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// ==UserScript==
// @name x
// @namespace xx
// @version 1
// @license MIT
// @description vv
// @author bb
// @match *://*.hcaptcha.com/*hcaptcha-challenge*
// @match *://*.hcaptcha.com/*checkbox*
// @grant GM_xmlhttpRequest
// @connect https://cdnjs.cloudflare.com
// @connect https://cdn.jsdelivr.net
// @connect https://unpkg.com
// @connect *://*.hcaptcha.com/*
// @require https://cdn.jsdelivr.net/npm/jquery@3.6.0/dist/jquery.min.js
// @require https://unpkg.com/jimp@0.5.2/browser/lib/jimp.min.js
// @require https://cdnjs.cloudflare.com/ajax/libs/tesseract.js/2.0.0-alpha.2/tesseract.min.js
// @require https://cdn.jsdelivr.net/npm/@tensorflow/tfjs/dist/tf.min.js
// @require https://cdn.jsdelivr.net/npm/@tensorflow-models/coco-ssd
// ==/UserScript==
(function() {
'use strict';
var selectedImageCount = 0;
var tensorFlowModel = undefined;
var worker = undefined;
//Node Selectors
const CHECK_BOX = "#checkbox";
const SUBMIT_BUTTON = ".button-submit";
const TASK_IMAGE_BORDER = ".task-image .border";
const IMAGE = ".task-image .image";
const TASK_IMAGE = ".task-image";
const PROMPT_TEXT = ".prompt-text";
const NO_SELECTION = ".no-selection";
const CHALLENGE_INPUT_FIELD = ".challenge-input .input-field";
const CHALLENGE_INPUT = ".challenge-input";
const IMAGE_FOR_OCR = ".challenge-image .zoom-image";
//Attributes
const ARIA_CHECKED = "aria-checked";
const ARIA_HIDDEN = "aria-hidden";
//Values that can be changed for other languages
const AIRPLANE = "airplane";
const BICYCLE = "bicycle";
const BOAT = "boat";
const CAR = "car";
const MOTORBUS = "motorbus";
const MOTORCYCLE = "motorcycle";
const TRAIN = "train";
const TRUCK = "truck";
const TRANSPORT_TYPES = [AIRPLANE, BICYCLE, BOAT, CAR, MOTORBUS, MOTORCYCLE, TRAIN, TRUCK];
const SENTENCE_TEXT_A = "Please click each image containing a ";
const SENTENCE_TEXT_AN = "Please click each image containing an ";
const LANGUAGE_FOR_OCR = "eng";
// Option to override the default image matching
//const ENABLE_TENSORFLOW = true;
String.prototype.includesOneOf = function(arrayOfStrings) {
//If this is not an Array, compare it as a String
if (!Array.isArray(arrayOfStrings)) {
return this.toLowerCase().includes(arrayOfStrings.toLowerCase());
}
for (var i = 0; i < arrayOfStrings.length; i++) {
if ((arrayOfStrings[i].substr(0, 1) == "=" && this.toLowerCase() == arrayOfStrings[i].substr(1).toLowerCase()) ||
(this.toLowerCase().includes(arrayOfStrings[i].toLowerCase()))) {
return true;
}
}
return false;
}
function matchImagesUsingTensorFlow(imageUrl, word, i) {
try {
var img = new Image();
img.crossOrigin = "Anonymous";
img.src = imageUrl;
img.onload = () => {
initializeTensorFlowModel().then(model => model.detect(img))
.then(function(predictions) {
var predictionslen = predictions.length;
for (var j = 0; j < predictionslen; j++) {
if (qSelectorAll(IMAGE)[i] && (qSelectorAll(IMAGE)[i].style.background).includes(imageUrl) &&
qSelectorAll(TASK_IMAGE_BORDER)[i].style.opacity == 0 &&
predictions[j].class.includesOneOf(word)) {
qSelectorAll(TASK_IMAGE)[i].click();
break;
}
}
selectedImageCount = selectedImageCount + 1;
});
}
} catch (err) {
console.log(err.message);
}
}
//Different Models can be set later based on usecase
//Ref Models: https://github.com/tensorflow/tfjs-models
async function initializeTensorFlowModel() {
if (!tensorFlowModel) {
tensorFlowModel = await cocoSsd.load();
}
return tensorFlowModel;
}
//Initialize TesseractWorker
function initializeTesseractWorker() {
if(!worker){
worker = new Tesseract.TesseractWorker();
}
}
function qSelectorAll(selector) {
return document.querySelectorAll(selector);
}
function qSelector(selector) {
return document.querySelector(selector);
}
async function getSynonyms(word) {
//TODO: Format this to JSON string
var tempWord = word;
if (!tempWord.includesOneOf(TRANSPORT_TYPES)) {
console.log("New word or different cyrillic");
var img = await convertTextToImage(word);
tempWord = await convertImageToText(img);
img.removeAttribute("src");
word = tempWord;
}
if (word == MOTORBUS) {
word = ['bus', 'motorbus'];
} else if (word == CAR) {
