106 lines
3.3 KiB
JavaScript
106 lines
3.3 KiB
JavaScript
const canvas = document.getElementById("canvas");
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const ctx = canvas.getContext("2d");
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const img = new Image();
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img.crossOrigin = "anonymous";
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img.src = "/rose.png";
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img.onload = () => {
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/*canvas.offscreenCanvas = document.createElement("canvas");
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canvas.offscreenCanvas.height = img.height;
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canvas.offscreenCanvas.width = img.width;
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canvas.offscreenCanvas.getContext("2d").drawImage(img, 0, 0);
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*/
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ctx.drawImage(img, 0, 0);
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};
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function invert(imgData) {
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const data = imgData.data;
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for (let i = 0; i < data.length; i += 4) {
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//const avg = (data[i] + data[i + 1] + data[i + 2]) / 3;
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data[i] = 255 - data[i];
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data[i+1] = 255 - data[i+1];
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data[i+2] = 255 - data[i+2];
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}
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}
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function greyscale(imgData) {
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const data = imgData.data;
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for (let i = 0; i < data.length; i += 4) {
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const avg = (data[i] + data[i + 1] + data[i + 2]) / 3;
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data[i] = avg;
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data[i+1] = avg;
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data[i+2] = avg;
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}
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}
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function clamp(x, min, max) {
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return Math.min(Math.max(x, min), max);
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}
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function convolve(imageData, kernel) {
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const width = imageData.width;
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const height = imageData.height;
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const data = imageData.data;
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const out = new ImageData(width, height);
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const kernelSize = Math.sqrt(kernel.length); // Assuming kernel is square
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const halfKernel = Math.floor(kernelSize / 2);
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for (let y = 0; y < height; y++) {
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for (let x = 0; x < width; x++) {
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let r = 0, g = 0, b = 0;
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for (let ky = -halfKernel; ky <= halfKernel; ky++) {
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for (let kx = -halfKernel; kx <= halfKernel; kx++) {
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const px = x + kx;
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const py = y + ky;
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if (px >= 0 && px < width && py >= 0 && py < height) {
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const idx = (py * width + px) * 4;
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const kernelValue = kernel[(ky + halfKernel) * kernelSize + (kx + halfKernel)];
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r += data[idx] * kernelValue;
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g += data[idx + 1] * kernelValue;
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b += data[idx + 2] * kernelValue;
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}
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}
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}
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out.data[(y*width+x)*4] = r;
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out.data[(y*width+x)*4 + 1] = g;
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out.data[(y*width+x)*4 + 2] = b;
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out.data[(y*width+x)*4 + 3] = data[(y*width+x) * 4 + 3]; // preserve original alpha
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}
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}
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return out;
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}
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// multiply two 3x3 matrices
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function matMult(a, b) {
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const result = new Array(9).fill(0);
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for (let j = 0; j < 3; ++j){
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for (let i = 0; i < 3; ++i) {
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for (let k = 0; k < 3; ++k) {
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result[j*3+i] += a[j*3+k] * b[k*3+i];
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}
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}
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}
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return result;
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}
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canvas.onclick = () => {
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const imgData = ctx.getImageData(0, 0, canvas.width, canvas.height);
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ctx.clearRect(0, 0, canvas.height, canvas.width);
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//invert(imgData);
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//greyscale(imgData);
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//const identityKernel = [0, 0, 0, 0, 1, 0, 0, 0, 0];
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const gaussianKernel = [0.075, 0.124, 0.075, 0.124, 0.204, 0.124, 0.075, 0.124, 0.075]
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const convolved = convolve(imgData, gaussianKernel);
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ctx.putImageData(convolved, 0, 0);
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};
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const matrixA = [1, 2, 3, 4, 5, 6, 7, 8, 9];
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const matrixB = [9, 8, 7, 6, 5, 4, 3, 2, 1];
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const result = matMult(matrixA, matrixB);
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console.log(result);
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