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526 lines
15 KiB
Go
526 lines
15 KiB
Go
4 years ago
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// Copyright 2015 The Go Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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//go:generate go run gen.go
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package draw
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import (
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"image"
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"image/color"
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"math"
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"sync"
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"golang.org/x/image/math/f64"
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)
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// Copy copies the part of the source image defined by src and sr and writes
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// the result of a Porter-Duff composition to the part of the destination image
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// defined by dst and the translation of sr so that sr.Min translates to dp.
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func Copy(dst Image, dp image.Point, src image.Image, sr image.Rectangle, op Op, opts *Options) {
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var o Options
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if opts != nil {
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o = *opts
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}
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dr := sr.Add(dp.Sub(sr.Min))
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if o.DstMask == nil {
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DrawMask(dst, dr, src, sr.Min, o.SrcMask, o.SrcMaskP.Add(sr.Min), op)
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} else {
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NearestNeighbor.Scale(dst, dr, src, sr, op, opts)
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}
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}
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// Scaler scales the part of the source image defined by src and sr and writes
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// the result of a Porter-Duff composition to the part of the destination image
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// defined by dst and dr.
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//
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// A Scaler is safe to use concurrently.
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type Scaler interface {
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Scale(dst Image, dr image.Rectangle, src image.Image, sr image.Rectangle, op Op, opts *Options)
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}
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// Transformer transforms the part of the source image defined by src and sr
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// and writes the result of a Porter-Duff composition to the part of the
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// destination image defined by dst and the affine transform m applied to sr.
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//
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// For example, if m is the matrix
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//
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// m00 m01 m02
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// m10 m11 m12
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//
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// then the src-space point (sx, sy) maps to the dst-space point
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// (m00*sx + m01*sy + m02, m10*sx + m11*sy + m12).
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//
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// A Transformer is safe to use concurrently.
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type Transformer interface {
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Transform(dst Image, m f64.Aff3, src image.Image, sr image.Rectangle, op Op, opts *Options)
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}
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// Options are optional parameters to Copy, Scale and Transform.
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//
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// A nil *Options means to use the default (zero) values of each field.
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type Options struct {
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// Masks limit what parts of the dst image are drawn to and what parts of
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// the src image are drawn from.
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//
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// A dst or src mask image having a zero alpha (transparent) pixel value in
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// the respective coordinate space means that dst pixel is entirely
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// unaffected or that src pixel is considered transparent black. A full
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// alpha (opaque) value means that the dst pixel is maximally affected or
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// the src pixel contributes maximally. The default values, nil, are
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// equivalent to fully opaque, infinitely large mask images.
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//
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// The DstMask is otherwise known as a clip mask, and its pixels map 1:1 to
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// the dst image's pixels. DstMaskP in DstMask space corresponds to
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// image.Point{X:0, Y:0} in dst space. For example, when limiting
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// repainting to a 'dirty rectangle', use that image.Rectangle and a zero
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// image.Point as the DstMask and DstMaskP.
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//
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// The SrcMask's pixels map 1:1 to the src image's pixels. SrcMaskP in
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// SrcMask space corresponds to image.Point{X:0, Y:0} in src space. For
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// example, when drawing font glyphs in a uniform color, use an
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// *image.Uniform as the src, and use the glyph atlas image and the
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// per-glyph offset as SrcMask and SrcMaskP:
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// Copy(dst, dp, image.NewUniform(color), image.Rect(0, 0, glyphWidth, glyphHeight), &Options{
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// SrcMask: glyphAtlas,
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// SrcMaskP: glyphOffset,
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// })
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DstMask image.Image
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DstMaskP image.Point
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SrcMask image.Image
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SrcMaskP image.Point
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// TODO: a smooth vs sharp edges option, for arbitrary rotations?
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}
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// Interpolator is an interpolation algorithm, when dst and src pixels don't
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// have a 1:1 correspondence.
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//
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// Of the interpolators provided by this package:
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// - NearestNeighbor is fast but usually looks worst.
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// - CatmullRom is slow but usually looks best.
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// - ApproxBiLinear has reasonable speed and quality.
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//
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// The time taken depends on the size of dr. For kernel interpolators, the
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// speed also depends on the size of sr, and so are often slower than
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// non-kernel interpolators, especially when scaling down.
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type Interpolator interface {
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Scaler
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Transformer
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}
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// Kernel is an interpolator that blends source pixels weighted by a symmetric
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// kernel function.
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type Kernel struct {
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// Support is the kernel support and must be >= 0. At(t) is assumed to be
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// zero when t >= Support.
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Support float64
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// At is the kernel function. It will only be called with t in the
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// range [0, Support).
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At func(t float64) float64
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}
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// Scale implements the Scaler interface.
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func (q *Kernel) Scale(dst Image, dr image.Rectangle, src image.Image, sr image.Rectangle, op Op, opts *Options) {
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q.newScaler(dr.Dx(), dr.Dy(), sr.Dx(), sr.Dy(), false).Scale(dst, dr, src, sr, op, opts)
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}
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// NewScaler returns a Scaler that is optimized for scaling multiple times with
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// the same fixed destination and source width and height.
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func (q *Kernel) NewScaler(dw, dh, sw, sh int) Scaler {
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return q.newScaler(dw, dh, sw, sh, true)
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}
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func (q *Kernel) newScaler(dw, dh, sw, sh int, usePool bool) Scaler {
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z := &kernelScaler{
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kernel: q,
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dw: int32(dw),
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dh: int32(dh),
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sw: int32(sw),
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sh: int32(sh),
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horizontal: newDistrib(q, int32(dw), int32(sw)),
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vertical: newDistrib(q, int32(dh), int32(sh)),
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}
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if usePool {
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z.pool.New = func() interface{} {
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tmp := z.makeTmpBuf()
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return &tmp
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}
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}
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return z
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}
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var (
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// NearestNeighbor is the nearest neighbor interpolator. It is very fast,
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// but usually gives very low quality results. When scaling up, the result
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// will look 'blocky'.
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NearestNeighbor = Interpolator(nnInterpolator{})
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// ApproxBiLinear is a mixture of the nearest neighbor and bi-linear
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// interpolators. It is fast, but usually gives medium quality results.
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//
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// It implements bi-linear interpolation when upscaling and a bi-linear
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// blend of the 4 nearest neighbor pixels when downscaling. This yields
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// nicer quality than nearest neighbor interpolation when upscaling, but
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// the time taken is independent of the number of source pixels, unlike the
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// bi-linear interpolator. When downscaling a large image, the performance
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// difference can be significant.
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ApproxBiLinear = Interpolator(ablInterpolator{})
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// BiLinear is the tent kernel. It is slow, but usually gives high quality
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// results.
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BiLinear = &Kernel{1, func(t float64) float64 {
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return 1 - t
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}}
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// CatmullRom is the Catmull-Rom kernel. It is very slow, but usually gives
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// very high quality results.
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//
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// It is an instance of the more general cubic BC-spline kernel with parameters
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// B=0 and C=0.5. See Mitchell and Netravali, "Reconstruction Filters in
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// Computer Graphics", Computer Graphics, Vol. 22, No. 4, pp. 221-228.
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CatmullRom = &Kernel{2, func(t float64) float64 {
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if t < 1 {
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return (1.5*t-2.5)*t*t + 1
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}
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return ((-0.5*t+2.5)*t-4)*t + 2
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}}
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// TODO: a Kaiser-Bessel kernel?
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)
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type nnInterpolator struct{}
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type ablInterpolator struct{}
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type kernelScaler struct {
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kernel *Kernel
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dw, dh, sw, sh int32
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horizontal, vertical distrib
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pool sync.Pool
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}
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func (z *kernelScaler) makeTmpBuf() [][4]float64 {
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return make([][4]float64, z.dw*z.sh)
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}
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// source is a range of contribs, their inverse total weight, and that ITW
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// divided by 0xffff.
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type source struct {
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i, j int32
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invTotalWeight float64
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invTotalWeightFFFF float64
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}
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// contrib is the weight of a column or row.
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type contrib struct {
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coord int32
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weight float64
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}
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// distrib measures how source pixels are distributed over destination pixels.
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type distrib struct {
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// sources are what contribs each column or row in the source image owns,
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// and the total weight of those contribs.
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sources []source
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// contribs are the contributions indexed by sources[s].i and sources[s].j.
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contribs []contrib
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}
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// newDistrib returns a distrib that distributes sw source columns (or rows)
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// over dw destination columns (or rows).
