Image convolution function ImageKernelConvolution (#3528)
* Added image convultion ImageKernelConvolution * comment changes * spelling changes and change to kernel size * removed kernel normalization inside function * fix to formating
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@ -490,6 +490,7 @@ TEXTURES = \
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textures/textures_gif_player \
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textures/textures_gif_player \
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textures/textures_image_drawing \
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textures/textures_image_drawing \
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textures/textures_image_generation \
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textures/textures_image_generation \
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textures/textures_image_kernel \
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textures/textures_image_loading \
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textures/textures_image_loading \
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textures/textures_image_processing \
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textures/textures_image_processing \
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textures/textures_image_rotate \
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textures/textures_image_rotate \
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127
examples/textures/textures_image_kernel.c
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127
examples/textures/textures_image_kernel.c
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@ -0,0 +1,127 @@
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/*******************************************************************************************
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*
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* raylib [textures] example - Image loading and texture creation
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*
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* NOTE: Images are loaded in CPU memory (RAM); textures are loaded in GPU memory (VRAM)
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*
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* Example originally created with raylib 1.3, last time updated with raylib 1.3
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*
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* Example licensed under an unmodified zlib/libpng license, which is an OSI-certified,
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* BSD-like license that allows static linking with closed source software
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*
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* Copyright (c) 2015-2023 Karim Salem (@kimo-s)
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*
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********************************************************************************************/
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#include "raylib.h"
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//------------------------------------------------------------------------------------
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// Program main entry point
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//------------------------------------------------------------------------------------
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void normalizeKernel(float *kernel, int size){
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float sum = 0.0f;
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for(int i = 0; i < size; i++)
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{
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sum += kernel[i];
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}
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if(sum != 0.0f)
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{
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for(int i = 0; i < size; i++)
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{
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kernel[i] /= sum;
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}
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}
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}
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int main(void)
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{
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// Initialization
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//--------------------------------------------------------------------------------------
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Image image = LoadImage("resources/cat.png"); // Loaded in CPU memory (RAM)
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const int screenWidth = 800;
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const int screenHeight = 450;
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InitWindow(screenWidth, screenHeight, "raylib [textures] example - image convolution");
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float gaussiankernel[] = {1.0, 2.0, 1.0,
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2.0, 4.0, 2.0,
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1.0, 2.0, 1.0};
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float sobelkernel[] = {1.0, 0.0, -1.0,
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2.0, 0.0, -2.0,
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1.0, 0.0, -1.0};
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float sharpenkernel[] = {0.0, -1.0, 0.0,
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-1.0, 5.0, -1.0,
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0.0, -1.0, 0.0};
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normalizeKernel(gaussiankernel, 9);
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normalizeKernel(sharpenkernel, 9);
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normalizeKernel(sobelkernel, 9);
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Image catSharpend = ImageCopy(image);
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ImageKernelConvolution(&catSharpend, sharpenkernel, 9);
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Image catSobel = ImageCopy(image);
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ImageKernelConvolution(&catSobel, sobelkernel, 9);
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Image catGaussian = ImageCopy(image);
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for(int i = 0; i < 6; i++)
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{
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ImageKernelConvolution(&catGaussian, gaussiankernel, 9);
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}
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ImageCrop(&image, (Rectangle){ 0, 0, (float)200, (float)450 });
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ImageCrop(&catGaussian, (Rectangle){ 0, 0, (float)200, (float)450 });
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ImageCrop(&catSobel, (Rectangle){ 0, 0, (float)200, (float)450 });
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ImageCrop(&catSharpend, (Rectangle){ 0, 0, (float)200, (float)450 });
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Texture2D texture = LoadTextureFromImage(image); // Image converted to texture, GPU memory (VRAM)
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Texture2D catSharpendTexture = LoadTextureFromImage(catSharpend);
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Texture2D catSobelTexture = LoadTextureFromImage(catSobel);
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Texture2D catGaussianTexture = LoadTextureFromImage(catGaussian);
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UnloadImage(image); // Once image has been converted to texture and uploaded to VRAM, it can be unloaded from RAM
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UnloadImage(catGaussian);
