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Added image convultion ImageKernelConvolution

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kimo-s 2023-11-11 17:24:10 -05:00
parent 1b88f2ec03
commit 590f714c26
5 changed files with 233 additions and 0 deletions
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1
examples/Makefile
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@ -490,6 +490,7 @@ TEXTURES = \
textures/textures_gif_player \
textures/textures_image_drawing \
textures/textures_image_generation \
textures/textures_image_kernel \
textures/textures_image_loading \
textures/textures_image_processing \
textures/textures_image_rotate \

104
examples/textures/textures_image_kernel.c Normal file
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@ -0,0 +1,104 @@
/*******************************************************************************************
*
* raylib [textures] example - Image loading and texture creation
*
* NOTE: Images are loaded in CPU memory (RAM); textures are loaded in GPU memory (VRAM)
*
* Example originally created with raylib 1.3, last time updated with raylib 1.3
*
* 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)
*
********************************************************************************************/
#include "raylib.h"
//------------------------------------------------------------------------------------
// Program main entry point
//------------------------------------------------------------------------------------
int main(void)
{
// Initialization
//--------------------------------------------------------------------------------------
Image image = LoadImage("resources/cat.png"); // Loaded in CPU memory (RAM)
const int screenWidth = image.width*4;
const int screenHeight = image.height;
InitWindow(screenWidth, screenHeight, "raylib [textures] example - image convolution");
float gaussiankernel[] = {1.0, 2.0, 1.0,
2.0, 4.0, 2.0,
1.0, 2.0, 1.0};
float sobelkernel[] = {1.0, 0.0, -1.0,
2.0, 0.0, -2.0,
1.0, 0.0, -1.0};
float sharpenkernel[] = {0.0, 1.0, 0.0,
-1.0, 5.0, -1.0,
0.0, -1.0, 0.0};
Image catSharpend = ImageCopy(image);
ImageKernelConvolution(&catSharpend, sharpenkernel, 3);
Image catSobel = ImageCopy(image);
ImageKernelConvolution(&catSobel, sobelkernel, 3);
Image catGaussian = ImageCopy(image);
for(int i = 0; i < 6; i++){
ImageKernelConvolution(&catGaussian, gaussiankernel, 3);
}
Texture2D texture = LoadTextureFromImage(image); // Image converted to texture, GPU memory (VRAM)
Texture2D catSharpendTexture = LoadTextureFromImage(catSharpend);
Texture2D catSobelTexture = LoadTextureFromImage(catSobel);
Texture2D catGaussianTexture = LoadTextureFromImage(catGaussian);
UnloadImage(image); // Once image has been converted to texture and uploaded to VRAM, it can be unloaded from RAM
UnloadImage(catGaussian);
UnloadImage(catSobel);
UnloadImage(catSharpend);
SetTargetFPS(60); // Set our game to run at 60 frames-per-second
//---------------------------------------------------------------------------------------
// Main game loop
while (!WindowShouldClose()) // Detect window close button or ESC key
{
// Update
//----------------------------------------------------------------------------------
// TODO: Update your variables here
//----------------------------------------------------------------------------------
// Draw
//----------------------------------------------------------------------------------
BeginDrawing();
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);
EndDrawing();
//----------------------------------------------------------------------------------
}
// De-Initialization
//--------------------------------------------------------------------------------------
UnloadTexture(texture); // Texture unloading
UnloadTexture(catGaussianTexture);
UnloadTexture(catSobelTexture);
UnloadTexture(catSharpendTexture);
CloseWindow(); // Close window and OpenGL context
//--------------------------------------------------------------------------------------
return 0;
}

1
projects/Notepad++/raylib_npp_parser/raylib_to_parse.h
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@ -339,6 +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 Gaussian blur using a box blur approximation
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

1
src/raylib.h
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@ -1329,6 +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 Gaussian blur using a box blur approximation
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

126
src/rtextures.c
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@ -2082,6 +2082,132 @@ void ImageBlurGaussian(Image *image, int blurSize) {
ImageFormat(image, format);
}
// The kernel matrix is assumed to be square. Only supply the width of the kernel.
void ImageKernelConvolution(Image *image, float* karnel, int karenlWidth){
if ((image->data == NULL) || (image->width == 0) || (image->height == 0) || karnel == NULL) return;
ImageAlphaPremultiply(image);
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));
float normKernel = 0.0f;
for(int i = 0; i < karenlWidth * karenlWidth; i++){
temp[i].x = 0.0f;
temp[i].y = 0.0f;
temp[i].z = 0.0f;
temp[i].w = 0.0f;
normKernel += karnel[i];
}
if(normKernel != 0.0f){
for(int i = 0; i < karenlWidth * karenlWidth; i++){
karnel[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;
} else {
startRange = -karenlWidth/2;
endRange = karenlWidth/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;
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;
} 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];
}
}
}
for(int i = 0; i < karenlWidth * karenlWidth; 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);
imageCopy2[image->width * (x) + (y)].x = rRes;
imageCopy2[image->width * (x) + (y)].y = gRes;
imageCopy2[image->width * (x) + (y)].z = bRes;
imageCopy2[image->width * (x) + (y)].w = aRes;
rRes = 0.0f;
gRes = 0.0f;
bRes = 0.0f;
aRes = 0.0f;
for(int i = 0; i < karenlWidth * karenlWidth; i++){
temp[i].x = 0.0f;
temp[i].y = 0.0f;
temp[i].z = 0.0f;
temp[i].w = 0.0f;
}
}
}
for (int i = 0; i < (image->width)*(image->height); i++) {
float alpha = (float)imageCopy2[i].w;
pixels[i].r = (unsigned char)((imageCopy2[i].x)*255.0f);
pixels[i].g = (unsigned char)((imageCopy2[i].y)*255.0f);
pixels[i].b = (unsigned char)((imageCopy2[i].z)*255.0f);
pixels[i].a = (unsigned char)((alpha)*255.0f);
// printf("pixels[%d] = %d", i, pixels[i].r);
}
int format = image->format;
RL_FREE(image->data);
RL_FREE(imageCopy1);
RL_FREE(imageCopy2);
RL_FREE(temp);
image->data = pixels;
image->format = PIXELFORMAT_UNCOMPRESSED_R8G8B8A8;
ImageFormat(image, format);
}
// Generate all mipmap levels for a provided image
// NOTE 1: Supports POT and NPOT images
// NOTE 2: image.data is scaled to include mipmap levels