word = ['=car', 'coupe', 'jeep', 'limo', 'sport utility vehicle', 'station wagon', 'hatchback', 'bumper car', 'modelT', 'electric battery', 'cruiser'];
} else if (word == AIRPLANE) {
word = ['airplane', 'plane', 'aircraft', 'aeroplane', 'hangar', 'Airdock', 'JumboJet', 'jetliner', 'stealth fighter', 'field artillery']
} else if (word == TRAIN) {
word = ['train', 'rail', 'cable car', 'locomotive', 'subway station']
} else if (word == BOAT) {
word = ['=boat', '=barge', 'houseboat', 'bobsled', 'pontoon', 'small boat', 'SnowBlower', 'Sea-coast', 'PaddleSteamer', 'Freighter', 'Sternwheeler', 'kayak', 'canoe', 'deck', 'DockingFacility', 'surfboard', 'ship', '=cruise', 'watercraft', 'sail', 'canvas', '=raft']
} else if (word == BICYCLE) {
word = ['bicycle', 'tricycle', 'mountain bike', 'AcceleratorPedal', 'macaw', 'knot']
} else if (word == MOTORCYCLE) {
word = ['motorcycle', 'windshield', 'dashboard']
} else if (word == TRUCK) {
word = ['truck', 'cargocontainer', 'bazooka']
} else {
console.log("Word does not match. New type identified::" + word);
}
return word
}
function isHidden(el) {
return (el.offsetParent === null)
}
if (window.location.href.includes("checkbox")) {
var checkboxInterval = setInterval(function() {
if (!qSelector(CHECK_BOX)) {
clearInterval(checkboxInterval);
} else if (qSelector(CHECK_BOX).getAttribute(ARIA_CHECKED) == "true") {
clearInterval(checkboxInterval);
} else if (!isHidden(qSelector(CHECK_BOX)) && qSelector(CHECK_BOX).getAttribute(ARIA_CHECKED) == "false") {
qSelector(CHECK_BOX).click();
} else {
return;
}
}, 5000);
} else {
try {
initializeTesseractWorker();
selectImages();
} catch (err) {
console.log(err);
console.log("Tesseract could not be initialized");
}
}
function selectImagesAfterDelay(delay) {
setTimeout(function() {
selectImages();
}, delay * 1000);
}
function triggerEvent(el, type) {
var e = document.createEvent('HTMLEvents');
e.initEvent(type, false, true);
el.dispatchEvent(e);
}
// Small hack to select the nodes
function unsure(targetNodeText) {
var targetNode = Array.from(qSelectorAll('div'))
.find(el => el.textContent === targetNodeText);
//Works for now
//TODO: Select clothing
//TODO: Draw boxes around images
if (targetNode) {
triggerEvent(targetNode, 'mousedown');
triggerEvent(targetNode, 'mouseup');
if (qSelector(SUBMIT_BUTTON)) {
qSelector(SUBMIT_BUTTON).click();
}
}
return selectImagesAfterDelay(1);
}
function getUrlFromString(urlString) {
var urlMatch = urlString.match(/(?<=\(\").+?(?=\"\))/g);
if (!urlMatch) {
return 0;
}
var imageUrl = urlMatch[0];
return imageUrl;
}
function getImageList() {
var imageList = [];
if (qSelectorAll(IMAGE).length > 0) {
for (var i = 0; i < 9; i++) {
var urlString = qSelectorAll(IMAGE)[i].style.background;
var imageUrl = getUrlFromString(urlString);
if (imageUrl == 0) {
//console.log("Image url is empty");
return imageList;
}
imageList[i] = imageUrl;
}
}
return imageList;
}
function waitUntilImageSelection() {
var imageIntervalCount = 0;
var imageInterval = setInterval(function() {
imageIntervalCount = imageIntervalCount + 1;
if (selectedImageCount == 9) {
clearInterval(imageInterval);
if (qSelector(SUBMIT_BUTTON)) {
qSelector(SUBMIT_BUTTON).click();
}
return selectImagesAfterDelay(5);
} else if (imageIntervalCount > 8) {
clearInterval(imageInterval);
return selectImages();
} else {
}
}, 3000);
}
function waitForImagesToAppear() {
var checkImagesSelectedCount = 0;
var waitForImagesInterval = setInterval(function() {
checkImagesSelectedCount = checkImagesSelectedCount + 1;
if (qSelectorAll(IMAGE) && qSelectorAll(IMAGE).length == 9) {
clearInterval(waitForImagesInterval);
return selectImages();
} else if (checkImagesSelectedCount > 30) {
clearInterval(waitForImagesInterval);
} else if (qSelector(CHALLENGE_INPUT_FIELD) && qSelector(NO_SELECTION).getAttribute(ARIA_HIDDEN) != true) {
clearInterval(waitForImagesInterval);
return imageUsingOCR();
} else if(qSelector('canvas')){
var $el = $(qSelector('canvas'));
var offset = $el.offset()
console.log(offset)
var event = jQuery.Event('mousedown', {
which: 1,
pageX: offset.left+200,
pageY: offset.top+300,
})
$el.trigger(event);
var event = jQuery.Event('mousedown', {
which: 1,
pageX: offset.left+300,
pageY: offset.top+400,
})
$el.trigger(event);
