登入介面中自動填寫驗證碼
// ==UserScript==
// @name 北科入口網站 - 自動填寫驗證碼
// @namespace http://tampermonkey.net/
// @version 2024-12-26 v2
// @description 登入介面中自動填寫驗證碼
// @author umeow
// @match https://nportal.ntut.edu.tw/index.do*
// @icon https://www.google.com/s2/favicons?sz=64&domain=edu.tw
// @connect istream.ntut.edu.tw
// @run-at document-end
// @require https://cdnjs.cloudflare.com/ajax/libs/mathjs/14.0.1/math.min.js
// @license MIT
// ==/UserScript==
let model = undefined;
const img = document.getElementById("authImage");
async function getModel() {
let text = localStorage.getItem('ntut.edu.tw_model_weight.json');
if(text === null) {
const res = await fetch('https://gistcdn.githack.com/umeow0716/d2f9ff8c5d060eeb0bdb86985cd328d8/raw/df1bac93ceb0d85eb2e4234a34b298d800f512a6/ntut.edu.tw_model_weight.json');
text = await res.text();
localStorage.setItem('ntut.edu.tw_model_weight.json', text);
}
model = JSON.parse(text);
}
function dotProduct(arr1, arr2) {
if (arr1[0].length !== arr2.length) {
throw new Error("Matrix dimensions do not align for dot product");
}
const result = Array.from({ length: arr1.length }, () => new Array(arr2[0].length).fill(0))
for (let i = 0; i < arr1.length; i++) {
const row = [];
for (let j = 0; j < arr2[0].length; j++) {
for (let k = 0; k < arr2.length; k++) {
result[i][j] += arr1[i][k] * arr2[k][j];
}
}
}
return result;
}
function applyFunction(arr, func) {
return arr.map(element =>
Array.isArray(element) ? applyFunction(element, func) : func(element)
);
}
function ELU(x) {
if(x >= 0.0) {
return x;
}
return 1.2 * (Math.exp(x) - 1);
}
function ReLU(x) {
return Math.max(x, 0);
}
function sigmoid(x) {
return 1 / (1 + Math.exp(-x));
}
function findChar(arr) {
const maxValue = Math.max(...arr);
const maxIndex = arr.indexOf(maxValue);
return String.fromCharCode(65 + maxIndex);
}
function transpose(matrix) {
if (!Array.isArray(matrix) || !Array.isArray(matrix[0])) {
throw new Error("Input must be a 2D array");
}
const rows = matrix.length;
const cols = matrix[0].length;
const transposed = Array.from({ length: cols }, () => new Array(rows));
for (let i = 0; i < rows; i++) {
for (let j = 0; j < cols; j++) {
transposed[j][i] = matrix[i][j];
}
}
return transposed;
}
function forward(x) {
const layer_1_output = applyFunction(math.add(dotProduct(model.layer_1_weight, x), model.layer_1_bias), ELU);
const layer_2_output = applyFunction(math.add(dotProduct(model.layer_2_weight, layer_1_output), model.layer_2_bias), ReLU);
const layer_3_output = applyFunction(math.add(dotProduct(model.layer_3_weight, layer_2_output), model.layer_3_bias), sigmoid);
let result = ''
for(let i = 0 ; i < 4 ; i++) {
result += findChar(layer_3_output.map(arr => arr[i]));
}
return result;
}
function normalize(matrix) {
const h = matrix.length;
const w = matrix[0].length;
const dHeight = 40 - h;
const dWidth = 40 - w;
if(dHeight < 0 || dWidth < 0) {
throw new Error("Input must smaller than 40x40");
}
const padTop = Math.floor(dHeight / 2);
const padLeft = Math.floor(dWidth / 2);
// Create new padded matrix
const padded = Array.from({ length: 40 }, () => Array(40).fill(0));
// Copy the original matrix into the padded one
for (let i = 0; i < h; i++) {
for (let j = 0; j < w; j++) {
padded[i + padTop][j + padLeft] = matrix[i][j];
}
}
return padded;
}
function getImage() {
