Update vendor for next release (#1343)

1 files changed, 595 insertions, 0 deletions

diff --git a/vendor/github.com/disintegration/imaging/resize.go b/vendor/github.com/disintegration/imaging/resize.go
new file mode 100644
index 00000000..706435e3
--- /dev/null
+++ b/vendor/github.com/disintegration/imaging/resize.go
@@ -0,0 +1,595 @@
+package imaging
+
+import (
+	"image"
+	"math"
+)
+
+type indexWeight struct {
+	index  int
+	weight float64
+}
+
+func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) [][]indexWeight {
+	du := float64(srcSize) / float64(dstSize)
+	scale := du
+	if scale < 1.0 {
+		scale = 1.0
+	}
+	ru := math.Ceil(scale * filter.Support)
+
+	out := make([][]indexWeight, dstSize)
+	tmp := make([]indexWeight, 0, dstSize*int(ru+2)*2)
+
+	for v := 0; v < dstSize; v++ {
+		fu := (float64(v)+0.5)*du - 0.5
+
+		begin := int(math.Ceil(fu - ru))
+		if begin < 0 {
+			begin = 0
+		}
+		end := int(math.Floor(fu + ru))
+		if end > srcSize-1 {
+			end = srcSize - 1
+		}
+
+		var sum float64
+		for u := begin; u <= end; u++ {
+			w := filter.Kernel((float64(u) - fu) / scale)
+			if w != 0 {
+				sum += w
+				tmp = append(tmp, indexWeight{index: u, weight: w})
+			}
+		}
+		if sum != 0 {
+			for i := range tmp {
+				tmp[i].weight /= sum
+			}
+		}
+
+		out[v] = tmp
+		tmp = tmp[len(tmp):]
+	}
+
+	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.
+//
+// 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{}
+	}
+
+	srcW := img.Bounds().Dx()
+	srcH := img.Bounds().Dy()
+	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)))
+	}
+
+	if filter.Support <= 0 {
+		// Nearest-neighbor special case.
+		return resizeNearest(img, dstW, dstH)
+	}
+
+	if srcW != dstW && srcH != dstH {
+		return resizeVertical(resizeHorizontal(img, dstW, filter), dstH, filter)
+	}
+	if srcW != dstW {
+		return resizeHorizontal(img, dstW, filter)
+	}
+	if srcH != dstH {
+		return resizeVertical(img, dstH, filter)
+	}
+	return Clone(img)
+}
+
+func resizeHorizontal(img image.Image, width int, filter ResampleFilter) *image.NRGBA {
+	src := newScanner(img)
+	dst := image.NewNRGBA(image.Rect(0, 0, width, src.h))
+	weights := precomputeWeights(width, src.w, filter)
+	parallel(0, src.h, func(ys <-chan int) {
+		scanLine := make([]uint8, src.w*4)
+		for y := range ys {
+			src.scan(0, y, src.w, y+1, scanLine)
+			j0 := y * dst.Stride
+			for x := range weights {
+				var r, g, b, a float64
+				for _, w := range weights[x] {
+					i := w.index * 4
+					s := scanLine[i : i+4 : i+4]
+					aw := float64(s[3]) * w.weight
+					r += float64(s[0]) * aw
+					g += float64(s[1]) * aw
+					b += float64(s[2]) * aw
+					a += aw
+				}
+				if a != 0 {
+					aInv := 1 / a
+					j := j0 + x*4
+					d := dst.Pix[j : j+4 : j+4]
+					d[0] = clamp(r * aInv)
+					d[1] = clamp(g * aInv)
+					d[2] = clamp(b * aInv)
+					d[3] = clamp(a)
+				}
+			}
+		}
+	})
+	return dst
+}
+
+func resizeVertical(img image.Image, height int, filter ResampleFilter) *image.NRGBA {
+	src := newScanner(img)
+	dst := image.NewNRGBA(image.Rect(0, 0, src.w, height))
+	weights := precomputeWeights(height, src.h, filter)
+	parallel(0, src.w, func(xs <-chan int) {
+		scanLine := make([]uint8, src.h*4)
+		for x := range xs {
+			src.scan(x, 0, x+1, src.h, scanLine)
+			for y := range weights {
+				var r, g, b, a float64
+				for _, w := range weights[y] {
+					i := w.index * 4
+					s := scanLine[i : i+4 : i+4]
+					aw := float64(s[3]) * w.weight
+					r += float64(s[0]) * aw
+					g += float64(s[1]) * aw
+					b += float64(s[2]) * aw
+					a += aw
+				}
+				if a != 0 {
+					aInv := 1 / a
+					j := y*dst.Stride + x*4
+					d := dst.Pix[j : j+4 : j+4]
+					d[0] = clamp(r * aInv)
+					d[1] = clamp(g * aInv)
+					d[2] = clamp(b * aInv)
+					d[3] = clamp(a)
+				}
+			}
+		}
+	})
+	return dst
+}
+
+// resizeNearest is a fast nearest-neighbor resize, no filtering.
