diff options
Diffstat (limited to 'source/blender/compositor/operations/COM_OpenCLKernels.cl.h')
-rw-r--r-- | source/blender/compositor/operations/COM_OpenCLKernels.cl.h | 250 |
1 files changed, 0 insertions, 250 deletions
diff --git a/source/blender/compositor/operations/COM_OpenCLKernels.cl.h b/source/blender/compositor/operations/COM_OpenCLKernels.cl.h deleted file mode 100644 index e72ed5bf755..00000000000 --- a/source/blender/compositor/operations/COM_OpenCLKernels.cl.h +++ /dev/null @@ -1,250 +0,0 @@ -/* clkernelstoh output of file <COM_OpenCLKernels_cl> */ - -const char * clkernelstoh_COM_OpenCLKernels_cl = "/*\n" \ -" * Copyright 2011, Blender Foundation.\n" \ -" *\n" \ -" * This program is free software; you can redistribute it and/or\n" \ -" * modify it under the terms of the GNU General Public License\n" \ -" * as published by the Free Software Foundation; either version 2\n" \ -" * of the License, or (at your option) any later version.\n" \ -" *\n" \ -" * This program is distributed in the hope that it will be useful,\n" \ -" * but WITHOUT ANY WARRANTY; without even the implied warranty of\n" \ -" * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n" \ -" * GNU General Public License for more details.\n" \ -" *\n" \ -" * You should have received a copy of the GNU General Public License\n" \ -" * along with this program; if not, write to the Free Software Foundation,\n" \ -" * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.\n" \ -" *\n" \ -" * Contributor:\n" \ -" * Jeroen Bakker\n" \ -" * Monique Dewanchand\n" \ -" */\n" \ -"\n" \ -"/// This file contains all opencl kernels for node-operation implementations\n" \ -"\n" \ -"// Global SAMPLERS\n" \ -"const sampler_t SAMPLER_NEAREST = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST;\n" \ -"const sampler_t SAMPLER_NEAREST_CLAMP = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" \ -"\n" \ -"__constant const int2 zero = {0,0};\n" \ -"\n" \ -"// KERNEL --- BOKEH BLUR ---\n" \ -"__kernel void bokehBlurKernel(__read_only image2d_t boundingBox, __read_only image2d_t inputImage,\n" \ -" __read_only image2d_t bokehImage, __write_only image2d_t output,\n" \ -" int2 offsetInput, int2 offsetOutput, int radius, int step, int2 dimension, int2 offset)\n" \ -"{\n" \ -" int2 coords = {get_global_id(0), get_global_id(1)};\n" \ -" coords += offset;\n" \ -" float tempBoundingBox;\n" \ -" float4 color = {0.0f,0.0f,0.0f,0.0f};\n" \ -" float4 multiplyer = {0.0f,0.0f,0.0f,0.0f};\n" \ -" float4 bokeh;\n" \ -" const float radius2 = radius*2.0f;\n" \ -" const int2 realCoordinate = coords + offsetOutput;\n" \ -"\n" \ -" tempBoundingBox = read_imagef(boundingBox, SAMPLER_NEAREST, coords).s0;\n" \ -"\n" \ -" if (tempBoundingBox > 0.0f && radius > 0 ) {\n" \ -" const int2 bokehImageDim = get_image_dim(bokehImage);\n" \ -" const int2 bokehImageCenter = bokehImageDim/2;\n" \ -" const int2 minXY = max(realCoordinate - radius, zero);\n" \ -" const int2 maxXY = min(realCoordinate + radius, dimension);\n" \ -" int nx, ny;\n" \ -"\n" \ -" float2 uv;\n" \ -" int2 inputXy;\n" \ -"\n" \ -" for (ny = minXY.y, inputXy.y = ny - offsetInput.y ; ny < maxXY.y ; ny +=step, inputXy.y+=step) {\n" \ -" uv.y = ((realCoordinate.y-ny)/radius2)*bokehImageDim.y+bokehImageCenter.y;\n" \ -"\n" \ -" for (nx = minXY.x, inputXy.x = nx - offsetInput.x; nx < maxXY.x ; nx +=step, inputXy.x+=step) {\n" \ -" uv.x = ((realCoordinate.x-nx)/radius2)*bokehImageDim.x+bokehImageCenter.x;\n" \ -" bokeh = read_imagef(bokehImage, SAMPLER_NEAREST, uv);\n" \ -" color += bokeh * read_imagef(inputImage, SAMPLER_NEAREST, inputXy);\n" \ -" multiplyer += bokeh;\n" \ -" }\n" \ -" }\n" \ -" color /= multiplyer;\n" \ -"\n" \ -" } else {\n" \ -" int2 imageCoordinates = realCoordinate - offsetInput;\n" \ -" color = read_imagef(inputImage, SAMPLER_NEAREST, imageCoordinates);\n" \ -" }\n" \ -"\n" \ -" write_imagef(output, coords, color);\n" \ -"}\n" \ -"\n" \ -"//KERNEL --- DEFOCUS /VARIABLESIZEBOKEHBLUR ---\n" \ -"__kernel void defocusKernel(__read_only image2d_t inputImage, __read_only image2d_t bokehImage,\n" \ -" __read_only image2d_t inputSize,\n" \ -" __write_only image2d_t output, int2 offsetInput, int2 offsetOutput,\n" \ -" int step, int maxBlur, float threshold, int2 dimension, int2 offset)\n" \ -"{\n" \ -" float4 color = {1.0f, 0.0f, 0.0f, 1.0f};\n" \ -" int2 coords = {get_global_id(0), get_global_id(1)};\n" \ -" coords += offset;\n" \ -" const int2 realCoordinate = coords + offsetOutput;\n" \ -"\n" \ -" float4 readColor;\n" \ -" float4 tempColor;\n" \ -" float4 bokeh;\n" \ -" float size;\n" \ -" float4 multiplier_accum = {1.0f, 1.0f, 1.0f, 1.0f};\n" \ -" float4 color_accum;\n" \ -"\n" \ -" int minx = max(realCoordinate.s0 - maxBlur, 0);\n" \ -" int miny = max(realCoordinate.s1 - maxBlur, 0);\n" \ -" int maxx = min(realCoordinate.s0 + maxBlur, dimension.s0);\n" \ -" int maxy = min(realCoordinate.s1 + maxBlur, dimension.s1);\n" \ -"\n" \ -" {\n" \ -" int2 inputCoordinate = realCoordinate - offsetInput;\n" \ -" float size_center = read_imagef(inputSize, SAMPLER_NEAREST, inputCoordinate).s0;\n" \ -" color_accum = read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate);\n" \ -" readColor = color_accum;\n" \ -"\n" \ -" if (size_center > threshold) {\n" \ -" for (int ny = miny; ny < maxy; ny += step) {\n" \ -" inputCoordinate.s1 = ny - offsetInput.s1;\n" \ -" float dy = ny - realCoordinate.s1;\n" \ -" for (int nx = minx; nx < maxx; nx += step) {\n" \ -" float dx = nx - realCoordinate.s0;\n" \ -" if (dx != 0 || dy != 0) {\n" \ -" inputCoordinate.s0 = nx - offsetInput.s0;\n" \ -" size = read_imagef(inputSize, SAMPLER_NEAREST, inputCoordinate).s0;\n" \ -" if (size > threshold) {\n" \ -" if (size >= fabs(dx) && size >= fabs(dy)) {\n" \ -" float2 uv = {256.0f + dx * 255.0f / size,\n" \ -" 256.0f + dy * 255.0f / size};\n" \ -" bokeh = read_imagef(bokehImage, SAMPLER_NEAREST, uv);\n" \ -" tempColor = read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate);\n" \ -" color_accum += bokeh * tempColor;\n" \ -" multiplier_accum += bokeh;\n" \ -" }\n" \ -" }\n" \ -" }\n" \ -" }\n" \ -" }\n" \ -" }\n" \ -"\n" \ -" color = color_accum * (1.0f / multiplier_accum);\n" \ -"\n" \ -" /* blend in out values over the threshold, otherwise we get sharp, ugly transitions */\n" \ -" if ((size_center > threshold) &&\n" \ -" (size_center < threshold * 2.0f))\n" \ -" {\n" \ -" /* factor from 0-1 */\n" \ -" float fac = (size_center - threshold) / threshold;\n" \ -" color = (readColor * (1.0f - fac)) + (color * fac);\n" \ -" }\n" \ -"\n" \ -" write_imagef(output, coords, color);\n" \ -" }\n" \ -"}\n" \ -"\n" \ -"\n" \ -"// KERNEL --- DILATE ---\n" \ -"__kernel void dilateKernel(__read_only image2d_t inputImage, __write_only image2d_t output,\n" \ -" int2 offsetInput, int2 offsetOutput, int scope, int distanceSquared, int2 dimension,\n" \ -" int2 offset)\n" \ -"{\n" \ -" int2 coords = {get_global_id(0), get_global_id(1)};\n" \ -" coords += offset;\n" \ -" const int2 realCoordinate = coords + offsetOutput;\n" \ -"\n" \ -" const int2 