Stu Leak
68df790d27
Major improvements to UnifiedPlayer: 1. GetFrameImage() now works when paused for responsive UI updates 2. Play() method properly starts FFmpeg process 3. Frame display loop runs continuously for smooth video display 4. Disabled audio temporarily to fix video playback fundamentals 5. Simplified FFmpeg command to focus on video stream only Player now: - Generates video frames correctly - Shows video when paused - Has responsive progress tracking - Starts playback properly Next steps: Re-enable audio playback once video is stable
621 lines
20 KiB
Go
621 lines
20 KiB
Go
/*
|
|
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.
|
|
// If the input image has width or height of 0, it is returned unchanged.
|
|
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
|
|
}
|
|
|
|
// Input image has no pixels
|
|
if img.Bounds().Dx() <= 0 || img.Bounds().Dy() <= 0 {
|
|
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))
|
|
}
|