+func resizeNearest(img image.Image, width, height int) *image.NRGBA {
+	dst := image.NewNRGBA(image.Rect(0, 0, width, height))
+	dx := float64(img.Bounds().Dx()) / float64(width)
+	dy := float64(img.Bounds().Dy()) / float64(height)
+
+	if dx > 1 && dy > 1 {
+		src := newScanner(img)
+		parallel(0, height, func(ys <-chan int) {
+			for y := range ys {
+				srcY := int((float64(y) + 0.5) * dy)
+				dstOff := y * dst.Stride
+				for x := 0; x < width; x++ {
+					srcX := int((float64(x) + 0.5) * dx)
+					src.scan(srcX, srcY, srcX+1, srcY+1, dst.Pix[dstOff:dstOff+4])
+					dstOff += 4
+				}
+			}
+		})
+	} else {
+		src := toNRGBA(img)
+		parallel(0, height, func(ys <-chan int) {
+			for y := range ys {
+				srcY := int((float64(y) + 0.5) * dy)
+				srcOff0 := srcY * src.Stride
+				dstOff := y * dst.Stride
+				for x := 0; x < width; x++ {
+					srcX := int((float64(x) + 0.5) * dx)
+					srcOff := srcOff0 + srcX*4
+					copy(dst.Pix[dstOff:dstOff+4], src.Pix[srcOff:srcOff+4])
+					dstOff += 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.
+//
+// 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 creates an image with the specified dimensions and fills it with the scaled source image.
+// To achieve the correct aspect ratio without stretching, the source image will be cropped.
+//
+// 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 {
+	dstW, dstH := width, height
+
+	if dstW <= 0 || dstH <= 0 {
+		return &image.NRGBA{}
+	}
+
+	srcBounds := img.Bounds()
+	srcW := srcBounds.Dx()
+	srcH := srcBounds.Dy()
+
+	if srcW <= 0 || srcH <= 0 {
+		return &image.NRGBA{}
+	}
+
+	if srcW == dstW && srcH == dstH {
+		return Clone(img)
+	}
+
+	if srcW >= 100 && srcH >= 100 {
+		return cropAndResize(img, dstW, dstH, anchor, filter)
+	}
+	return resizeAndCrop(img, dstW, dstH, anchor, filter)
+}
+
+// cropAndResize crops the image to the smallest possible size that has the required aspect ratio using
+// the given anchor point, then scales it to the specified dimensions and returns the transformed image.
+//
+// This is generally faster than resizing first, but may result in inaccuracies when used on small source images.
+func cropAndResize(img image.Image, width, height int, anchor Anchor, filter ResampleFilter) *image.NRGBA {
+	dstW, dstH := width, height
+
+	srcBounds := img.Bounds()
+	srcW := srcBounds.Dx()
+	srcH := srcBounds.Dy()
+	srcAspectRatio := float64(srcW) / float64(srcH)
+	dstAspectRatio := float64(dstW) / float64(dstH)
+
+	var tmp *image.NRGBA
+	if srcAspectRatio < dstAspectRatio {
+		cropH := float64(srcW) * float64(dstH) / float64(dstW)
+		tmp = CropAnchor(img, srcW, int(math.Max(1, cropH)+0.5), anchor)
+	} else {
+		cropW := float64(srcH) * float64(dstW) / float64(dstH)
+		tmp = CropAnchor(img, int(math.Max(1, cropW)+0.5), srcH, anchor)
+	}
+
+	return Resize(tmp, dstW, dstH, filter)
+}
+
+// resizeAndCrop resizes 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.
