diff options
Diffstat (limited to 'Godeps/_workspace/src/github.com/disintegration/imaging/resize.go')
| -rw-r--r-- | Godeps/_workspace/src/github.com/disintegration/imaging/resize.go | 583 |
1 files changed, 0 insertions, 583 deletions
diff --git a/Godeps/_workspace/src/github.com/disintegration/imaging/resize.go b/Godeps/_workspace/src/github.com/disintegration/imaging/resize.go deleted file mode 100644 index 3c792e904..000000000 --- a/Godeps/_workspace/src/github.com/disintegration/imaging/resize.go +++ /dev/null @@ -1,583 +0,0 @@ -package imaging - -import ( - "image" - "math" -) - -type iwpair struct { - i int - w int32 -} - -type pweights struct { - iwpairs []iwpair - wsum int32 -} - -func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights { - du := float64(srcSize) / float64(dstSize) - scale := du - if scale < 1.0 { - scale = 1.0 - } - ru := math.Ceil(scale * filter.Support) - - out := make([]pweights, dstSize) - - for v := 0; v < dstSize; v++ { - fu := (float64(v)+0.5)*du - 0.5 - - startu := int(math.Ceil(fu - ru)) - if startu < 0 { - startu = 0 - } - endu := int(math.Floor(fu + ru)) - if endu > srcSize-1 { - endu = srcSize - 1 - } - - wsum := int32(0) - for u := startu; u <= endu; u++ { - w := int32(0xff * filter.Kernel((float64(u)-fu)/scale)) - if w != 0 { - wsum += w - out[v].iwpairs = append(out[v].iwpairs, iwpair{u, w}) - } - } - out[v].wsum = wsum - } - - return out -} - -// Resize resizes the image to the specified width and height using the specified resampling -// filter and returns the transformed image. If one of width or height is 0, the image aspect -// ratio is preserved. -// -// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, -// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. -// -// Usage example: -// -// dstImage := imaging.Resize(srcImage, 800, 600, imaging.Lanczos) -// -func Resize(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA { - dstW, dstH := width, height - - if dstW < 0 || dstH < 0 { - return &image.NRGBA{} - } - if dstW == 0 && dstH == 0 { - return &image.NRGBA{} - } - - src := toNRGBA(img) - - srcW := src.Bounds().Max.X - srcH := src.Bounds().Max.Y - - if srcW <= 0 || srcH <= 0 { - return &image.NRGBA{} - } - - // if new width or height is 0 then preserve aspect ratio, minimum 1px - if dstW == 0 { - tmpW := float64(dstH) * float64(srcW) / float64(srcH) - dstW = int(math.Max(1.0, math.Floor(tmpW+0.5))) - } - if dstH == 0 { - tmpH := float64(dstW) * float64(srcH) / float64(srcW) - dstH = int(math.Max(1.0, math.Floor(tmpH+0.5))) - } - - var dst *image.NRGBA - - if filter.Support <= 0.0 { - // nearest-neighbor special case - dst = resizeNearest(src, dstW, dstH) - - } else { - // two-pass resize - if srcW != dstW { - dst = resizeHorizontal(src, dstW, filter) - } else { - dst = src - } - - if srcH != dstH { - dst = resizeVertical(dst, dstH, filter) - } - } - - return dst -} - -func resizeHorizontal(src *image.NRGBA, width int, filter ResampleFilter) *image.NRGBA { - srcBounds := src.Bounds() - srcW := srcBounds.Max.X - srcH := srcBounds.Max.Y - - dstW := width - dstH := srcH - - dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH)) - - weights := precomputeWeights(dstW, srcW, filter) - - parallel(dstH, func(partStart, partEnd int) { - for dstY := partStart; dstY < partEnd; dstY++ { - for dstX := 0; dstX < dstW; dstX++ { - var c [4]int32 - for _, iw := range weights[dstX].iwpairs { - i := dstY*src.Stride + iw.i*4 - c[0] += int32(src.Pix[i+0]) * iw.w - c[1] += int32(src.Pix[i+1]) * iw.w - c[2] += int32(src.Pix[i+2]) * iw.w - c[3] += int32(src.Pix[i+3]) * iw.w - } - j := dstY*dst.Stride + dstX*4 - sum := weights[dstX].wsum - dst.Pix[j+0] = clampint32(int32(float32(c[0])/float32(sum) + 0.5)) - dst.Pix[j+1] = clampint32(int32(float32(c[1])/float32(sum) + 0.5)) - dst.Pix[j+2] = clampint32(int32(float32(c[2])/float32(sum) + 0.5)) - dst.Pix[j+3] = clampint32(int32(float32(c[3])/float32(sum) + 0.5)) - } - } - }) - - return dst -} - -func resizeVertical(src *image.NRGBA, height int, filter ResampleFilter) *image.NRGBA { - srcBounds := src.Bounds() - srcW := srcBounds.Max.X - srcH := srcBounds.Max.Y - - dstW := srcW - dstH := height - - dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH)) - - weights := precomputeWeights(dstH, srcH, filter) - - parallel(dstW, func(partStart, partEnd int) { - - for dstX := partStart; dstX < partEnd; dstX++ { - for dstY := 0; dstY < dstH; dstY++ { - var c [4]int32 - for _, iw := range weights[dstY].iwpairs { - i := iw.i*src.Stride + dstX*4 - c[0] += int32(src.Pix[i+0]) * iw.w - c[1] += int32(src.Pix[i+1]) * iw.w - c[2] += int32(src.Pix[i+2]) * iw.w - c[3] += int32(src.Pix[i+3]) * iw.w - } - j := dstY*dst.Stride + dstX*4 - sum := weights[dstY].wsum - dst.Pix[j+0] = clampint32(int32(float32(c[0])/float32(sum) + 0.5)) - dst.Pix[j+1] = clampint32(int32(float32(c[1])/float32(sum) + 0.5)) - dst.Pix[j+2] = clampint32(int32(float32(c[2])/float32(sum) + 0.5)) - dst.Pix[j+3] = clampint32(int32(float32(c[3])/float32(sum) + 0.5)) - } - } - - }) - - return dst -} - -// fast nearest-neighbor resize, no filtering -func resizeNearest(src *image.NRGBA, width, height int) *image.NRGBA { - dstW, dstH := width, height - - srcBounds := src.Bounds() - srcW := srcBounds.Max.X - srcH := srcBounds.Max.Y - - dst := image.NewNRGBA(image.Rect(0, 0, dstW, dstH)) - - dx := float64(srcW) / float64(dstW) - dy := float64(srcH) / float64(dstH) - - parallel(dstH, func(partStart, partEnd int) { - - for dstY := partStart; dstY < partEnd; dstY++ { - fy := (float64(dstY)+0.5)*dy - 0.5 - - for dstX := 0; dstX < dstW; dstX++ { - fx := (float64(dstX)+0.5)*dx - 0.5 - - srcX := int(math.Min(math.Max(math.Floor(fx+0.5), 0.0), float64(srcW))) - srcY := int(math.Min(math.Max(math.Floor(fy+0.5), 0.0), float64(srcH))) - - srcOff := srcY*src.Stride + srcX*4 - dstOff := dstY*dst.Stride + dstX*4 - - copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4]) - } - } - - }) - - return dst -} - -// Fit scales down the image using the specified resample filter to fit the specified -// maximum width and height and returns the transformed image. -// -// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, -// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. -// -// Usage example: -// -// dstImage := imaging.Fit(srcImage, 800, 600, imaging.Lanczos) -// -func Fit(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA { - maxW, maxH := width, height - - if maxW <= 0 || maxH <= 0 { - return &image.NRGBA{} - } - - srcBounds := img.Bounds() - srcW := srcBounds.Dx() - srcH := srcBounds.Dy() - - if srcW <= 0 || srcH <= 0 { - return &image.NRGBA{} - } - - if srcW <= maxW && srcH <= maxH { - return Clone(img) - } - - srcAspectRatio := float64(srcW) / float64(srcH) - maxAspectRatio := float64(maxW) / float64(maxH) - - var newW, newH int - if srcAspectRatio > maxAspectRatio { - newW = maxW - newH = int(float64(newW) / srcAspectRatio) - } else { - newH = maxH - newW = int(float64(newH) * srcAspectRatio) - } - - return Resize(img, newW, newH, filter) -} - -// Fill scales the image to the smallest possible size that will cover the specified dimensions, -// crops the resized image to the specified dimensions using the given anchor point and returns -// the transformed image. -// -// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, -// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. -// -// Usage example: -// -// dstImage := imaging.Fill(srcImage, 800, 600, imaging.Center, imaging.Lanczos) -// -func Fill(img image.Image, width, height int, anchor Anchor, filter ResampleFilter) *image.NRGBA { - minW, minH := width, height - - if minW <= 0 || minH <= 0 { - return &image.NRGBA{} - } - - srcBounds := img.Bounds() - srcW := srcBounds.Dx() - srcH := srcBounds.Dy() - - if srcW <= 0 || srcH <= 0 { - return &image.NRGBA{} - } - - if srcW == minW && srcH == minH { - return Clone(img) - } - - srcAspectRatio := float64(srcW) / float64(srcH) - minAspectRatio := float64(minW) / float64(minH) - - var tmp *image.NRGBA - if srcAspectRatio < minAspectRatio { - tmp = Resize(img, minW, 0, filter) - } else { - tmp = Resize(img, 0, minH, filter) - } - - return CropAnchor(tmp, minW, minH, anchor) -} - -// Thumbnail scales the image up or down using the specified resample filter, crops it -// to the specified width and hight and returns the transformed image. -// -// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, -// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. -// -// Usage example: -// -// dstImage := imaging.Thumbnail(srcImage, 100, 100, imaging.Lanczos) -// -func Thumbnail(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA { - return Fill(img, width, height, Center, filter) -} - -// Resample filter struct. It can be used to make custom filters. -// -// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, -// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. -// -// General filter recommendations: -// -// - Lanczos -// Probably the best resampling filter for photographic images yielding sharp results, -// but it's slower than cubic filters (see below). -// -// - CatmullRom -// A sharp cubic filter. It's a good filter for both upscaling and downscaling if sharp results are needed. -// -// - MitchellNetravali -// A high quality cubic filter that produces smoother results with less ringing than CatmullRom. -// -// - BSpline -// A good filter if a very smooth output is needed. -// -// - Linear -// Bilinear interpolation filter, produces reasonably good, smooth output. It's faster than cubic filters. -// -// - Box -// Simple and fast resampling filter appropriate for downscaling. -// When upscaling it's similar to NearestNeighbor. -// -// - NearestNeighbor -// Fastest resample filter, no antialiasing at all. Rarely used. -// -type ResampleFilter struct { - Support float64 - Kernel func(float64) float64 -} - -// Nearest-neighbor filter, no anti-aliasing. -var NearestNeighbor ResampleFilter - -// Box filter (averaging pixels). -var Box ResampleFilter - -// Linear filter. -var Linear ResampleFilter - -// Hermite cubic spline filter (BC-spline; B=0; C=0). -var Hermite ResampleFilter - -// Mitchell-Netravali cubic filter (BC-spline; B=1/3; C=1/3). -var MitchellNetravali ResampleFilter - -// Catmull-Rom - sharp cubic filter (BC-spline; B=0; C=0.5). -var CatmullRom ResampleFilter - -// Cubic B-spline - smooth cubic filter (BC-spline; B=1; C=0). -var