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blender-archive/source/blender/compositor/operations/COM_OpenCLKernels.cl
Jeroen Bakker b63b8ea69d Compositor:
Added OpenCL kernel for the directional blur.

This operation always uses the full input image. In the current
implementation this input image is not cached on the device.

Future enhancement could be to cache it on the available opencl devices
2012-07-11 19:32:32 +00:00

235 lines
8.2 KiB
Common Lisp

/*
* Copyright 2011, Blender Foundation.
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*
* Contributor:
* Jeroen Bakker
* Monique Dewanchand
*/
/// This file contains all opencl kernels for node-operation implementations
// Global SAMPLERS
const sampler_t SAMPLER_NEAREST = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST;
const sampler_t SAMPLER_NEAREST_CLAMP = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
__constant const int2 zero = {0,0};
// KERNEL --- BOKEH BLUR ---
__kernel void bokehBlurKernel(__read_only image2d_t boundingBox, __read_only image2d_t inputImage,
__read_only image2d_t bokehImage, __write_only image2d_t output,
int2 offsetInput, int2 offsetOutput, int radius, int step, int2 dimension, int2 offset)
{
int2 coords = {get_global_id(0), get_global_id(1)};
coords += offset;
float tempBoundingBox;
float4 color = {0.0f,0.0f,0.0f,0.0f};
float4 multiplyer = {0.0f,0.0f,0.0f,0.0f};
float4 bokeh;
const float radius2 = radius*2.0f;
const int2 realCoordinate = coords + offsetOutput;
tempBoundingBox = read_imagef(boundingBox, SAMPLER_NEAREST, coords).s0;
if (tempBoundingBox > 0.0f && radius > 0 ) {
const int2 bokehImageDim = get_image_dim(bokehImage);
const int2 bokehImageCenter = bokehImageDim/2;
const int2 minXY = max(realCoordinate - radius, zero);
const int2 maxXY = min(realCoordinate + radius, dimension);
int nx, ny;
float2 uv;
int2 inputXy;
for (ny = minXY.y, inputXy.y = ny - offsetInput.y ; ny < maxXY.y ; ny +=step, inputXy.y+=step) {
uv.y = ((realCoordinate.y-ny)/radius2)*bokehImageDim.y+bokehImageCenter.y;
for (nx = minXY.x, inputXy.x = nx - offsetInput.x; nx < maxXY.x ; nx +=step, inputXy.x+=step) {
uv.x = ((realCoordinate.x-nx)/radius2)*bokehImageDim.x+bokehImageCenter.x;
bokeh = read_imagef(bokehImage, SAMPLER_NEAREST, uv);
color += bokeh * read_imagef(inputImage, SAMPLER_NEAREST, inputXy);
multiplyer += bokeh;
}
}
color /= multiplyer;
} else {
int2 imageCoordinates = realCoordinate - offsetInput;
color = read_imagef(inputImage, SAMPLER_NEAREST, imageCoordinates);
}
write_imagef(output, coords, color);
}
//KERNEL --- DEFOCUS /VARIABLESIZEBOKEHBLUR ---
__kernel void defocusKernel(__read_only image2d_t inputImage, __read_only image2d_t bokehImage,
__read_only image2d_t inputSize,
__write_only image2d_t output, int2 offsetInput, int2 offsetOutput,
int step, int maxBlur, float threshold, int2 dimension, int2 offset)
{
float4 color = {1.0f, 0.0f, 0.0f, 1.0f};
int2 coords = {get_global_id(0), get_global_id(1)};
coords += offset;
const int2 realCoordinate = coords + offsetOutput;
float4 readColor;
float4 bokeh;
float tempSize;
float4 multiplier_accum = {1.0f, 1.0f, 1.0f, 1.0f};
float4 color_accum;
int minx = max(realCoordinate.s0 - maxBlur, 0);
int miny = max(realCoordinate.s1 - maxBlur, 0);
int maxx = min(realCoordinate.s0 + maxBlur, dimension.s0);
int maxy = min(realCoordinate.s1 + maxBlur, dimension.s1);
{
int2 inputCoordinate = realCoordinate - offsetInput;
float size = read_imagef(inputSize, SAMPLER_NEAREST, inputCoordinate).s0;
color_accum = read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate);
for (int ny = miny; ny < maxy; ny += step) {
for (int nx = minx; nx < maxx; nx += step) {
if (nx >= 0 && nx < dimension.s0 && ny >= 0 && ny < dimension.s1) {
inputCoordinate.s0 = nx - offsetInput.s0;