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func newDistrib(q *Kernel, dw, sw int32) distrib {
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scale := float64(sw) / float64(dw)
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halfWidth, kernelArgScale := q.Support, 1.0
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// When shrinking, broaden the effective kernel support so that we still
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// visit every source pixel.
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if scale > 1 {
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halfWidth *= scale
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kernelArgScale = 1 / scale
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}
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// Make the sources slice, one source for each column or row, and temporarily
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// appropriate its elements' fields so that invTotalWeight is the scaled
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// coordinate of the source column or row, and i and j are the lower and
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// upper bounds of the range of destination columns or rows affected by the
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// source column or row.
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n, sources := int32(0), make([]source, dw)
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for x := range sources {
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center := (float64(x)+0.5)*scale - 0.5
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i := int32(math.Floor(center - halfWidth))
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if i < 0 {
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i = 0
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}
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j := int32(math.Ceil(center + halfWidth))
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if j > sw {
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j = sw
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if j < i {
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j = i
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}
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}
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sources[x] = source{i: i, j: j, invTotalWeight: center}
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n += j - i
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}
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contribs := make([]contrib, 0, n)
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for k, b := range sources {
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totalWeight := 0.0
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l := int32(len(contribs))
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for coord := b.i; coord < b.j; coord++ {
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t := abs((b.invTotalWeight - float64(coord)) * kernelArgScale)
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if t >= q.Support {
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continue
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}
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weight := q.At(t)
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if weight == 0 {
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continue
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}
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totalWeight += weight
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contribs = append(contribs, contrib{coord, weight})
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}
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totalWeight = 1 / totalWeight
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sources[k] = source{
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i: l,
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j: int32(len(contribs)),
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invTotalWeight: totalWeight,
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invTotalWeightFFFF: totalWeight / 0xffff,
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}
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}
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return distrib{sources, contribs}
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}
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// abs is like math.Abs, but it doesn't care about negative zero, infinities or
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// NaNs.
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func abs(f float64) float64 {
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if f < 0 {
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f = -f
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}
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return f
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}
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// ftou converts the range [0.0, 1.0] to [0, 0xffff].
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func ftou(f float64) uint16 {
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i := int32(0xffff*f + 0.5)
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if i > 0xffff {
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return 0xffff
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}
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if i > 0 {
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return uint16(i)
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}
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return 0
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}
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// fffftou converts the range [0.0, 65535.0] to [0, 0xffff].
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func fffftou(f float64) uint16 {
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i := int32(f + 0.5)
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if i > 0xffff {
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return 0xffff
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}
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if i > 0 {
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return uint16(i)
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}
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return 0
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}
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// invert returns the inverse of m.
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//
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// TODO: move this into the f64 package, once we work out the convention for
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// matrix methods in that package: do they modify the receiver, take a dst
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// pointer argument, or return a new value?
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func invert(m *f64.Aff3) f64.Aff3 {
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m00 := +m[3*1+1]
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m01 := -m[3*0+1]
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m02 := +m[3*1+2]*m[3*0+1] - m[3*1+1]*m[3*0+2]
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m10 := -m[3*1+0]
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m11 := +m[3*0+0]
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m12 := +m[3*1+0]*m[3*0+2] - m[3*1+2]*m[3*0+0]
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det := m00*m11 - m10*m01
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return f64.Aff3{
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m00 / det,
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m01 / det,
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m02 / det,
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m10 / det,
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m11 / det,
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m12 / det,
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}
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}
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func matMul(p, q *f64.Aff3) f64.Aff3 {
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return f64.Aff3{
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p[3*0+0]*q[3*0+0] + p[3*0+1]*q[3*1+0],
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p[3*0+0]*q[3*0+1] + p[3*0+1]*q[3*1+1],
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p[3*0+0]*q[3*0+2] + p[3*0+1]*q[3*1+2] + p[3*0+2],
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p[3*1+0]*q[3*0+0] + p[3*1+1]*q[3*1+0],
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p[3*1+0]*q[3*0+1] + p[3*1+1]*q[3*1+1],
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p[3*1+0]*q[3*0+2] + p[3*1+1]*q[3*1+2] + p[3*1+2],
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}
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}
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// transformRect returns a rectangle dr that contains sr transformed by s2d.
