| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614 | /*Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com>Permission to use, copy, modify, and/or distribute this software for any purposewith or without fee is hereby granted, provided that the above copyright noticeand this permission notice appear in all copies.THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITHREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY ANDFITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSSOF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHERTORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OFTHIS SOFTWARE.*/// Package resize implements various image resizing methods.//// The package works with the Image interface described in the image package.// Various interpolation methods are provided and multiple processors may be// utilized in the computations.//// Example://     imgResized := resize.Resize(1000, 0, imgOld, resize.MitchellNetravali)package resizeimport (	"image"	"runtime"	"sync")// An InterpolationFunction provides the parameters that describe an// interpolation kernel. It returns the number of samples to take// and the kernel function to use for sampling.type InterpolationFunction int// InterpolationFunction constantsconst (	// Nearest-neighbor interpolation	NearestNeighbor InterpolationFunction = iota	// Bilinear interpolation	Bilinear	// Bicubic interpolation (with cubic hermite spline)	Bicubic	// Mitchell-Netravali interpolation	MitchellNetravali	// Lanczos interpolation (a=2)	Lanczos2	// Lanczos interpolation (a=3)	Lanczos3)// kernal, returns an InterpolationFunctions taps and kernel.func (i InterpolationFunction) kernel() (int, func(float64) float64) {	switch i {	case Bilinear:		return 2, linear	case Bicubic:		return 4, cubic	case MitchellNetravali:		return 4, mitchellnetravali	case Lanczos2:		return 4, lanczos2	case Lanczos3:		return 6, lanczos3	default:		// Default to NearestNeighbor.		return 2, nearest	}}// values <1 will sharpen the imagevar blur = 1.0// Resize scales an image to new width and height using the interpolation function interp.// A new image with the given dimensions will be returned.// If one of the parameters width or height is set to 0, its size will be calculated so that// the aspect ratio is that of the originating image.// The resizing algorithm uses channels for parallel computation.func Resize(width, height uint, img image.Image, interp InterpolationFunction) image.Image {	scaleX, scaleY := calcFactors(width, height, float64(img.Bounds().Dx()), float64(img.Bounds().Dy()))	if width == 0 {		width = uint(0.7 + float64(img.Bounds().Dx())/scaleX)	}	if height == 0 {		height = uint(0.7 + float64(img.Bounds().Dy())/scaleY)	}	// Trivial case: return input image	if int(width) == img.Bounds().Dx() && int(height) == img.Bounds().Dy() {		return img	}	if interp == NearestNeighbor {		return resizeNearest(width, height, scaleX, scaleY, img, interp)	}	taps, kernel := interp.kernel()	cpus := runtime.GOMAXPROCS(0)	wg := sync.WaitGroup{}	// Generic access to image.Image is slow in tight loops.	// The optimal access has to be determined from the concrete image type.	switch input := img.(type) {	case *image.RGBA:		// 8-bit precision		temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA)			go func() {				defer wg.Done()				resizeRGBA(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA)			go func() {				defer wg.Done()				resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.NRGBA:		// 8-bit precision		temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA)			go func() {				defer wg.Done()				resizeNRGBA(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA)			go func() {				defer wg.Done()				resizeRGBA(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.YCbCr:		// 8-bit precision		// accessing the YCbCr arrays in a tight loop is slow.		// converting the image to ycc increases performance by 2x.		temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)		result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)		coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		in := imageYCbCrToYCC(input)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*ycc)			go func() {				defer wg.Done()				resizeYCbCr(in, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*ycc)			go func() {				defer wg.Done()				resizeYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result.YCbCr()	case *image.RGBA64:		// 16-bit precision		temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				resizeRGBA64(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.NRGBA64:		// 16-bit precision		temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				resizeNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.Gray:		// 8-bit precision		temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewGray(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.Gray)			go func() {				defer wg.Done()				resizeGray(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeights8(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.Gray)			go func() {				defer wg.Done()				resizeGray(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.Gray16:		// 16-bit precision		temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.Gray16)			go func() {				defer wg.Done()				resizeGray16(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.Gray16)			go func() {				defer wg.Done()				resizeGray16(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	default:		// 16-bit precision		temp := image.NewRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))		result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				resizeGeneric(img, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeights16(result.Bounds().Dy(), taps, blur, scaleY, kernel)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				resizeRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	}}func resizeNearest(width, height uint, scaleX, scaleY float64, img image.Image, interp InterpolationFunction) image.Image {	taps, _ := interp.kernel()	cpus := runtime.GOMAXPROCS(0)	wg := sync.WaitGroup{}	switch input := img.