}else{
var targetNodeList = ["3 or more items of furniture", "Equipped space or room", "Photo is clean, no watermarks, logos or text overlays", "An interior photo of room", "Unsure", "Photo is sharp"];
for (var j = 0; j < targetNodeList.length; j++) {
var targetNode = Array.from(qSelectorAll('div'))
.find(el => el.textContent === targetNodeList[j]);
if (targetNode) {
//console.log("Target Node Found");
clearInterval(waitForImagesInterval);
return unsure(targetNodeList[j]);
}
}
}
}, 5000);
}
function makeid(length) {
var result = '';
var characters = 'abcdefghijklmnopqrstuvwxyz';
var charactersLength = characters.length;
for ( var i = 0; i < length; i++ ) {
result += characters.charAt(Math.floor(Math.random() * charactersLength));
}
return result;
}
function preProcessImage(imageUrl) {
//Darken and Brighten
Jimp.read(imageUrl).then(function(data) {
data.color([
{
apply: 'darken',
params: [20]
}
]).color([
{
apply: 'brighten',
params: [20]
}
])
.greyscale()
.getBase64(Jimp.AUTO, function(err, src) {
var img = document.createElement("img");
img.setAttribute("src", src);
worker.recognize(img, LANGUAGE_FOR_OCR).then(function(data) {
//Remove Image After recognizing
img.removeAttribute("src");
//If null change to other methods
//if (data && data.text && data.text.length > 0) {
inputChallenge(postProcessImage(data), imageUrl);
return selectImages();
//} else {
//preProcessImageMethod2(imageUrl);
//}
});
});
});
}
function postProcessImage(data) {
var filterValues = ['\n', '{', '}', '[', ']'];
for (var i = 0; i < filterValues.length; i++) {
data.text = data.text.replaceAll(filterValues[i], "");
}
return data;
}
// Using Tesseract to recognize images
function imageUsingOCR() {
try {
//console.log("Image using OCR");
var urlString = qSelector(IMAGE_FOR_OCR).style.background;
var imageUrl = getUrlFromString(urlString);
if (imageUrl == 0) {
return selectImagesAfterDelay(1);
}
preProcessImage(imageUrl);
} catch (err) {
console.log(err.message);
return selectImagesAfterDelay(1);
}
}
async function convertTextToImage(text) {
//Convert Text to image
var canvas = document.createElement("canvas");
canvas.width = 620;
canvas.height = 80;
var ctx = canvas.getContext('2d');
ctx.font = "30px Arial";
ctx.fillText(text, 10, 50);
var img = document.createElement("img");
img.src = canvas.toDataURL();
return img;
}
async function convertImageToText(img) {
//Convert Image to Text
var text = "";
await worker.recognize(img, LANGUAGE_FOR_OCR).then(function(data) {
text = data.text;
// console.log("Recognized Text::" + text);
});
return text.trim();
}
function inputChallenge(data, imageUrl) {
try {
if ((qSelector(IMAGE_FOR_OCR).style.background).includes(imageUrl)) {
console.log(data.text);
var targetNode = qSelector(CHALLENGE_INPUT_FIELD);
targetNode.value = data.text.replaceAll("\n", "");
var challengeInput = qSelector(CHALLENGE_INPUT);
triggerEvent(challengeInput, 'input');
// Set a timeout if you want to see the text
qSelector(SUBMIT_BUTTON).click();
}
} catch (err) {
console.log(err.message);
}
}
async function selectImages() {
if (qSelectorAll(IMAGE) && qSelectorAll(IMAGE).length == 9 && qSelector(NO_SELECTION).getAttribute(ARIA_HIDDEN) != true) {
selectedImageCount = 0;
try {
await initializeTensorFlowModel();
var word = qSelector(PROMPT_TEXT).innerText;
if (word && (word.includes(SENTENCE_TEXT_A) || word.includes(SENTENCE_TEXT_AN))) {
word = word.replace(SENTENCE_TEXT_A, '');
word = word.replace(SENTENCE_TEXT_AN, '');
} else {
//TODO: Select images from example and identify the word for other languages
}
} catch (err) {
console.log(err.message);
return selectImagesAfterDelay(5);
}
var imageList = [];
try {
imageList = getImageList();
if (imageList.length != 9) {
//console.log("Waiting");
return selectImagesAfterDelay(5);
}
} catch (err) {
console.log(err.message);
return selectImagesAfterDelay(5);
}
//Get Synonyms for the word
word = await getSynonyms(word);
//console.log("words are::" + word);
for (var i = 0; i < 9; i++) {
//if (ENABLE_TENSORFLOW) {
matchImagesUsingTensorFlow(imageList[i], word, i);
//} else {
// matchImages(imageList[i], word, i);
//}
}
waitUntilImageSelection();
} else {
waitForImagesToAppear();
}
}
})();