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func transformRect(s2d *f64.Aff3, sr *image.Rectangle) (dr image.Rectangle) {
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ps := [...]image.Point{
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{sr.Min.X, sr.Min.Y},
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{sr.Max.X, sr.Min.Y},
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{sr.Min.X, sr.Max.Y},
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{sr.Max.X, sr.Max.Y},
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}
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for i, p := range ps {
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sxf := float64(p.X)
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syf := float64(p.Y)
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dx := int(math.Floor(s2d[0]*sxf + s2d[1]*syf + s2d[2]))
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dy := int(math.Floor(s2d[3]*sxf + s2d[4]*syf + s2d[5]))
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// The +1 adjustments below are because an image.Rectangle is inclusive
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// on the low end but exclusive on the high end.
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if i == 0 {
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dr = image.Rectangle{
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Min: image.Point{dx + 0, dy + 0},
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Max: image.Point{dx + 1, dy + 1},
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}
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continue
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}
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if dr.Min.X > dx {
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dr.Min.X = dx
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}
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dx++
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if dr.Max.X < dx {
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dr.Max.X = dx
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}
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if dr.Min.Y > dy {
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dr.Min.Y = dy
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}
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dy++
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if dr.Max.Y < dy {
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dr.Max.Y = dy
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}
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}
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return dr
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}
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func clipAffectedDestRect(adr image.Rectangle, dstMask image.Image, dstMaskP image.Point) (image.Rectangle, image.Image) {
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if dstMask == nil {
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return adr, nil
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}
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if r, ok := dstMask.(image.Rectangle); ok {
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return adr.Intersect(r.Sub(dstMaskP)), nil
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}
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// TODO: clip to dstMask.Bounds() if the color model implies that out-of-bounds means 0 alpha?
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||
|
return adr, dstMask
|
||
|
}
|
||
|
|
||
|
func transform_Uniform(dst Image, dr, adr image.Rectangle, d2s *f64.Aff3, src *image.Uniform, sr image.Rectangle, bias image.Point, op Op) {
