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A collection of parallel image processing algorithms in pure Go
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README.md

bild

bild logo

MIT License GoDoc CircleCI 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 absolute high performance, but most algorithms are designed to be efficient and make use of parallelism when available.

It uses packages from the standard library whenever possible to reduce dependency use and development abstractions.

All operations return image types from the standard library.

Documentation

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

CLI usage

Download and compile from sources:

go get github.com/anthonynsimon/bild

Or get the pre-compiled binaries for your platform on the releases page

bild

A collection of parallel image processing algorithms in pure Go

Usage:
  bild [command]

Available Commands:
  adjust      adjust basic image features like brightness or contrast
  blend       blend two images together
  blur        blur an image using the specified method
  channel     channel operations on images
  effect      apply effects on images
  help        Help about any command
  histogram   histogram operations on images
  imgio       i/o operations on images
  noise       noise generators
  segment     segment an image using the specified method

Flags:
  -h, --help      help for bild
      --version   version for bild

Use "bild [command] --help" for more information about a command.

For example, to apply a median effect with a radius of 1.5 on the image input.png, writing the result into a new file called output.png:

bild effect median --radius 1.5 input.png output.png

Install package

bild requires Go version 1.11 or greater.

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

Basic package usage 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("input.jpg")
    if err != nil {
        fmt.Println(err)
        return
    }

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

    if err := imgio.Save("output.png", rotated, imgio.PNGEncoder()); err != nil {
        fmt.Println(err)
        return
    }
}

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 Channels

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

example

Extract Multiple Channels

result := channel.ExtractMultiple(img, channel.Red, channel.Alpha)

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

Perlin Noise

result := noise.GeneratePerlin(280, 280, 0.25)

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

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.

Changelog

Please see the changelog for more details.

License

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

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