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kernel_examples_test.go
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267 lines (215 loc) · 5.83 KB
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package convolver_test
import (
"github.com/mandykoh/convolver"
"image/png"
"log"
"os"
"path"
"runtime"
"time"
)
func ExampleKernel_channelExtraction() {
imgFile, err := os.Open("test-images/avocado.png")
if err != nil {
log.Panicf("Error opening input image: %v", err)
}
defer imgFile.Close()
img, err := png.Decode(imgFile)
if err != nil {
log.Panicf("Error decoding PNG: %v", err)
}
kernel := convolver.KernelWithRadius(0)
kernel.SetWeightRGBA(0, 0, 0, 0, 1, 1)
startTime := time.Now()
result := kernel.ApplyAvg(img, runtime.NumCPU())
endTime := time.Now()
log.Printf("Channel extraction applied in %v", endTime.Sub(startTime))
_ = os.Mkdir("example-output", os.ModePerm)
outFilePath := path.Join("example-output", "example-channel-extraction.png")
outFile, err := os.Create(outFilePath)
if err != nil {
log.Panicf("Error creating output file: %v", err)
}
defer outFile.Close()
err = png.Encode(outFile, result)
if err != nil {
log.Panicf("Error encoding output image: %v", err)
}
err = outFile.Close()
if err != nil {
log.Panicf("Error closing output file: %v", err)
}
log.Printf("Output written to %s", outFilePath)
// Output:
}
func ExampleKernel_dilateErode() {
const numPasses = 5
imgFile, err := os.Open("test-images/convolver-alpha-1024.png")
if err != nil {
log.Panicf("Error opening input image: %v", err)
}
defer imgFile.Close()
img, err := png.Decode(imgFile)
if err != nil {
log.Panicf("Error decoding PNG: %v", err)
}
weights := []float32{
0, 1, 1, 1, 0,
1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
0, 1, 1, 1, 0,
}
kernel := convolver.KernelWithRadius(2)
kernel.SetWeightsUniform(weights)
startTime := time.Now()
result := img
for i := 0; i < numPasses; i++ {
result = kernel.ApplyMax(result, runtime.NumCPU())
}
for i := 0; i < numPasses; i++ {
result = kernel.ApplyMin(result, runtime.NumCPU())
}
endTime := time.Now()
log.Printf("Dilate-erode applied in %v", endTime.Sub(startTime))
_ = os.Mkdir("example-output", os.ModePerm)
outFilePath := path.Join("example-output", "example-dilate-erode.png")
outFile, err := os.Create(outFilePath)
if err != nil {
log.Panicf("Error creating output file: %v", err)
}
defer outFile.Close()
err = png.Encode(outFile, result)
if err != nil {
log.Panicf("Error encoding output image: %v", err)
}
err = outFile.Close()
if err != nil {
log.Panicf("Error closing output file: %v", err)
}
log.Printf("Output written to %s", outFilePath)
// Output:
}
func ExampleKernel_edgeDetect() {
imgFile, err := os.Open("test-images/avocado.png")
if err != nil {
log.Panicf("Error opening input image: %v", err)
}
defer imgFile.Close()
img, err := png.Decode(imgFile)
if err != nil {
log.Panicf("Error decoding PNG: %v", err)
}
weights := []float32{
-1, -1, -1,
-1, 8, -1,
-1, -1, -1,
}
kernel := convolver.KernelWithRadius(1)
kernel.SetWeightsUniform(weights)
startTime := time.Now()
result := kernel.ApplyAvg(img, runtime.NumCPU())
endTime := time.Now()
log.Printf("Edge detection applied in %v", endTime.Sub(startTime))
_ = os.Mkdir("example-output", os.ModePerm)
outFilePath := path.Join("example-output", "example-edge-detect.png")
outFile, err := os.Create(outFilePath)
if err != nil {
log.Panicf("Error creating output file: %v", err)
}
defer outFile.Close()
err = png.Encode(outFile, result)
if err != nil {
log.Panicf("Error encoding output image: %v", err)
}
err = outFile.Close()
if err != nil {
log.Panicf("Error closing output file: %v", err)
}
log.Printf("Output written to %s", outFilePath)
// Output:
}
func ExampleKernel_gaussianBlur() {
const numPasses = 8
imgFile, err := os.Open("test-images/avocado.png")
if err != nil {
log.Panicf("Error opening input image: %v", err)
}
defer imgFile.Close()
img, err := png.Decode(imgFile)
if err != nil {
log.Panicf("Error decoding PNG: %v", err)
}
weights := []float32{
1, 4, 6, 4, 1,
4, 16, 24, 16, 4,
6, 24, 36, 24, 6,
4, 16, 24, 16, 4,
1, 4, 6, 4, 1,
}
kernel := convolver.KernelWithRadius(2)
kernel.SetWeightsUniform(weights)
startTime := time.Now()
result := img
for i := 0; i < numPasses; i++ {
result = kernel.ApplyAvg(result, runtime.NumCPU())
}
endTime := time.Now()
log.Printf("Gaussian blur applied in %v", endTime.Sub(startTime))
_ = os.Mkdir("example-output", os.ModePerm)
outFilePath := path.Join("example-output", "example-gaussian-blur.png")
outFile, err := os.Create(outFilePath)
if err != nil {
log.Panicf("Error creating output file: %v", err)
}
defer outFile.Close()
err = png.Encode(outFile, result)
if err != nil {
log.Panicf("Error encoding output image: %v", err)
}
err = outFile.Close()
if err != nil {
log.Panicf("Error closing output file: %v", err)
}
log.Printf("Output written to %s", outFilePath)
// Output:
}
func ExampleKernel_sharpen() {
imgFile, err := os.Open("test-images/avocado.png")
if err != nil {
log.Panicf("Error opening input image: %v", err)
}
defer imgFile.Close()
img, err := png.Decode(imgFile)
if err != nil {
log.Panicf("Error decoding PNG: %v", err)
}
weights := []float32{
0, -1, 0,
-1, 5, -1,
0, -1, 0,
}
kernel := convolver.KernelWithRadius(1)
kernel.SetWeightsUniform(weights)
startTime := time.Now()
result := kernel.ApplyAvg(img, runtime.NumCPU())
endTime := time.Now()
log.Printf("Sharpen applied in %v", endTime.Sub(startTime))
_ = os.Mkdir("example-output", os.ModePerm)
outFilePath := path.Join("example-output", "example-sharpen.png")
outFile, err := os.Create(outFilePath)
if err != nil {
log.Panicf("Error creating output file: %v", err)
}
defer outFile.Close()
err = png.Encode(outFile, result)
if err != nil {
log.Panicf("Error encoding output image: %v", err)
}
err = outFile.Close()
if err != nil {
log.Panicf("Error closing output file: %v", err)
}
log.Printf("Output written to %s", outFilePath)
// Output:
}