gogh

gogh

image processing package write in go for Computer Vision (like OpenCV)

##How To Install/Update?

go get -u github.com/ironpark/gogh

##How To Use?

Simple Examples

Binarization/Histogram

import (
	"fmt"
	"github.com/ironpark/gogh"
)


func main() {
	src := gogh.Load("some.jpg")
	//method chaining pattern!
	fmt.Println("histogram",src.Histogram().Array()) //Nomal histogram
	fmt.Println("histogram",src.Histogram().Cumulative()) //Cumulative histogram
	
	//Binarization
	src.Binarization(50, false).Save("Binarization.png")
}

Pixel Get/Set

import (
	"fmt"
	"github.com/ironpark/gogh"
)


func main() {
		src := gogh.Load("some.jpg")
		//src.At(x,y).Set(r,g,b)
		src.At(1,2).Set(0,0,0)
		
		fmt.Println(src.At(1,2).Gray())
		fmt.Println(src.At(1,2).RGBA())
}

Pixel Loop

if you want loop all pixels you can use double for loop

	src := gogh.Load("some.jpg")
	bounds := src.Bounds()
	for x := bounds.Min.X; x < bounds.Max.X; x++ {
		for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
			fmt.Println(c.At(x, y).Gray()
		}
	}

it is same fuction more than simple

	src.Loop(func(x, y int) {
		fmt.Println(src.At(x, y).Gray())
	})

Blur

import (
	"fmt"
	"github.com/ironpark/gogh"
)

func main() {
	img := gogh.Load("some.jpg")
	img.Blur(3, gogh.BLUR_BOX).Filter(sobel).Save("5.png")
}

Convolution Filter

import (
	"fmt"
	"github.com/ironpark/gogh"
	"github.com/ironpark/gogh/mask"
)
var (
	sobel = [][]float32{
		{-1, 0, 1},
		{-2, 0, 2},
		{-1, 0, 1},
	}
)

func main() {
	img := gogh.Load("some.jpg")
	
	img.Filter(sobel).Save("Sobel1.png")
	//same code
	img.Filter(mask.SobelMask3x3X).Save("Sobel2.png")
	
	//Box Blur
	img.Filter(mask.GenBoxBlurMask(3)).Save("BoxBlur1.png")
	//or
	img.Blur(3, gogh.BLUR_BOX).Save("BoxBlur2.png")
	
}