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https://github.com/superseriousbusiness/gotosocial.git
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91c8d5d20d
* use disintegration/imaging instead of nfnt/resize * update tests * use disintegration lib for thumbing (if necessary)
52 lines
1.1 KiB
Go
52 lines
1.1 KiB
Go
package imaging
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import (
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"image"
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"sync"
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)
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// Histogram returns a normalized histogram of an image.
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//
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// Resulting histogram is represented as an array of 256 floats, where
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// histogram[i] is a probability of a pixel being of a particular luminance i.
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func Histogram(img image.Image) [256]float64 {
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var mu sync.Mutex
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var histogram [256]float64
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var total float64
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src := newScanner(img)
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if src.w == 0 || src.h == 0 {
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return histogram
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}
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parallel(0, src.h, func(ys <-chan int) {
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var tmpHistogram [256]float64
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var tmpTotal float64
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scanLine := make([]uint8, src.w*4)
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for y := range ys {
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src.scan(0, y, src.w, y+1, scanLine)
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i := 0
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for x := 0; x < src.w; x++ {
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s := scanLine[i : i+3 : i+3]
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r := s[0]
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g := s[1]
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b := s[2]
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y := 0.299*float32(r) + 0.587*float32(g) + 0.114*float32(b)
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tmpHistogram[int(y+0.5)]++
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tmpTotal++
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i += 4
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}
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}
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mu.Lock()
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for i := 0; i < 256; i++ {
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histogram[i] += tmpHistogram[i]
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}
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total += tmpTotal
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mu.Unlock()
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})
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for i := 0; i < 256; i++ {
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histogram[i] = histogram[i] / total
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}
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return histogram
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}
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