diff options
author | Manuel Castilla <manzanillawork@gmail.com> | 2021-10-14 00:01:15 +0300 |
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committer | Manuel Castilla <manzanillawork@gmail.com> | 2021-10-14 00:41:14 +0300 |
commit | 1c42d4930a24d639b3aa561b9a8b4bbce05977e0 (patch) | |
tree | 68c2aae3fd5ae98b78708bea28c0b55d3f4fb5f0 /source/blender/compositor/operations/COM_OpenCLKernels.cl | |
parent | a2ee3c3a9f01f5cb2f05f1e84a1b6c1931d9d4a4 (diff) |
Cleanup: convert camelCase naming to snake_case in Compositor
To convert old code to the current convention and
use a single code style.
Diffstat (limited to 'source/blender/compositor/operations/COM_OpenCLKernels.cl')
-rw-r--r-- | source/blender/compositor/operations/COM_OpenCLKernels.cl | 196 |
1 files changed, 98 insertions, 98 deletions
diff --git a/source/blender/compositor/operations/COM_OpenCLKernels.cl b/source/blender/compositor/operations/COM_OpenCLKernels.cl index ebe8a6d08ec..d01e209d3e4 100644 --- a/source/blender/compositor/operations/COM_OpenCLKernels.cl +++ b/source/blender/compositor/operations/COM_OpenCLKernels.cl @@ -29,101 +29,101 @@ const sampler_t SAMPLER_NEAREST_CLAMP = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRES __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) +__kernel void bokeh_blur_kernel(__read_only image2d_t bounding_box, __read_only image2d_t input_image, + __read_only image2d_t bokeh_image, __write_only image2d_t output, + int2 offset_input, int2 offset_output, int radius, int step, int2 dimension, int2 offset) { int2 coords = {get_global_id(0), get_global_id(1)}; coords += offset; - float tempBoundingBox; + float temp_bounding_box; 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; - int2 imageCoordinates = realCoordinate - offsetInput; + const int2 real_coordinate = coords + offset_output; + int2 image_coordinates = real_coordinate - offset_input; - tempBoundingBox = read_imagef(boundingBox, SAMPLER_NEAREST, coords).s0; + temp_bounding_box = read_imagef(bounding_box, 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); + if (temp_bounding_box > 0.0f && radius > 0 ) { + const int2 bokeh_image_dim = get_image_dim(bokeh_image); + const int2 bokeh_image_center = bokeh_image_dim/2; + const int2 minXY = max(real_coordinate - radius, zero); + const int2 maxXY = min(real_coordinate + radius, dimension); int nx, ny; float2 uv; - int2 inputXy; + int2 input_xy; if (radius < 2) { - color = read_imagef(inputImage, SAMPLER_NEAREST, imageCoordinates); + color = read_imagef(input_image, SAMPLER_NEAREST, image_coordinates); multiplyer = (float4)(1.0f, 1.0f, 1.0f, 1.0f); } - 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 (ny = minXY.y, input_xy.y = ny - offset_input.y ; ny < maxXY.y ; ny += step, input_xy.y += step) { + uv.y = ((real_coordinate.y-ny)/radius2)*bokeh_image_dim.y+bokeh_image_center.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); + for (nx = minXY.x, input_xy.x = nx - offset_input.x; nx < maxXY.x ; nx += step, input_xy.x += step) { + uv.x = ((real_coordinate.x-nx)/radius2)*bokeh_image_dim.x+bokeh_image_center.x; + bokeh = read_imagef(bokeh_image, SAMPLER_NEAREST, uv); + color += bokeh * read_imagef(input_image, SAMPLER_NEAREST, input_xy); multiplyer += bokeh; } } color /= multiplyer; } else { - color = read_imagef(inputImage, SAMPLER_NEAREST, imageCoordinates); + color = read_imagef(input_image, SAMPLER_NEAREST, image_coordinates); } 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 maxBlurScalar, float threshold, float scalar, int2 dimension, int2 offset) +__kernel void defocus_kernel(__read_only image2d_t input_image, __read_only image2d_t bokeh_image, + __read_only image2d_t input_size, + __write_only image2d_t output, int2 offset_input, int2 offset_output, + int step, int max_blur_scalar, float threshold, float scalar, 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; + const int2 real_coordinate = coords + offset_output; - float4 readColor; - float4 tempColor; + float4 read_color; + float4 temp_color; float4 bokeh; float size; float4 multiplier_accum = {1.0f, 1.0f, 1.0f, 1.0f}; float4 color_accum; - int minx = max(realCoordinate.s0 - maxBlurScalar, 0); - int miny = max(realCoordinate.s1 - maxBlurScalar, 0); - int maxx = min(realCoordinate.s0 + maxBlurScalar, dimension.s0); - int maxy = min(realCoordinate.s1 + maxBlurScalar, dimension.s1); + int minx = max(real_coordinate.s0 - max_blur_scalar, 0); + int miny = max(real_coordinate.s1 - max_blur_scalar, 0); + int maxx = min(real_coordinate.s0 + max_blur_scalar, dimension.s0); + int