diff --git a/examples/textures/textures_image_kernel.c b/examples/textures/textures_image_kernel.c index ba120f108..781e47d8c 100644 --- a/examples/textures/textures_image_kernel.c +++ b/examples/textures/textures_image_kernel.c @@ -9,7 +9,7 @@ * Example licensed under an unmodified zlib/libpng license, which is an OSI-certified, * BSD-like license that allows static linking with closed source software * -* Copyright (c) 2015-2023 Ramon Santamaria (@raysan5) +* Copyright (c) 2015-2023 Karim Salem (@kimo-s) * ********************************************************************************************/ @@ -25,8 +25,8 @@ int main(void) Image image = LoadImage("resources/cat.png"); // Loaded in CPU memory (RAM) - const int screenWidth = image.width*4; - const int screenHeight = image.height; + const int screenWidth = 800; + const int screenHeight = 450; InitWindow(screenWidth, screenHeight, "raylib [textures] example - image convolution"); @@ -43,18 +43,20 @@ int main(void) 0.0, -1.0, 0.0}; Image catSharpend = ImageCopy(image); - ImageKernelConvolution(&catSharpend, sharpenkernel, 3); + ImageKernelConvolution(&catSharpend, sharpenkernel, 16); - Image catSobel = ImageCopy(image); - ImageKernelConvolution(&catSobel, sobelkernel, 3); + ImageKernelConvolution(&catSobel, sobelkernel, 16); Image catGaussian = ImageCopy(image); for(int i = 0; i < 6; i++){ - ImageKernelConvolution(&catGaussian, gaussiankernel, 3); + ImageKernelConvolution(&catGaussian, gaussiankernel, 16); } - + ImageCrop(&image, (Rectangle){ 0, 0, (float)200, (float)450 }); + ImageCrop(&catGaussian, (Rectangle){ 0, 0, (float)200, (float)450 }); + ImageCrop(&catSobel, (Rectangle){ 0, 0, (float)200, (float)450 }); + ImageCrop(&catSharpend, (Rectangle){ 0, 0, (float)200, (float)450 }); Texture2D texture = LoadTextureFromImage(image); // Image converted to texture, GPU memory (VRAM) Texture2D catSharpendTexture = LoadTextureFromImage(catSharpend); Texture2D catSobelTexture = LoadTextureFromImage(catSobel); @@ -82,9 +84,9 @@ int main(void) ClearBackground(RAYWHITE); DrawTexture(catSharpendTexture, 0, 0, WHITE); - DrawTexture(catSobelTexture, texture.width, 0, WHITE); - DrawTexture(catGaussianTexture, texture.width*2, 0, WHITE); - DrawTexture(texture, texture.width*3, 0, WHITE); + DrawTexture(catSobelTexture, 200, 0, WHITE); + DrawTexture(catGaussianTexture, 400, 0, WHITE); + DrawTexture(texture, 600, 0, WHITE); EndDrawing(); //---------------------------------------------------------------------------------- diff --git a/projects/Notepad++/raylib_npp_parser/raylib_to_parse.h b/projects/Notepad++/raylib_npp_parser/raylib_to_parse.h index 364265ef3..58dc94f54 100644 --- a/projects/Notepad++/raylib_npp_parser/raylib_to_parse.h +++ b/projects/Notepad++/raylib_npp_parser/raylib_to_parse.h @@ -339,7 +339,7 @@ RLAPI void ImageAlphaClear(Image *image, Color color, float threshold); RLAPI void ImageAlphaMask(Image *image, Image alphaMask); // Apply alpha mask to image RLAPI void ImageAlphaPremultiply(Image *image); // Premultiply alpha channel RLAPI void ImageBlurGaussian(Image *image, int blurSize); // Apply Gaussian blur using a box blur approximation -RLAPI void ImageKernelConvolution(Image *image, float* karnel, int karenlWidth); // Apply Custom Square image convolution kernel +RLAPI void ImageKernelConvolution(Image *image, float* kernel, int kernelSize); // Apply Custom Square image convolution kernel RLAPI void ImageResize(Image *image, int newWidth, int newHeight); // Resize image (Bicubic scaling algorithm) RLAPI void ImageResizeNN(Image *image, int newWidth,int newHeight); // Resize image (Nearest-Neighbor scaling algorithm) RLAPI void ImageResizeCanvas(Image *image, int newWidth, int newHeight, int offsetX, int offsetY, Color fill); // Resize canvas and fill with color diff --git a/src/raylib.h b/src/raylib.h index 4c1755715..43ee5f8fe 100644 --- a/src/raylib.h +++ b/src/raylib.h @@ -1329,7 +1329,7 @@ RLAPI void ImageAlphaClear(Image *image, Color color, float threshold); RLAPI void ImageAlphaMask(Image *image, Image alphaMask); // Apply alpha mask to image RLAPI void ImageAlphaPremultiply(Image *image); // Premultiply alpha channel RLAPI void ImageBlurGaussian(Image *image, int blurSize); // Apply Gaussian blur using a box blur approximation -RLAPI void ImageKernelConvolution(Image *image, float* karnel, int karenlWidth); // Apply Custom Square image convolution kernel +RLAPI void ImageKernelConvolution(Image *image, float* kernel, int kernelSize); // Apply Custom Square image convolution kernel RLAPI void ImageResize(Image *image, int newWidth, int newHeight); // Resize image (Bicubic scaling algorithm) RLAPI void ImageResizeNN(Image *image, int newWidth,int newHeight); // Resize image (Nearest-Neighbor scaling algorithm) RLAPI void ImageResizeCanvas(Image *image, int newWidth, int newHeight, int offsetX, int offsetY, Color fill); // Resize canvas and fill with color diff --git a/src/rtextures.c b/src/rtextures.c index 0572692a2..7cc38d14a 100644 --- a/src/rtextures.c +++ b/src/rtextures.c @@ -2083,90 +2083,100 @@ void ImageBlurGaussian(Image *image, int blurSize) { } // The kernel matrix is assumed to be square. Only supply the width of the kernel. -void ImageKernelConvolution(Image *image, float* karnel, int karenlWidth){ +void ImageKernelConvolution(Image *image, float* kernel, int kernelSize){ - if ((image->data == NULL) || (image->width == 0) || (image->height == 0) || karnel == NULL) return; + if ((image->data == NULL) || (image->width == 0) || (image->height == 0) || kernel == NULL) return; - ImageAlphaPremultiply(image); + int kernelWidth = (int)sqrtf((float)kernelSize); + if (kernelWidth*kernelWidth != kernelSize) + { + TRACELOG(LOG_WARNING, "IMAGE: Convolution kernel must be square to be applied"); + return; + } Color *pixels = LoadImageColors(*image); - Vector4 *imageCopy1 = RL_MALLOC((image->height)*(image->width)*sizeof(Vector4)); Vector4 *imageCopy2 = RL_MALLOC((image->height)*(image->width)*sizeof(Vector4)); - Vector4 *temp = RL_MALLOC(karenlWidth*karenlWidth*sizeof(Vector4)); + Vector4 *temp = RL_MALLOC(kernelSize*sizeof(Vector4)); float normKernel = 0.0f; - for(int i = 0; i < karenlWidth * karenlWidth; i++){ + for(int i = 0; i < kernelSize; i++){ temp[i].x = 0.0f; temp[i].y = 0.0f; temp[i].z = 0.0f; temp[i].w = 0.0f; - normKernel += karnel[i]; + normKernel += kernel[i]; } if(normKernel != 0.0f){ - for(int i = 0; i < karenlWidth * karenlWidth; i++){ - karnel[i] /= normKernel; + for(int i = 0; i < kernelSize; i++){ + kernel[i] /= normKernel; } } - float rRes = 0.0f; float gRes = 0.0f; float bRes = 0.0f; float aRes = 0.0f; - for (int i = 0; i < (image->height)*(image->width); i++) { - imageCopy1[i].x = ((float)pixels[i].r)/255.0f; - imageCopy1[i].y = ((float)pixels[i].g)/255.0f; - imageCopy1[i].z = ((float)pixels[i].b)/255.0f; - imageCopy1[i].w = ((float)pixels[i].a)/255.0f; - } - - int startRange, endRange; - if(karenlWidth % 2 == 0){ - startRange = -karenlWidth/2; - endRange = karenlWidth/2; + if(kernelWidth % 2 == 0){ + startRange = -kernelWidth/2; + endRange = kernelWidth/2; } else { - startRange = -karenlWidth/2; - endRange = karenlWidth/2+1; + startRange = -kernelWidth/2; + endRange = kernelWidth/2+1; } for(int x = 0; x < image->height; x++) { for(int y = 0; y < image->width; y++) { for(int xk = startRange; xk < endRange; xk++){ for(int yk = startRange; yk < endRange; yk++){ - int xkabs = xk + karenlWidth/2; - int ykabs = yk + karenlWidth/2; + int xkabs = xk + kernelWidth/2; + int ykabs = yk + kernelWidth/2; size_t imgindex = image->width * (x+xk) + (y+yk); if(imgindex < 0 || imgindex >= image->width * image->height){ - temp[karenlWidth * xkabs + ykabs].x = 0.0f; - temp[karenlWidth * xkabs + ykabs].y = 0.0f; - temp[karenlWidth * xkabs + ykabs].z = 0.0f; - temp[karenlWidth * xkabs + ykabs].w = 0.0f; + temp[kernelWidth * xkabs + ykabs].x = 0.0f; + temp[kernelWidth * xkabs + ykabs].y = 0.0f; + temp[kernelWidth * xkabs + ykabs].z = 0.0f; + temp[kernelWidth * xkabs + ykabs].w = 0.0f; } else { - temp[karenlWidth * xkabs + ykabs].x = imageCopy1[imgindex].x * karnel[karenlWidth * xkabs + ykabs]; - temp[karenlWidth * xkabs + ykabs].y = imageCopy1[imgindex].y * karnel[karenlWidth * xkabs + ykabs]; - temp[karenlWidth * xkabs + ykabs].z = imageCopy1[imgindex].z * karnel[karenlWidth * xkabs + ykabs]; - temp[karenlWidth * xkabs + ykabs].w = imageCopy1[imgindex].w * karnel[karenlWidth * xkabs + ykabs]; + temp[kernelWidth * xkabs + ykabs].x = ((float)pixels[imgindex].r)/255.0f * kernel[kernelWidth * xkabs + ykabs]; + temp[kernelWidth * xkabs + ykabs].y = ((float)pixels[imgindex].g)/255.0f * kernel[kernelWidth * xkabs + ykabs]; + temp[kernelWidth * xkabs + ykabs].z = ((float)pixels[imgindex].b)/255.0f * kernel[kernelWidth * xkabs + ykabs]; + temp[kernelWidth * xkabs + ykabs].w = ((float)pixels[imgindex].a)/255.0f * kernel[kernelWidth * xkabs + ykabs]; } } } - for(int i = 0; i < karenlWidth * karenlWidth; i++){ + for(int i = 0; i < kernelSize; i++){ rRes += temp[i].x; gRes += temp[i].y; bRes += temp[i].z; aRes += temp[i].w; } - STBIR_CLAMP(rRes, 0.0f, 1.0f); - STBIR_CLAMP(gRes, 0.0f, 1.0f); - STBIR_CLAMP(bRes, 0.0f, 1.0f); - STBIR_CLAMP(aRes, 0.0f, 1.0f); + if(rRes < 0.0f){ + rRes = 0.0f; + } + if(gRes < 0.0f){ + gRes = 0.0f; + } + if(bRes < 0.0f){ + bRes = 0.0f; + } + + if(rRes > 1.0f){ + rRes = 1.0f; + } + if(gRes > 1.0f){ + gRes = 1.0f; + } + if(bRes > 1.0f){ + bRes = 1.0f; + } imageCopy2[image->width * (x) + (y)].x = rRes; imageCopy2[image->width * (x) + (y)].y = gRes; @@ -2178,7 +2188,7 @@ void ImageKernelConvolution(Image *image, float* karnel, int karenlWidth){ bRes = 0.0f; aRes = 0.0f; - for(int i = 0; i < karenlWidth * karenlWidth; i++){ + for(int i = 0; i < kernelSize; i++){ temp[i].x = 0.0f; temp[i].y = 0.0f; temp[i].z = 0.0f; @@ -2199,7 +2209,6 @@ void ImageKernelConvolution(Image *image, float* karnel, int karenlWidth){ int format = image->format; RL_FREE(image->data); - RL_FREE(imageCopy1); RL_FREE(imageCopy2); RL_FREE(temp);