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UnloadImage(catSobel);
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UnloadImage(catSharpend);
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SetTargetFPS(60); // Set our game to run at 60 frames-per-second
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//---------------------------------------------------------------------------------------
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// Main game loop
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while (!WindowShouldClose()) // Detect window close button or ESC key
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{
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// Update
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//----------------------------------------------------------------------------------
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// TODO: Update your variables here
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//----------------------------------------------------------------------------------
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// Draw
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//----------------------------------------------------------------------------------
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BeginDrawing();
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ClearBackground(RAYWHITE);
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DrawTexture(catSharpendTexture, 0, 0, WHITE);
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DrawTexture(catSobelTexture, 200, 0, WHITE);
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DrawTexture(catGaussianTexture, 400, 0, WHITE);
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DrawTexture(texture, 600, 0, WHITE);
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EndDrawing();
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//----------------------------------------------------------------------------------
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}
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// De-Initialization
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//--------------------------------------------------------------------------------------
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UnloadTexture(texture); // Texture unloading
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UnloadTexture(catGaussianTexture);
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UnloadTexture(catSobelTexture);
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UnloadTexture(catSharpendTexture);
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CloseWindow(); // Close window and OpenGL context
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//--------------------------------------------------------------------------------------
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return 0;
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}
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@ -375,6 +375,7 @@ RLAPI void ImageAlphaClear(Image *image, Color color, float threshold);
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RLAPI void ImageAlphaMask(Image *image, Image alphaMask); // Apply alpha mask to image
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RLAPI void ImageAlphaMask(Image *image, Image alphaMask); // Apply alpha mask to image
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RLAPI void ImageAlphaPremultiply(Image *image); // Premultiply alpha channel
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RLAPI void ImageAlphaPremultiply(Image *image); // Premultiply alpha channel
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RLAPI void ImageBlurGaussian(Image *image, int blurSize); // Apply Gaussian blur using a box blur approximation
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RLAPI void ImageBlurGaussian(Image *image, int blurSize); // Apply Gaussian blur using a box blur approximation
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RLAPI void ImageKernelConvolution(Image *image, float* kernel, int kernelSize); // Apply Custom Square image convolution kernel
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RLAPI void ImageResize(Image *image, int newWidth, int newHeight); // Resize image (Bicubic scaling algorithm)
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RLAPI void ImageResize(Image *image, int newWidth, int newHeight); // Resize image (Bicubic scaling algorithm)
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RLAPI void ImageResizeNN(Image *image, int newWidth,int newHeight); // Resize image (Nearest-Neighbor scaling algorithm)
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RLAPI void ImageResizeNN(Image *image, int newWidth,int newHeight); // Resize image (Nearest-Neighbor scaling algorithm)
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RLAPI void ImageResizeCanvas(Image *image, int newWidth, int newHeight, int offsetX, int offsetY, Color fill); // Resize canvas and fill with color
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RLAPI void ImageResizeCanvas(Image *image, int newWidth, int newHeight, int offsetX, int offsetY, Color fill); // Resize canvas and fill with color
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@ -1329,6 +1329,7 @@ RLAPI void ImageAlphaClear(Image *image, Color color, float threshold);
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RLAPI void ImageAlphaMask(Image *image, Image alphaMask); // Apply alpha mask to image
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RLAPI void ImageAlphaMask(Image *image, Image alphaMask); // Apply alpha mask to image
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RLAPI void ImageAlphaPremultiply(Image *image); // Premultiply alpha channel
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RLAPI void ImageAlphaPremultiply(Image *image); // Premultiply alpha channel
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RLAPI void ImageBlurGaussian(Image *image, int blurSize); // Apply Gaussian blur using a box blur approximation
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RLAPI void ImageBlurGaussian(Image *image, int blurSize); // Apply Gaussian blur using a box blur approximation
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RLAPI void ImageKernelConvolution(Image *image, float* kernel, int kernelSize); // Apply Custom Square image convolution kernel
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RLAPI void ImageResize(Image *image, int newWidth, int newHeight); // Resize image (Bicubic scaling algorithm)
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RLAPI void ImageResize(Image *image, int newWidth, int newHeight); // Resize image (Bicubic scaling algorithm)
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RLAPI void ImageResizeNN(Image *image, int newWidth,int newHeight); // Resize image (Nearest-Neighbor scaling algorithm)
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RLAPI void ImageResizeNN(Image *image, int newWidth,int newHeight); // Resize image (Nearest-Neighbor scaling algorithm)
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RLAPI void ImageResizeCanvas(Image *image, int newWidth, int newHeight, int offsetX, int offsetY, Color fill); // Resize canvas and fill with color
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RLAPI void ImageResizeCanvas(Image *image, int newWidth, int newHeight, int offsetX, int offsetY, Color fill); // Resize canvas and fill with color
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142
src/rtextures.c
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src/rtextures.c
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@ -2082,6 +2082,148 @@ void ImageBlurGaussian(Image *image, int blurSize) {
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ImageFormat(image, format);
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ImageFormat(image, format);
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}
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}
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// The kernel matrix is assumed to be square. Only supply the width of the kernel.