maxy = min(real_coordinate.s1 + max_blur_scalar, dimension.s1); { - int2 inputCoordinate = realCoordinate - offsetInput; - float size_center = read_imagef(inputSize, SAMPLER_NEAREST, inputCoordinate).s0 * scalar; - color_accum = read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate); - readColor = color_accum; + int2 input_coordinate = real_coordinate - offset_input; + float size_center = read_imagef(input_size, SAMPLER_NEAREST, input_coordinate).s0 * scalar; + color_accum = read_imagef(input_image, SAMPLER_NEAREST, input_coordinate); + read_color = color_accum; if (size_center > threshold) { for (int ny = miny; ny < maxy; ny += step) { - inputCoordinate.s1 = ny - offsetInput.s1; - float dy = ny - realCoordinate.s1; + input_coordinate.s1 = ny - offset_input.s1; + float dy = ny - real_coordinate.s1; for (int nx = minx; nx < maxx; nx += step) { - float dx = nx - realCoordinate.s0; + float dx = nx - real_coordinate.s0; if (dx != 0 || dy != 0) { - inputCoordinate.s0 = nx - offsetInput.s0; - size = min(read_imagef(inputSize, SAMPLER_NEAREST, inputCoordinate).s0 * scalar, size_center); + input_coordinate.s0 = nx - offset_input.s0; + size = min(read_imagef(input_size, SAMPLER_NEAREST, input_coordinate).s0 * scalar, size_center); if (size > threshold) { if (size >= fabs(dx) && size >= fabs(dy)) { float2 uv = {256.0f + dx * 255.0f / size, 256.0f + dy * 255.0f / size}; - bokeh = read_imagef(bokehImage, SAMPLER_NEAREST, uv); - tempColor = read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate); - color_accum += bokeh * tempColor; + bokeh = read_imagef(bokeh_image, SAMPLER_NEAREST, uv); + temp_color = read_imagef(input_image, SAMPLER_NEAREST, input_coordinate); + color_accum += bokeh * temp_color; multiplier_accum += bokeh; } } @@ -140,7 +140,7 @@ __kernel void defocusKernel(__read_only image2d_t inputImage, __read_only image2 { /* factor from 0-1 */ float fac = (size_center - threshold) / threshold; - color = (readColor * (1.0f - fac)) + (color * fac); + color = (read_color * (1.0f - fac)) + (color * fac); } write_imagef(output, coords, color); @@ -149,28 +149,28 @@ __kernel void defocusKernel(__read_only image2d_t inputImage, __read_only image2 // 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, +__kernel void dilate_kernel(__read_only image2d_t input_image, __write_only image2d_t output, + int2 offset_input, int2 offset_output, int scope, int distance_squared, int2 dimension, int2 offset) { int2 coords = {get_global_id(0), get_global_id(1)}; coords += offset; - const int2 realCoordinate = coords + offsetOutput; + const int2 real_coordinate = coords + offset_output; - const int2 minXY = max(realCoordinate - scope, zero); - const int2 maxXY = min(realCoordinate + scope, dimension); + const int2 minXY = max(real_coordinate - scope, zero); + const int2 maxXY = min(real_coordinate + scope, dimension); float value = 0.0f; int nx, ny; - int2 inputXy; + int2 input_xy; - 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); + for (ny = minXY.y, input_xy.y = ny - offset_input.y ; ny < maxXY.y ; ny ++, input_xy.y++) { + const float deltaY = (real_coordinate.y - ny); + for (nx = minXY.x, input_xy.x = nx - offset_input.x; nx < maxXY.x ; nx ++, input_xy.x++) { + const float deltaX = (real_coordinate.x - nx); + const float measured_distance = deltaX * deltaX + deltaY * deltaY; + if (measured_distance <= distance_squared) { + value = max(value, read_imagef(input_image, SAMPLER_NEAREST, input_xy).s0); } } } @@ -180,28 +180,28 @@ __kernel void dilateKernel(__read_only image2d_t inputImage, __write_only image } // 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, +__kernel void erode_kernel(__read_only image2d_t input_image, __write_only image2d_t output, + int2 offset_input, int2 offset_output, int scope, int distance_squared, int2 dimension, int2 offset) { int2 coords = {get_global_id(0), get_global_id(1)}; coords += offset; - const int2 realCoordinate = coords + offsetOutput; + const int2 real_coordinate = coords + offset_output; - const int2 minXY = max(realCoordinate - scope, zero); - const int2 maxXY = min(realCoordinate + scope, dimension); + const int2 minXY = max(real_coordinate - scope, zero); + const int2 maxXY = min(real_coordinate + scope, dimension); float value = 1.0f; int nx, ny; - int2 inputXy; + int2 input_xy; - 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); + for (ny = minXY.y, input_xy.y = ny - offset_input.y ; ny < maxXY.y ; ny ++, input_xy.y++) { + for (nx = minXY.x, input_xy.x = nx - offset_input.x; nx < maxXY.x ; nx ++, input_xy.x++) { + const