bild

All credits goes to the original repository at https://github.com/anthonynsimon/bild.

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

The documentation for the various packages is available here.

CLI usage

Download and compile from sources:

go get github.com/speedata/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/speedata/bild/...

Basic package usage example:

package main

import (
    "github.com/speedata/bild/effect"
    "github.com/speedata/bild/imgio"
    "github.com/speedata/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/speedata/bild/adjust"

Brightness

result := adjust.Brightness(img, 0.25)

Contrast

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

Gamma

result := adjust.Gamma(img, 2.2)

Hue

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

Saturation

result := adjust.Saturation(img, 0.5)

Blend modes

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

Box Blur

result := blur.Box(img, 3.0)

Gaussian Blur

result := blur.Gaussian(img, 3.0)

Channel

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

Extract Channels

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

Extract Multiple Channels

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

Effect

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

Dilate

result := effect.Dilate(img, 3)

Edge Detection

result := effect.EdgeDetection(img, 1.0)

Emboss

result := effect.Emboss(img)

Erode

result := effect.Erode(img, 3)

Grayscale

result := effect.Grayscale(img)

Invert

result := effect.Invert(img)

Median

result := effect.Median(img, 10.0)

Sepia

result := effect.Sepia(img)

Sharpen

result := effect.Sharpen(img)

Sobel

result := effect.Sobel(img)

Unsharp Mask

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

Histogram

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

RGBA Histogram

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

Noise

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

Uniform colored

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

Binary monochrome

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

Gaussian monochrome

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

Perlin Noise

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

Paint

import "github.com/speedata/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)

Segmentation

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

Threshold

result := segment.Threshold(img, 128)

Transform

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

Crop

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

FlipH

result := transform.FlipH(img)

FlipV

result := transform.FlipV(img)

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)

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

// 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}})

Shear Horizontal

result := transform.ShearH(img, 30)

Shear Vertical

result := transform.ShearV(img, 30)

Translate

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

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.