From 6f6c263a072c9df4e826d8ebb2035c82a87be7e0 Mon Sep 17 00:00:00 2001
From: Arpit Chakladar <arpitchakladar+git@gmail.com>
Date: Mon, 13 Jul 2026 20:49:57 +0530
Subject: refactor: organised the scripts into a more well defined structure

now all scripts that are common to all pages lie in src/scripts/common
each page gets its own folder in src/pages and different parts of the
page's configuration are separated in separated folders which are all
finally imported in src/pages/*/index.ts
---
 src/scripts/common/login/captcha.ts | 122 ++++++++++++++++++++++++++++++++++++
 1 file changed, 122 insertions(+)
 create mode 100644 src/scripts/common/login/captcha.ts

(limited to 'src/scripts/common/login/captcha.ts')

diff --git a/src/scripts/common/login/captcha.ts b/src/scripts/common/login/captcha.ts
new file mode 100644
index 0000000..73e8995
--- /dev/null
+++ b/src/scripts/common/login/captcha.ts
@@ -0,0 +1,122 @@
+import { observeDOM } from "@/shared/observe-dom";
+
+/**
+ * Pre-processes a CAPTCHA image on a canvas by removing grayish
+ * background noise while preserving dark pixels, producing a clean
+ * binary image suitable for OCR.
+ *
+ * @param ctx    - The 2D rendering context of the canvas.
+ * @param width  - Canvas width in pixels.
+ * @param height - Canvas height in pixels.
+ */
+export function prepareCaptcha(ctx: CanvasRenderingContext2D, width: number, height: number) {
+	const imgData = ctx.getImageData(0, 0, width, height);
+	const data = imgData.data;
+	const radius = 1;
+
+	/** Returns true when all three channels are below 50 (very dark). */
+	function isBlack(r: number, g: number, b: number) {
+		return r < 50 && g < 50 && b < 50;
+	}
+
+	/** Returns true when the colour is a mid-range grey (no strong hue). */
+	function isGrayish(r: number, g: number, b: number) {
+		return Math.abs(r - g) < 15 && Math.abs(g - b) < 15 && r > 100 && r < 200;
+	}
+
+	/**
+	 * Checks whether a black pixel exists within `radius` pixels of (x, y).
+	 * Used to preserve dark structures when removing grey noise.
+	 */
+	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);
+}
+
+observeDOM(() => {
+	const loginFormElement = document.querySelector("#loginform") as (HTMLFormElement | undefined);
+
+	if (loginFormElement) {
+		const captchaImg = loginFormElement.querySelector("#captchaImg") as HTMLImageElement;
+		const captchaInput = loginFormElement.querySelector("#txtInput") as HTMLInputElement;
+
+		// Wait for image to load to get correct dimensions
+		captchaImg.addEventListener("load", async () => {
+			const { width, height } = captchaImg;
+
+			// 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(captchaImg).cssText;
+			canvas.style.display = "none";
+
+			// 3. Insert canvas before image
+			captchaImg.parentNode!.querySelectorAll("canvas").forEach(c => c.remove());
+			captchaImg.parentNode!.insertBefore(canvas, captchaImg);
+
+			// 4. Hide image
+			captchaImg.style.display = "none";
+
+			// 5. Draw the image onto the canvas
+			const ctx = canvas.getContext("2d")!;
+			ctx.drawImage(captchaImg, 0, 0);
+			prepareCaptcha(ctx, canvas.width, canvas.height);
+			canvas.style.display = "";
+			const dataURL = canvas.toDataURL("image/png");
+
+			// Perform OCR
+			chrome.runtime.sendMessage(
+				{ type: "OCR", dataURL },
+				({ success, text, confidence }) => {
+					if (success) {
+						const textResult = text.trim();
+						if (confidence < 80 || textResult.length !== 6) {
+							// Reset the captcha if confidence is low
+							captchaImg.src = "generateCaptcha?" + new Date().getTime();
+						} else {
+							captchaInput.value = textResult;
+						}
+					}
+				},
+			);
+		});
+	}
+
+	// This runs forever
+	return false;
+});
-- 
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