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
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)
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/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)
Gaussian Blur
result := blur.Gaussian(img, 3.0)
Channel
import "github.com/anthonynsimon/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/anthonynsimon/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/anthonynsimon/bild/histogram"
RGBA Histogram
hist := histogram.NewRGBAHistogram(img)
result := hist.Image()
Noise
import "github.com/anthonynsimon/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/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)
Segmentation
import "github.com/anthonynsimon/bild/segment"
Threshold
result := segment.Threshold(img, 128)
Transform
import "github.com/anthonynsimon/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.