// Create a canvas element
const canvas = document.createElement("canvas");
const context = canvas.getContext("2d");
// Set canvas dimensions to image dimensions
canvas.width = img.width;
canvas.height = img.height;
// Draw the image onto the canvas
context.drawImage(img, 0, 0);
// Extract pixel data
const imageData = context.getImageData(0, 0, img.width, img.height);
const data = imageData.data; // Array of RGBA values (one-dimensional)
// Convert the flat array into a 2D array of RGB values
const rgbArray = [];
for (let i = 0; i < data.length; i += 4) {
const r = data[i]; // Red
const g = data[i + 1]; // Green
const b = data[i + 2]; // Blue
rgbArray.push([r, g, b]);
}
return {
w: img.width,
h: img.height,
rgbArray: rgbArray,
};
};
const run = async() => {
const { w, h, rgbArray } = getImage();
const colorSet = new Set();
for (let i = 0; i < rgbArray.length; i += 4) {
const r = rgbArray[i][0];
const g = rgbArray[i][1];
const b = rgbArray[i][2];
colorSet.add(JSON.stringify([r, g, b]));
}
const colorList = Array.from(colorSet).map(item => JSON.parse(item));
const originImage = [];
for(let i = 0 ; i < h ; i++) {
const row = []
for(let j = 0 ; j < w ; j++) {
row.push(rgbArray[i * w + j]);
}
originImage.push(row);
}
const posList = [];
colorList.forEach((color, i) => {
const xSet = new Set();
const ySet = new Set();
const posData = [[], []];
for (let y = 0 ; y < h ; y++) {
for (let x = 0 ; x < w; x++) {
if (JSON.stringify(originImage[y][x]) === JSON.stringify(color)) {
xSet.add(x);
ySet.add(y);
posData[1].push(x);
posData[0].push(y);
}
}
}
posList.push([
xSet,
ySet,
posData
]);
});
// Filter out background colors, dot colors, and text colors
const backgroundList = [];
const dotList = [];
let textColorList = [];
for(let i = 0 ; i < colorList.length ; i++) {
if(posList[i][0].size > 40 || posList[i][0].size > 40) {
backgroundList.push(colorList[i]);
continue;
}
if(Math.min(...posList[i][1]) < 2 && Math.max(...posList[i][1]) > w-3) {
backgroundList.push(colorList[i]);
continue;
}
if(Math.min(...posList[i][0]) < 2 && Math.max(...posList[i][0]) > h-3) {
backgroundList.push(colorList[i]);
continue;
}
if((colorList[i][0] * 299 + colorList[i][1] * 587 + colorList[i][2] * 114 + 500) / 1000 > 150) {
backgroundList.push(colorList[i]);
continue;
}
if(posList[i][0].size < 5 || posList[i][0].size < 5) {
dotList.push(colorList[i]);
continue;
}
textColorList.push(i);
}
textColorList = textColorList.sort((a, b) => Math.min(...posList[a][0]) - Math.min(...posList[b][0]));
result = [];
for(const i of textColorList) {
const posData = posList[i][2];
const xMin = Math.min(...posData[1]);
const yMin = Math.min(...posData[0]);
const xMax = Math.max(...posData[1]);
const yMax = Math.max(...posData[0]);
const genImage = Array.from({ length: yMax - yMin + 1 }, () => Array(xMax - xMin + 1).fill(0));
for(let j = 0 ; j < posData[0].length ; j++) {
genImage[posData[0][j]-yMin][posData[1][j]-xMin] = 1;
}
result.push(normalize(genImage));
}
const MLPInput = transpose(result.map(arr => arr.flat()));
document.querySelector('#authcode').value = forward(MLPInput);
}
const main = async () => {
let n = 5;
await getModel();
let done = false;
setInterval(() => {
if(!done && img.complete) {
run();
done = true;
};
}, 100);
}
document.querySelector('#authcode').value = "稍待片刻...";
main();