minXY = max(realCoordinate - scope, zero);\n" \ -" const int2 maxXY = min(realCoordinate + scope, dimension);\n" \ -"\n" \ -" float value = 0.0f;\n" \ -" int nx, ny;\n" \ -" int2 inputXy;\n" \ -"\n" \ -" for (ny = minXY.y, inputXy.y = ny - offsetInput.y ; ny < maxXY.y ; ny ++, inputXy.y++) {\n" \ -" const float deltaY = (realCoordinate.y - ny);\n" \ -" for (nx = minXY.x, inputXy.x = nx - offsetInput.x; nx < maxXY.x ; nx ++, inputXy.x++) {\n" \ -" const float deltaX = (realCoordinate.x - nx);\n" \ -" const float measuredDistance = deltaX * deltaX + deltaY * deltaY;\n" \ -" if (measuredDistance <= distanceSquared) {\n" \ -" value = max(value, read_imagef(inputImage, SAMPLER_NEAREST, inputXy).s0);\n" \ -" }\n" \ -" }\n" \ -" }\n" \ -"\n" \ -" float4 color = {value,0.0f,0.0f,0.0f};\n" \ -" write_imagef(output, coords, color);\n" \ -"}\n" \ -"\n" \ -"// KERNEL --- DILATE ---\n" \ -"__kernel void erodeKernel(__read_only image2d_t inputImage, __write_only image2d_t output,\n" \ -" int2 offsetInput, int2 offsetOutput, int scope, int distanceSquared, int2 dimension,\n" \ -" int2 offset)\n" \ -"{\n" \ -" int2 coords = {get_global_id(0), get_global_id(1)};\n" \ -" coords += offset;\n" \ -" const int2 realCoordinate = coords + offsetOutput;\n" \ -"\n" \ -" const int2 minXY = max(realCoordinate - scope, zero);\n" \ -" const int2 maxXY = min(realCoordinate + scope, dimension);\n" \ -"\n" \ -" float value = 1.0f;\n" \ -" int nx, ny;\n" \ -" int2 inputXy;\n" \ -"\n" \ -" for (ny = minXY.y, inputXy.y = ny - offsetInput.y ; ny < maxXY.y ; ny ++, inputXy.y++) {\n" \ -" for (nx = minXY.x, inputXy.x = nx - offsetInput.x; nx < maxXY.x ; nx ++, inputXy.x++) {\n" \ -" const float deltaX = (realCoordinate.x - nx);\n" \ -" const float deltaY = (realCoordinate.y - ny);\n" \ -" const float measuredDistance = deltaX * deltaX+deltaY * deltaY;\n" \ -" if (measuredDistance <= distanceSquared) {\n" \ -" value = min(value, read_imagef(inputImage, SAMPLER_NEAREST, inputXy).s0);\n" \ -" }\n" \ -" }\n" \ -" }\n" \ -"\n" \ -" float4 color = {value,0.0f,0.0f,0.0f};\n" \ -" write_imagef(output, coords, color);\n" \ -"}\n" \ -"\n" \ -"// KERNEL --- DIRECTIONAL BLUR ---\n" \ -"__kernel void directionalBlurKernel(__read_only image2d_t inputImage, __write_only image2d_t output,\n" \ -" int2 offsetOutput, int iterations, float scale, float rotation, float2 translate,\n" \ -" float2 center, int2 offset)\n" \ -"{\n" \ -" int2 coords = {get_global_id(0), get_global_id(1)};\n" \ -" coords += offset;\n" \ -" const int2 realCoordinate = coords + offsetOutput;\n" \ -"\n" \ -" float4 col;\n" \ -" float2 ltxy = translate;\n" \ -" float lsc = scale;\n" \ -" float lrot = rotation;\n" \ -"\n" \ -" col = read_imagef(inputImage, SAMPLER_NEAREST, realCoordinate);\n" \ -"\n" \ -" /* blur the image */\n" \ -" for (int i = 0; i < iterations; ++i) {\n" \ -" const float cs = cos(lrot), ss = sin(lrot);\n" \ -" const float isc = 1.0f / (1.0f + lsc);\n" \ -"\n" \ -" const float v = isc * (realCoordinate.s1 - center.s1) + ltxy.s1;\n" \ -" const float u = isc * (realCoordinate.s0 - center.s0) + ltxy.s0;\n" \ -" float2 uv = {\n" \ -" cs * u + ss * v + center.s0,\n" \ -" cs * v - ss * u + center.s1\n" \ -" };\n" \ -"\n" \ -" col += read_imagef(inputImage, SAMPLER_NEAREST_CLAMP, uv);\n" \ -"\n" \ -" /* double transformations */\n" \ -" ltxy += translate;\n" \ -" lrot += rotation;\n" \ -" lsc += scale;\n" \ -" }\n" \ -"\n" \ -" col *= (1.0f/(iterations+1));\n" \ -"\n" \ -" write_imagef(output, coords, col);\n" \ -"}\n" \ -"\0"; |