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void ImageKernelConvolution(Image *image, float* kernel, int kernelSize){
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if ((image->data == NULL) || (image->width == 0) || (image->height == 0) || kernel == NULL) return;
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int kernelWidth = (int)sqrtf((float)kernelSize);
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if (kernelWidth*kernelWidth != kernelSize)
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{
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TRACELOG(LOG_WARNING, "IMAGE: Convolution kernel must be square to be applied");
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return;
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}
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Color *pixels = LoadImageColors(*image);
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Vector4 *imageCopy2 = RL_MALLOC((image->height)*(image->width)*sizeof(Vector4));
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Vector4 *temp = RL_MALLOC(kernelSize*sizeof(Vector4));
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for(int i = 0; i < kernelSize; i++){
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temp[i].x = 0.0f;
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temp[i].y = 0.0f;
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temp[i].z = 0.0f;
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temp[i].w = 0.0f;
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}
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float rRes = 0.0f;
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float gRes = 0.0f;
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float bRes = 0.0f;
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float aRes = 0.0f;
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int startRange, endRange;
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if(kernelWidth % 2 == 0)
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{
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startRange = -kernelWidth/2;
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endRange = kernelWidth/2;
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} else
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{
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startRange = -kernelWidth/2;
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endRange = kernelWidth/2+1;
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}
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for(int x = 0; x < image->height; x++)
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{
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for(int y = 0; y < image->width; y++)
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{
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for(int xk = startRange; xk < endRange; xk++)
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{
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for(int yk = startRange; yk < endRange; yk++)
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{
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int xkabs = xk + kernelWidth/2;
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int ykabs = yk + kernelWidth/2;
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size_t imgindex = image->width * (x+xk) + (y+yk);
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if(imgindex < 0 || imgindex >= image->width * image->height){
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temp[kernelWidth * xkabs + ykabs].x = 0.0f;
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temp[kernelWidth * xkabs + ykabs].y = 0.0f;
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temp[kernelWidth * xkabs + ykabs].z = 0.0f;
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temp[kernelWidth * xkabs + ykabs].w = 0.0f;
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} else {
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temp[kernelWidth * xkabs + ykabs].x = ((float)pixels[imgindex].r)/255.0f * kernel[kernelWidth * xkabs + ykabs];
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temp[kernelWidth * xkabs + ykabs].y = ((float)pixels[imgindex].g)/255.0f * kernel[kernelWidth * xkabs + ykabs];
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temp[kernelWidth * xkabs + ykabs].z = ((float)pixels[imgindex].b)/255.0f * kernel[kernelWidth * xkabs + ykabs];
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temp[kernelWidth * xkabs + ykabs].w = ((float)pixels[imgindex].a)/255.0f * kernel[kernelWidth * xkabs + ykabs];
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}
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}
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}
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for(int i = 0; i < kernelSize; i++)
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{
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rRes += temp[i].x;
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gRes += temp[i].y;
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bRes += temp[i].z;
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aRes += temp[i].w;
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}
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if(rRes < 0.0f)
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{
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rRes = 0.0f;
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}
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if(gRes < 0.0f)
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{
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gRes = 0.0f;
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}
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if(bRes < 0.0f)
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{
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bRes = 0.0f;
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}
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if(rRes > 1.0f)
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{
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rRes = 1.0f;
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}
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if(gRes > 1.0f)
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{
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gRes = 1.0f;
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}
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if(bRes > 1.0f)
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{
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bRes = 1.0f;
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}
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imageCopy2[image->width * (x) + (y)].x = rRes;
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imageCopy2[image->width * (x) + (y)].y = gRes;
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imageCopy2[image->width * (x) + (y)].z = bRes;
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imageCopy2[image->width * (x) + (y)].w = aRes;
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rRes = 0.0f;
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gRes = 0.0f;
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bRes = 0.0f;
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aRes = 0.0f;
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for(int i = 0; i < kernelSize; i++)
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{
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temp[i].x = 0.0f;
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temp[i].y = 0.0f;
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temp[i].z = 0.0f;
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temp[i].w = 0.0f;
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}
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}
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}
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for (int i = 0; i < (image->width) * (image->height); i++)
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{
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float alpha = (float)imageCopy2[i].w;
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pixels[i].r = (unsigned char)((imageCopy2[i].x)*255.0f);
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pixels[i].g = (unsigned char)((imageCopy2[i].y)*255.0f);
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pixels[i].b = (unsigned char)((imageCopy2[i].z)*255.0f);
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pixels[i].a = (unsigned char)((alpha)*255.0f);
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// printf("pixels[%d] = %d", i, pixels[i].r);
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}
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int format = image->format;
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RL_FREE(image->data);
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RL_FREE(imageCopy2);
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RL_FREE(temp);
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image->data = pixels;
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image->format = PIXELFORMAT_UNCOMPRESSED_R8G8B8A8;
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ImageFormat(image, format);
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}
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// Generate all mipmap levels for a provided image
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// Generate all mipmap levels for a provided image
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// NOTE 1: Supports POT and NPOT images
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// NOTE 1: Supports POT and NPOT images
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// NOTE 2: image.data is scaled to include mipmap levels
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// NOTE 2: image.data is scaled to include mipmap levels
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