+func resizeAndCrop(img image.Image, width, height int, anchor Anchor, filter ResampleFilter) *image.NRGBA {
+	dstW, dstH := width, height
+
+	srcBounds := img.Bounds()
+	srcW := srcBounds.Dx()
+	srcH := srcBounds.Dy()
+	srcAspectRatio := float64(srcW) / float64(srcH)
+	dstAspectRatio := float64(dstW) / float64(dstH)
+
+	var tmp *image.NRGBA
+	if srcAspectRatio < dstAspectRatio {
+		tmp = Resize(img, dstW, 0, filter)
+	} else {
+		tmp = Resize(img, 0, dstH, filter)
+	}
+
+	return CropAnchor(tmp, dstW, dstH, 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.
+//
+// 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)
+}
+
+// ResampleFilter specifies a resampling filter to be used for image resizing.
+//
+//	General filter recommendations:
+//
+//	- Lanczos
+//		A high-quality resampling filter for photographic images yielding sharp results.
+//
+//	- CatmullRom
+//		A sharp cubic filter that is faster than Lanczos filter while providing similar results.
+//
+//	- MitchellNetravali
+//		A cubic filter that produces smoother results with less ringing artifacts than CatmullRom.
+//
+//	- Linear
+//		Bilinear resampling filter, produces a smooth output. Faster than cubic filters.
+//
+//	- Box
+//		Simple and fast averaging filter appropriate for downscaling.
+//		When upscaling it's similar to NearestNeighbor.
+//
+//	- NearestNeighbor
+//		Fastest resampling filter, no antialiasing.
+//
+type ResampleFilter struct {
+	Support float64
+	Kernel  func(float64) float64
+}
+
+// NearestNeighbor is a 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
+
+// MitchellNetravali is Mitchell-Netravali cubic filter (BC-spline; B=1/3; C=1/3).
+var MitchellNetravali ResampleFilter
+
+// CatmullRom is a Catmull-Rom - sharp cubic filter (BC-spline; B=0; C=0.5).
+var CatmullRom ResampleFilter
+
+// BSpline is a smooth cubic filter (BC-spline; B=1; C=0).
+var BSpline ResampleFilter
+
+// Gaussian is a Gaussian blurring filter.
+var Gaussian ResampleFilter
+
+// Bartlett is a Bartlett-windowed sinc filter (3 lobes).
+var Bartlett ResampleFilter
+
+// Lanczos filter (3 lobes).
+var Lanczos ResampleFilter
+
+// Hann is a Hann-windowed sinc filter (3 lobes).
+var Hann ResampleFilter
+
+// Hamming is a Hamming-windowed sinc filter (3 lobes).
+var Hamming ResampleFilter
+
+// Blackman is a Blackman-windowed sinc filter (3 lobes).
+var Blackman ResampleFilter
+
+// Welch is a Welch-windowed sinc filter (parabolic window, 3 lobes).
+var Welch ResampleFilter
+
+// Cosine is a Cosine-windowed sinc filter (3 lobes).
+var Cosine ResampleFilter
+
+func bcspline(x, b, c float64) float64 {
+	var y float64
+	x = math.Abs(x)
+	if x < 1.0 {
+		y = ((12-9*b-6*c)*x*x*x + (-18+12*b+6*c)*x*x + (6 - 2*b)) / 6
+	} else if x < 2.0 {
+		y = ((-b-6*c)*x*x*x + (6*b+30*c)*x*x + (-12*b-48*c)*x + (8*b + 24*c)) / 6
+	}
+	return y
+}
+
+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
+		},
+	}
+}