|
||
|
switch op {
|
||
|
case Over:
|
||
|
switch dst := dst.(type) {
|
||
|
case *image.RGBA:
|
||
|
pr, pg, pb, pa := src.C.RGBA()
|
||
|
pa1 := (0xffff - pa) * 0x101
|
||
|
|
||
|
for dy := int32(adr.Min.Y); dy < int32(adr.Max.Y); dy++ {
|
||
|
dyf := float64(dr.Min.Y+int(dy)) + 0.5
|
||
|
d := dst.PixOffset(dr.Min.X+adr.Min.X, dr.Min.Y+int(dy))
|
||
|
for dx := int32(adr.Min.X); dx < int32(adr.Max.X); dx, d = dx+1, d+4 {
|
||
|
dxf := float64(dr.Min.X+int(dx)) + 0.5
|
||
|
sx0 := int(d2s[0]*dxf+d2s[1]*dyf+d2s[2]) + bias.X
|
||
|
sy0 := int(d2s[3]*dxf+d2s[4]*dyf+d2s[5]) + bias.Y
|
||
|
if !(image.Point{sx0, sy0}).In(sr) {
|
||
|
continue
|
||
|
}
|
||
|
dst.Pix[d+0] = uint8((uint32(dst.Pix[d+0])*pa1/0xffff + pr) >> 8)
|
||
|
dst.Pix[d+1] = uint8((uint32(dst.Pix[d+1])*pa1/0xffff + pg) >> 8)
|
||
|
dst.Pix[d+2] = uint8((uint32(dst.Pix[d+2])*pa1/0xffff + pb) >> 8)
|
||
|
dst.Pix[d+3] = uint8((uint32(dst.Pix[d+3])*pa1/0xffff + pa) >> 8)
|
||
|
}
|
||
|
}
|
||
|
|
||
|
default:
|
||
|
pr, pg, pb, pa := src.C.RGBA()
|
||
|
pa1 := 0xffff - pa
|
||
|
dstColorRGBA64 := &color.RGBA64{}
|
||
|
dstColor := color.Color(dstColorRGBA64)
|
||
|
|
||
|
for dy := int32(adr.Min.Y); dy < int32(adr.Max.Y); dy++ {
|
||
|
dyf := float64(dr.Min.Y+int(dy)) + 0.5
|
||
|
for dx := int32(adr.Min.X); dx < int32(adr.Max.X); dx++ {
|
||
|
dxf := float64(dr.Min.X+int(dx)) + 0.5
|
||
|
sx0 := int(d2s[0]*dxf+d2s[1]*dyf+d2s[2]) + bias.X
|
||
|
sy0 := int(d2s[3]*dxf+d2s[4]*dyf+d2s[5]) + bias.Y
|
||
|
if !(image.Point{sx0, sy0}).In(sr) {
|
||
|
continue
|
||
|
}
|
||
|
qr, qg, qb, qa := dst.At(dr.Min.X+int(dx), dr.Min.Y+int(dy)).RGBA()
|
||
|
dstColorRGBA64.R = uint16(qr*pa1/0xffff + pr)
|
||
|
dstColorRGBA64.G = uint16(qg*pa1/0xffff + pg)
|
||
|
dstColorRGBA64.B = uint16(qb*pa1/0xffff + pb)
|
||
|
dstColorRGBA64.A = uint16(qa*pa1/0xffff + pa)
|
||
|
dst.Set(dr.Min.X+int(dx), dr.Min.Y+int(dy), dstColor)
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
case Src:
|
||
|
switch dst := dst.(type) {
|
||
|
case *image.RGBA:
|
||
|
pr, pg, pb, pa := src.C.RGBA()
|
||
|
pr8 := uint8(pr >> 8)
|
||
|
pg8 := uint8(pg >> 8)
|
||
|
pb8 := uint8(pb >> 8)
|
||
|
pa8 := uint8(pa >> 8)
|
||
|
|
||
|
for dy := int32(adr.Min.Y); dy < int32(adr.Max.Y); dy++ {
|
||
|
dyf := float64(dr.Min.Y+int(dy)) + 0.5
|
||
|
d := dst.PixOffset(dr.Min.X+adr.Min.X, dr.Min.Y+int(dy))
|
||
|
for dx := int32(adr.Min.X); dx < int32(adr.Max.X); dx, d = dx+1, d+4 {
|
||
|
dxf := float64(dr.Min.X+int(dx)) + 0.5
|
||
|
sx0 := int(d2s[0]*dxf+d2s[1]*dyf+d2s[2]) + bias.X
|
||
|
sy0 := int(d2s[3]*dxf+d2s[4]*dyf+d2s[5]) + bias.Y
|
||
|
if !(image.Point{sx0, sy0}).In(sr) {
|
||
|
continue
|
||
|
}
|
||
|
dst.Pix[d+0] = pr8
|
||
|
dst.Pix[d+1] = pg8
|
||
|
dst.Pix[d+2] = pb8
|
||
|
dst.Pix[d+3] = pa8
|
||
|
}
|
||
|
}
|
||
|
|
||
|
default:
|
||
|
pr, pg, pb, pa := src.C.RGBA()
|
||
|
dstColorRGBA64 := &color.RGBA64{
|
||
|
uint16(pr),
|
||
|
uint16(pg),
|
||
|
uint16(pb),
|
||
|
uint16(pa),
|
||
|
}
|
||
|
dstColor := color.Color(dstColorRGBA64)
|
||
|
|
||
|
for dy := int32(adr.Min.Y); dy < int32(adr.Max.Y); dy++ {
|
||
|
dyf := float64(dr.Min.Y+int(dy)) + 0.5
|
||
|
for dx := int32(adr.Min.X); dx < int32(adr.Max.X); dx++ {
|
||
|
dxf := float64(dr.Min.X+int(dx)) + 0.5
|
||
|
sx0 := int(d2s[0]*dxf+d2s[1]*dyf+d2s[2]) + bias.X
|
||
|
sy0 := int(d2s[3]*dxf+d2s[4]*dyf+d2s[5]) + bias.Y
|
||
|
if !(image.Point{sx0, sy0}).In(sr) {
|
||
|
continue
|
||
|
}
|
||
|
dst.Set(dr.Min.X+int(dx), dr.Min.Y+int(dy), dstColor)
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
func opaque(m image.Image) bool {
|
||
|
o, ok := m.(interface {
|
||
|
Opaque() bool
|
||
|
})
|
||
|
return ok && o.Opaque()
|
||
|
}
|