BSpline ResampleFilter - -// Gaussian Blurring Filter. -var Gaussian ResampleFilter - -// Bartlett-windowed sinc filter (3 lobes). -var Bartlett ResampleFilter - -// Lanczos filter (3 lobes). -var Lanczos ResampleFilter - -// Hann-windowed sinc filter (3 lobes). -var Hann ResampleFilter - -// Hamming-windowed sinc filter (3 lobes). -var Hamming ResampleFilter - -// Blackman-windowed sinc filter (3 lobes). -var Blackman ResampleFilter - -// Welch-windowed sinc filter (parabolic window, 3 lobes). -var Welch ResampleFilter - -// Cosine-windowed sinc filter (3 lobes). -var Cosine ResampleFilter - -func bcspline(x, b, c float64) float64 { - x = math.Abs(x) - if x < 1.0 { - return ((12-9*b-6*c)*x*x*x + (-18+12*b+6*c)*x*x + (6 - 2*b)) / 6 - } - if x < 2.0 { - return ((-b-6*c)*x*x*x + (6*b+30*c)*x*x + (-12*b-48*c)*x + (8*b + 24*c)) / 6 - } - return 0 -} - -func sinc(x float64) float64 { - if x == 0 { - return 1 - } - return math.Sin(math.Pi*x) / (math.Pi * x) -} - -func init() { - NearestNeighbor = ResampleFilter{ - Support: 0.0, // special case - not applying the filter - } - - Box = ResampleFilter{ - Support: 0.5, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x <= 0.5 { - return 1.0 - } - return 0 - }, - } - - Linear = ResampleFilter{ - Support: 1.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 1.0 { - return 1.0 - x - } - return 0 - }, - } - - Hermite = ResampleFilter{ - Support: 1.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 1.0 { - return bcspline(x, 0.0, 0.0) - } - return 0 - }, - } - - MitchellNetravali = ResampleFilter{ - Support: 2.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 2.0 { - return bcspline(x, 1.0/3.0, 1.0/3.0) - } - return 0 - }, - } - - CatmullRom = ResampleFilter{ - Support: 2.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 2.0 { - return bcspline(x, 0.0, 0.5) - } - return 0 - }, - } - - BSpline = ResampleFilter{ - Support: 2.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 2.0 { - return bcspline(x, 1.0, 0.0) - } - return 0 - }, - } - - Gaussian = ResampleFilter{ - Support: 2.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 2.0 { - return math.Exp(-2 * x * x) - } - return 0 - }, - } - - Bartlett = ResampleFilter{ - Support: 3.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 3.0 { - return sinc(x) * (3.0 - x) / 3.0 - } - return 0 - }, - } - - Lanczos = ResampleFilter{ - Support: 3.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 3.0 { - return sinc(x) * sinc(x/3.0) - } - return 0 - }, - } - - Hann = ResampleFilter{ - Support: 3.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 3.0 { - return sinc(x) * (0.5 + 0.5*math.Cos(math.Pi*x/3.0)) - } - return 0 - }, - } - - Hamming = ResampleFilter{ - Support: 3.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 3.0 { - return sinc(x) * (0.54 + 0.46*math.Cos(math.Pi*x/3.0)) - } - return 0 - }, - } - - Blackman = ResampleFilter{ - Support: 3.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 3.0 { - return sinc(x) * (0.42 - 0.5*math.Cos(math.Pi*x/3.0+math.Pi) + 0.08*math.Cos(2.0*math.Pi*x/3.0)) - } - return 0 - }, - } - - Welch = ResampleFilter{ - Support: 3.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 3.0 { - return sinc(x) * (1.0 - (x * x / 9.0)) - } - return 0 - }, - } - - Cosine = ResampleFilter{ - Support: 3.0, - Kernel: func(x float64) float64 { - x = math.Abs(x) - if x < 3.0 { - return sinc(x) * math.Cos((math.Pi/2.0)*(x/3.0)) - } - return 0 - }, - } -} |