below).

Basic example:

package main

import (
	"github.com/anthonynsimon/bild/effect"
	"github.com/anthonynsimon/bild/imgio"
	"github.com/anthonynsimon/bild/transform"
)

func main() {
	img, err := imgio.Open("filename.jpg")
	if err != nil {
		panic(err)
	}

	inverted := effect.Invert(img)
	resized := transform.Resize(inverted, 800, 800, transform.Linear)
	rotated := transform.Rotate(resized, 45, nil)

	if err := imgio.Save("filename", rotated, imgio.PNG); err != nil {
		panic(err)
	}
}

Output examples

Adjustment

import "github.com/anthonynsimon/bild/adjust"

Brightness

result := adjust.Brightness(img, 0.25)

example

Contrast

result := adjust.Contrast(img, -0.5)

example

Gamma

result := adjust.Gamma(img, 2.2)

example

Hue

result := adjust.Hue(img, -42)

example

Saturation

result := adjust.Saturation(img, 0.5)

example

Blend modes

import "github.com/anthonynsimon/bild/blend"

result := blend.Multiply(bg, fg)
Add Color Burn Color Dodge
Darken Difference Divide
Exclusion Lighten Linear Burn
Linear Light Multiply Normal
Opacity Overlay Screen
Soft Light Subtract

Blur

import "github.com/anthonynsimon/bild/blur"

Box Blur

result := blur.Box(img, 3.0)

example

Gaussian Blur

result := blur.Gaussian(img, 3.0)

example

Channel

import "github.com/anthonynsimon/bild/channel"

Extract Channel

result := channel.Extract(img, channel.Alpha)

example

Effect

import "github.com/anthonynsimon/bild/effect"

Dilate

result := effect.Dilate(img, 3)

example

Edge Detection

result := effect.EdgeDetection(img, 1.0)

example

Emboss

result := effect.Emboss(img)

example

Erode

result := effect.Erode(img, 3)

example

Grayscale

result := effect.Grayscale(img)

example

Invert

result := effect.Invert(img)

example

Median

result := effect.Median(img, 10.0)

example

Sepia

result := effect.Sepia(img)

example

Sharpen

result := effect.Sharpen(img)

example

Sobel

result := effect.Sobel(img)

example

Unsharp Mask

result := effect.UnsharpMask(img, 0.6, 1.2)

example

Histogram

import "github.com/anthonynsimon/bild/histogram"

RGBA Histogram

hist := histogram.NewRGBAHistogram(img)
result := hist.Image()

example

Noise

import "github.com/anthonynsimon/bild/noise"

Uniform colored

result := noise.Generate(280, 280, &noise.Options{Monochrome: false, NoiseFn: noise.Uniform})

example

Binary monochrome

result := noise.Generate(280, 280, &noise.Options{Monochrome: true, NoiseFn: noise.Binary})

example

Gaussian monochrome

result := noise.Generate(280, 280, &noise.Options{Monochrome: true, NoiseFn: noise.Gaussian})

example

Paint

import "github.com/anthonynsimon/bild/paint"

Flood Fill

// Fuzz is the percentage of maximum color distance that is tolerated
result := paint.FloodFill(img, image.Point{240, 0}, color.RGBA{255, 0, 0, 255}, 15)

example

Segmentation

import "github.com/anthonynsimon/bild/segment"

Threshold

result := segment.Threshold(img, 128)

example

Transform

import "github.com/anthonynsimon/bild/transform"

Crop

// Source image is 280x280
result := transform.Crop(img, image.Rect(70,70,210,210))

example

FlipH

result := transform.FlipH(img)

example

FlipV

result := transform.FlipV(img)

example

Resize Resampling Filters

result := transform.Resize(img, 280, 280, transform.Linear)
Nearest Neighbor Linear Gaussian
Mitchell Netravali Catmull Rom Lanczos

Rotate

// Options set to nil will use defaults (ResizeBounds set to false, Pivot at center)
result := transform.Rotate(img, -45.0, nil)

example

// If ResizeBounds is set to true, the full rotation bounding area is used
result := transform.Rotate(img, -45.0, &transform.RotationOptions{ResizeBounds: true})

example

// Pivot coordinates are set from the top-left corner
// Notice ResizeBounds being set to default (false)
result := transform.Rotate(img, -45.0, &transform.RotationOptions{Pivot: &image.Point{0, 0}})

example

Shear Horizontal

result := transform.ShearH(img, 30)

example

Shear Vertical

result := transform.ShearV(img, 30)

example

Translate

result := transform.Translate(img, 80, 0)

example

License

This project is licensed under the MIT license. Please read the LICENSE file.

Contribute

Want to hack on the project? Any kind of contribution is welcome!
Simply follow the next steps:

  • Fork the project.
  • Create a new branch.
  • Make your changes and write tests when practical.
  • Commit your changes to the new branch.
  • Send a pull request, it will be reviewed shortly.

In case you want to add a feature, please create a new issue and briefly explain what the feature would consist of. For bugs or requests, before creating an issue please check if one has already been created for it.

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