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Diffstat (limited to 'Godeps/_workspace/src/github.com/nfnt/resize/resize.go')
| -rw-r--r-- | Godeps/_workspace/src/github.com/nfnt/resize/resize.go | 614 |
1 files changed, 614 insertions, 0 deletions
diff --git a/Godeps/_workspace/src/github.com/nfnt/resize/resize.go b/Godeps/_workspace/src/github.com/nfnt/resize/resize.go new file mode 100644 index 000000000..4d4ff6e3e --- /dev/null +++ b/Godeps/_workspace/src/github.com/nfnt/resize/resize.go @@ -0,0 +1,614 @@ +/* +Copyright (c) 2012, Jan Schlicht <jan.schlicht@gmail.com> + +Permission to use, copy, modify, and/or distribute this software for any purpose +with or without fee is hereby granted, provided that the above copyright notice +and this permission notice appear in all copies. + +THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH +REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND +FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, +INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS +OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER +TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF +THIS 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 resize + +import ( + "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 constants +const ( + // 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 image +var 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.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 := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel) + wg.Add(cpus) + for i := 0; i < cpus; i++ { + slice := makeSlice(temp, i, cpus).(*image.NRGBA) + 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.NRGBA) + go func() { + defer wg.Done() + resizeNRGBA(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 := createWeights8(temp.Bounds().Dy(), taps, blur, scaleX, kernel) + wg.Add(cpus) + for i := 0; i < cpus; i++ { + slice := makeSlice(temp, i, cpus).(*image.NRGBA) + 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.NRGBA) + go func() { + defer wg.Done() + resizeNRGBA(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)), input.SubsampleRatio) + + 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.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 := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel) + wg.Add(cpus) + for i := 0; i < cpus; i++ { + slice := makeSlice(temp, i, cpus).(*image.NRGBA64) + 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.NRGBA64) + go func() { + defer wg.Done() + resizeNRGBA64(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 := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel) + wg.Add(cpus) + for i := 0; i < cpus; i++ { + slice := makeSlice(temp, i, cpus).(*image.NRGBA64) + 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.NRGBA64) + go func() { + defer wg.Done() + resizeNRGBA64(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.NewNRGBA64(image.Rect(0, 0, img.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 := createWeights16(temp.Bounds().Dy(), taps, blur, scaleX, kernel) + wg.Add(cpus) + for i := 0; i < cpus; i++ { + slice := makeSlice(temp, i, cpus).(*image.NRGBA64) + 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.NRGBA64) + go func() { + defer wg.Done() + resizeNRGBA64(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)), input.SubsampleRatio) + + 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)) +} |