mirror of
https://github.com/superseriousbusiness/gotosocial.git
synced 2025-10-30 17:22:26 -05:00
Grand test fixup (#138)
* start fixing up tests * fix up tests + automate with drone * fiddle with linting * messing about with drone.yml * some more fiddling * hmmm * add cache * add vendor directory * verbose * ci updates * update some little things * update sig
This commit is contained in:
Tobi Smethurst
GitHub
parent
329a5e8144
commit
98263a7de6
2677 changed files with 1090869 additions and 219 deletions
620
vendor/github.com/nfnt/resize/resize.go
generated
vendored
Normal file
620
vendor/github.com/nfnt/resize/resize.go
generated
vendored
Normal file
|
|
@ -0,0 +1,620 @@
|
|||
/*
|
||||
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))
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue