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import { interceptPost, interceptGet } from "@/shared/intercept-jquery-ajax";
function prepareCaptcha(ctx: CanvasRenderingContext2D, width: number, height: number) {
const imgData = ctx.getImageData(0, 0, width, height);
const data = imgData.data;
const radius = 1;
function isBlack(r: number, g: number, b: number) {
return r < 50 && g < 50 && b < 50;
}
function isGrayish(r: number, g: number, b: number) {
return Math.abs(r - g) < 15 && Math.abs(g - b) < 15 && r > 100 && r < 200;
}
function hasNearbyBlack(x: number, y: number) {
for (let dx = -radius; dx <= radius; dx++) {
for (let dy = -radius; dy <= radius; dy++) {
const nx = x + dx;
const ny = y + dy;
if (nx >= 0 && nx < width && ny >= 0 && ny < height) {
const i = (ny * width + nx) * 4;
if (isBlack(data[i], data[i + 1], data[i + 2])) return true;
}
}
}
return false;
}
for (let y = 0; y < height; y++) {
for (let x = 0; x < width; x++) {
const i = (y * width + x) * 4;
const [r, g, b] = [data[i], data[i + 1], data[i + 2]];
if (isGrayish(r, g, b) && !hasNearbyBlack(x, y)) {
data[i] = data[i + 1] = data[i + 2] = 255;
}
}
}
for (let y = 0; y < height; y++) {
for (let x = 0; x < width; x++) {
const i = (y * width + x) * 4;
const [r, g, b] = [data[i], data[i + 1], data[i + 2]];
if (isGrayish(r, g, b)) {
data[i] = data[i + 1] = data[i + 2] = 0; // make black
}
}
}
ctx.putImageData(imgData, 0, 0);
}
const observer = new MutationObserver((mutationsList, obs) => {
for (const mutation of mutationsList) {
for (const node of mutation.addedNodes) {
if ((node as any).nodeType === 1 && (node as any).id === "loginform") {
const img = (node as HTMLFormElement).querySelector("#captchaImg") as HTMLImageElement;
const captchaInput = (node as HTMLFormElement).querySelector("txtInput") as HTMLInputElement;
// Wait for image to load to get correct dimensions
img.addEventListener("load", async () => {
const { width, height } = img;
// 1. Create canvas
const canvas = document.createElement("canvas");
canvas.width = width;
canvas.height = height;
canvas.style.display = "block";
// 2. Copy styles (optional)
canvas.style.cssText = getComputedStyle(img).cssText;
canvas.style.display = "none";
// 3. Insert canvas before image
img.parentNode!.querySelectorAll("canvas").forEach(c => c.remove());
img.parentNode!.insertBefore(canvas, img);
// 4. Hide image
img.style.display = "none";
// 5. Draw the image onto the canvas
const ctx = canvas.getContext("2d")!;
ctx.drawImage(img, 0, 0);
prepareCaptcha(ctx, canvas.width, canvas.height);
canvas.style.display = "";
const dataURL = canvas.toDataURL("image/png");
chrome.runtime.sendMessage({ type: "OCR", dataURL }, console.log);
// TODO: Perform OCR
// window.postMessage({
// type: "RUN_OCR",
// dataURL: dataURL
// }, "*");
//
// // Listen for OCR result
// function recieveOCRResult(event: any) {
// if (event.data.type === "OCR_RESULT") {
// console.log("Tesseract result:", event.data.text, "Confidence:", event.data.confidence);
// window.removeEventListener("message", recieveOCRResult);
// if (event.data.confidence < 80 || event.data.text.length !== 6) {
// img.src = "generateCaptcha?" + new Date().getTime();
// } else {
// captchaInput.value = event.data.text;
// }
// }
// }
// window.addEventListener("message", recieveOCRResult);
});
}
}
}
});
// Start observing the body
observer.observe(document.body, { childList: true, subtree: true });
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