float deltaX = (real_coordinate.x - nx); + const float deltaY = (real_coordinate.y - ny); + const float measured_distance = deltaX * deltaX+deltaY * deltaY; + if (measured_distance <= distance_squared) { + value = min(value, read_imagef(input_image, SAMPLER_NEAREST, input_xy).s0); } } } @@ -211,34 +211,34 @@ __kernel void erodeKernel(__read_only image2d_t inputImage, __write_only image2 } // 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, +__kernel void directional_blur_kernel(__read_only image2d_t input_image, __write_only image2d_t output, + int2 offset_output, 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; + const int2 real_coordinate = coords + offset_output; float4 col; float2 ltxy = translate; float lsc = scale; float lrot = rotation; - col = read_imagef(inputImage, SAMPLER_NEAREST, realCoordinate); + col = read_imagef(input_image, SAMPLER_NEAREST, real_coordinate); /* 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; + const float v = isc * (real_coordinate.s1 - center.s1) + ltxy.s1; + const float u = isc * (real_coordinate.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); + col += read_imagef(input_image, SAMPLER_NEAREST_CLAMP, uv); /* double transformations */ ltxy += translate; @@ -252,10 +252,10 @@ __kernel void directionalBlurKernel(__read_only image2d_t inputImage, __write_o } // KERNEL --- GAUSSIAN BLUR --- -__kernel void gaussianXBlurOperationKernel(__read_only image2d_t inputImage, - int2 offsetInput, +__kernel void gaussian_xblur_operation_kernel(__read_only image2d_t input_image, + int2 offset_input, __write_only image2d_t output, - int2 offsetOutput, + int2 offset_output, int filter_size, int2 dimension, __global float *gausstab, @@ -264,17 +264,17 @@ __kernel void gaussianXBlurOperationKernel(__read_only image2d_t inputImage, float4 color = {0.0f, 0.0f, 0.0f, 0.0f}; int2 coords = {get_global_id(0), get_global_id(1)}; coords += offset; - const int2 realCoordinate = coords + offsetOutput; - int2 inputCoordinate = realCoordinate - offsetInput; + const int2 real_coordinate = coords + offset_output; + int2 input_coordinate = real_coordinate - offset_input; float weight = 0.0f; - int xmin = max(realCoordinate.x - filter_size, 0) - offsetInput.x; - int xmax = min(realCoordinate.x + filter_size + 1, dimension.x) - offsetInput.x; + int xmin = max(real_coordinate.x - filter_size, 0) - offset_input.x; + int xmax = min(real_coordinate.x + filter_size + 1, dimension.x) - offset_input.x; - for (int nx = xmin, i = max(filter_size - realCoordinate.x, 0); nx < xmax; ++nx, ++i) { + for (int nx = xmin, i = max(filter_size - real_coordinate.x, 0); nx < xmax; ++nx, ++i) { float w = gausstab[i]; - inputCoordinate.x = nx; - color += read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate) * w; + input_coordinate.x = nx; + color += read_imagef(input_image, SAMPLER_NEAREST, input_coordinate) * w; weight += w; } @@ -283,10 +283,10 @@ __kernel void gaussianXBlurOperationKernel(__read_only image2d_t inputImage, write_imagef(output, coords, color); } -__kernel void gaussianYBlurOperationKernel(__read_only image2d_t inputImage, - int2 offsetInput, +__kernel void gaussian_yblur_operation_kernel(__read_only image2d_t input_image, + int2 offset_input, __write_only image2d_t output, - int2 offsetOutput, + int2 offset_output, int filter_size, int2 dimension, __global float *gausstab, @@ -295,17 +295,17 @@ __kernel void gaussianYBlurOperationKernel(__read_only image2d_t inputImage, float4 color = {0.0f, 0.0f, 0.0f, 0.0f}; int2 coords = {get_global_id(0), get_global_id(1)}; coords += offset; - const int2 realCoordinate = coords + offsetOutput; - int2 inputCoordinate = realCoordinate - offsetInput; + const int2 real_coordinate = coords + offset_output; + int2 input_coordinate = real_coordinate - offset_input; float weight = 0.0f; - int ymin = max(realCoordinate.y - filter_size, 0) - offsetInput.y; - int ymax = min(realCoordinate.y + filter_size + 1, dimension.y) - offsetInput.y; + int ymin = max(real_coordinate.y - filter_size, 0) - offset_input.y; + int ymax = min(real_coordinate.y + filter_size + 1, dimension.y) - offset_input.y; - for (int ny = ymin, i = max(filter_size - realCoordinate.y, 0); ny < ymax; ++ny, ++i) { + for (int ny = ymin, i = max(filter_size - real_coordinate.y, 0); ny < ymax; ++ny, ++i) { float w = gausstab[i]; - inputCoordinate.y = ny; - color += read_imagef(inputImage, SAMPLER_NEAREST, inputCoordinate) * w; + input_coordinate.y = ny; + color += read_imagef(input_image, SAMPLER_NEAREST, input_coordinate) * w; weight += w; } |