inputCoordinate.s1 = ny - offsetInput.s1;
tempSize = read_imagef(inputSize, SAMPLER_NEAREST, inputCoordinate).s0;
if (size > threshold && tempSize > threshold) {
float dx = nx - realCoordinate.s0;
float dy = ny - realCoordinate.s1;
if (dx != 0 || dy != 0) {
if (tempSize >= fabs(dx) && tempSize >= fabs(dy)) {
float2 uv = { 256.0f + dx * 256.0f / tempSize, 256.0f + dy * 256.0f / tempSize};
bokeh = read_imagef(bokehImage, SAMPLER_NEAREST, uv);
readColor = read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate);
color_accum += bokeh*readColor;
multiplier_accum += bokeh;
}
}
}
}
}
}
}
color = color_accum * (1.0f / multiplier_accum);
write_imagef(output, coords, color);
}
// KERNEL --- DILATE ---
__kernel void dilateKernel(__read_only image2d_t inputImage, __write_only image2d_t output,
int2 offsetInput, int2 offsetOutput, int scope, int distanceSquared, int2 dimension,
int2 offset)
{
int2 coords = {get_global_id(0), get_global_id(1)};
coords += offset;
const int2 realCoordinate = coords + offsetOutput;
const int2 minXY = max(realCoordinate - scope, zero);
const int2 maxXY = min(realCoordinate + scope, dimension);
float value = 0.0f;
int nx, ny;
int2 inputXy;
for (ny = minXY.y, inputXy.y = ny - offsetInput.y ; ny < maxXY.y ; ny ++, inputXy.y++) {
const float deltaY = (realCoordinate.y - ny);
for (nx = minXY.x, inputXy.x = nx - offsetInput.x; nx < maxXY.x ; nx ++, inputXy.x++) {
const float deltaX = (realCoordinate.x - nx);
const float measuredDistance = deltaX*deltaX+deltaY*deltaY;
if (measuredDistance <= distanceSquared) {
value = max(value, read_imagef(inputImage, SAMPLER_NEAREST, inputXy).s0);
}
}
}
float4 color = {value,0.0f,0.0f,0.0f};
write_imagef(output, coords, color);
}
// KERNEL --- DILATE ---
__kernel void erodeKernel(__read_only image2d_t inputImage, __write_only image2d_t output,
int2 offsetInput, int2 offsetOutput, int scope, int distanceSquared, int2 dimension,
int2 offset)
{
int2 coords = {get_global_id(0), get_global_id(1)};
coords += offset;
const int2 realCoordinate = coords + offsetOutput;
const int2 minXY = max(realCoordinate - scope, zero);
const int2 maxXY = min(realCoordinate + scope, dimension);
float value = 1.0f;
int nx, ny;
int2 inputXy;
for (ny = minXY.y, inputXy.y = ny - offsetInput.y ; ny < maxXY.y ; ny ++, inputXy.y++) {
for (nx = minXY.x, inputXy.x = nx - offsetInput.x; nx < maxXY.x ; nx ++, inputXy.x++) {
const float deltaX = (realCoordinate.x - nx);
const float deltaY = (realCoordinate.y - ny);
const float measuredDistance = deltaX*deltaX+deltaY*deltaY;
if (measuredDistance <= distanceSquared) {
value = min(value, read_imagef(inputImage, SAMPLER_NEAREST, inputXy).s0);
}
}
}
float4 color = {value,0.0f,0.0f,0.0f};
write_imagef(output, coords, color);
}
// KERNEL --- DIRECTIONAL BLUR ---
__kernel void directionalBlurKernel(__read_only image2d_t inputImage, __write_only image2d_t output,
int2 offsetOutput, int iterations, float scale, float rotation, float2 translate,
float2 center, int2 offset)
{
int2 coords = {get_global_id(0), get_global_id(1)};
coords += offset;
const int2 realCoordinate = coords + offsetOutput;
float4 col;
float2 ltxy = translate;
float lsc = scale;
float lrot = rotation;
col = read_imagef(inputImage, SAMPLER_NEAREST, realCoordinate);
/* blur the image */
for (int i = 0; i < iterations; ++i) {
const float cs = cos(lrot), ss = sin(lrot);
const float isc = 1.0f / (1.0f + lsc);
const float v = isc * (realCoordinate.s1 - center.s1) + ltxy.s1;
const float u = isc * (realCoordinate.s0 - center.s0) + ltxy.s0;
float2 uv = {
cs * u + ss * v + center.s0,
cs * v - ss * u + center.s1
};
col += read_imagef(inputImage, SAMPLER_NEAREST_CLAMP, uv);
/* double transformations */
ltxy += translate;
lrot += rotation;
lsc += scale;
}
col *= (1.0f/(iterations+1));
write_imagef(output, coords, col);
}