(type) {	case *image.RGBA:		// 8-bit precision		temp := image.NewRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewRGBA(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA)			go func() {				defer wg.Done()				nearestRGBA(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA)			go func() {				defer wg.Done()				nearestRGBA(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.NRGBA:		// 8-bit precision		temp := image.NewNRGBA(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewNRGBA(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.NRGBA)			go func() {				defer wg.Done()				nearestNRGBA(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.NRGBA)			go func() {				defer wg.Done()				nearestNRGBA(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.YCbCr:		// 8-bit precision		// accessing the YCbCr arrays in a tight loop is slow.		// converting the image to ycc increases performance by 2x.		temp := newYCC(image.Rect(0, 0, input.Bounds().Dy(), int(width)), input.SubsampleRatio)		result := newYCC(image.Rect(0, 0, int(width), int(height)), image.YCbCrSubsampleRatio444)		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		in := imageYCbCrToYCC(input)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*ycc)			go func() {				defer wg.Done()				nearestYCbCr(in, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*ycc)			go func() {				defer wg.Done()				nearestYCbCr(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result.YCbCr()	case *image.RGBA64:		// 16-bit precision		temp := image.NewRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				nearestRGBA64(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.NRGBA64:		// 16-bit precision		temp := image.NewNRGBA64(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewNRGBA64(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.NRGBA64)			go func() {				defer wg.Done()				nearestNRGBA64(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.NRGBA64)			go func() {				defer wg.Done()				nearestNRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.Gray:		// 8-bit precision		temp := image.NewGray(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewGray(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.Gray)			go func() {				defer wg.Done()				nearestGray(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.Gray)			go func() {				defer wg.Done()				nearestGray(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	case *image.Gray16:		// 16-bit precision		temp := image.NewGray16(image.Rect(0, 0, input.Bounds().Dy(), int(width)))		result := image.NewGray16(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.Gray16)			go func() {				defer wg.Done()				nearestGray16(input, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.Gray16)			go func() {				defer wg.Done()				nearestGray16(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	default:		// 16-bit precision		temp := image.NewRGBA64(image.Rect(0, 0, img.Bounds().Dy(), int(width)))		result := image.NewRGBA64(image.Rect(0, 0, int(width), int(height)))		// horizontal filter, results in transposed temporary image		coeffs, offset, filterLength := createWeightsNearest(temp.Bounds().Dy(), taps, blur, scaleX)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(temp, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				nearestGeneric(img, slice, scaleX, coeffs, offset, filterLength)			}()		}		wg.Wait()		// horizontal filter on transposed image, result is not transposed		coeffs, offset, filterLength = createWeightsNearest(result.Bounds().Dy(), taps, blur, scaleY)		wg.Add(cpus)		for i := 0; i < cpus; i++ {			slice := makeSlice(result, i, cpus).(*image.RGBA64)			go func() {				defer wg.Done()				nearestRGBA64(temp, slice, scaleY, coeffs, offset, filterLength)			}()		}		wg.Wait()		return result	}}// Calculates scaling factors using old and new image dimensions.func calcFactors(width, height uint, oldWidth, oldHeight float64) (scaleX, scaleY float64) {	if width == 0 {		if height == 0 {			scaleX = 1.0			scaleY = 1.0		} else {			scaleY = oldHeight / float64(height)			scaleX = scaleY		}	} else {		scaleX = oldWidth / float64(width)		if height == 0 {			scaleY = scaleX		} else {			scaleY = oldHeight / float64(height)		}	}	return}type imageWithSubImage interface {	image.Image	SubImage(image.Rectangle) image.Image}func makeSlice(img imageWithSubImage, i, n int) image.Image {	return img.SubImage(image.Rect(img.Bounds().Min.X, img.Bounds().Min.Y+i*img.Bounds().Dy()/n, img.Bounds().Max.X, img.Bounds().Min.Y+(i+1)*img.Bounds().Dy()/n))}
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