// ==UserScript==
// @name         mhyX
// @namespace    http://tampermonkey.net/
// @version      0.1.1
// @description  测试pyscript识别验证码目标区域位置
// @author       tfsn20
// @match        https://user.mihoyo.com/*
// @icon         https://user.mihoyo.com/favicon.ico
// @grant        GM_log
// @grant        GM_getValue
// @grant        GM_setValue
// @grant        GM_deleteValue
// @run-at       context-menu
// @grant        unsafeWindow

// ==/UserScript==

(async function () {

    function sleep(time) {
        return new Promise((resolve) => setTimeout(resolve, time))
    };
    await sleep(1000)
    GM_log('注入');
    //劫持console.info判断py运行时加载情况
    let oldLog = unsafeWindow.console.info;
    unsafeWindow.console.info = function (...a) {
        oldLog(...a)
        if (a[0].toString().match(/PyScript page fully initialized/)) {
            oldLog('python运行时加载完毕,可执行python代码...........')
            pythonRuntimeThen()

        }
    }
    function createObject(object, variableName) {
        //Bind a variable whose name is the string variableName
        // to the object called 'object'
        let execString = variableName + " = object"
        console.log("Running `" + execString + "`");
        eval(execString)
    }
    unsafeWindow.createObject = createObject;


    async function pythonRuntimeThen() {

        await loadPyodide()
        let res = then_js();
        listenThen(res);



        function listenThen(res = null) {
            let d = null;
            d = JSON.parse(res);
            console.log('parse', d);
            const imageData = ctx.createImageData(w, h);
            let len = imageData.data.length;
            let t = [];
            for (let i = 0, l = d.length; i < l; i += 3) {
                t.push(d[i + 0], d[i + 1], d[i + 2], 255)
            };
            for (let i = 0; i < len; i += 4) {
                imageData.data[i + 0] = t[i + 0];
                imageData.data[i + 1] = t[i + 1];
                imageData.data[i + 2] = t[i + 2];
                imageData.data[i + 3] = 255;
            };
            ctx.putImageData(imageData, 0, 0);
            console.log('has again draw');

        }
    }

    let w = null;
    let h = null;
    let canvas = document.createElement('canvas');
    let ctx = canvas.getContext("2d");
    let imgUrl = null;
    //绘制图像, 返回像素数据array
    async function drawAndGetData() {
        let imgDiv = document.querySelector('div[class="geetest_item_wrap"]');
        imgUrl = imgDiv.style.backgroundImage.match(/(http.*")/)[1];

        function getImageSize(url) {
            return new Promise(function (resolve, reject) {
                let image = new Image();
                image.onload = function () {
                    resolve({
                        width: image.width,
                        height: image.height
                    });
                };
                image.onerror = function () {
                    reject(new Error('error'));
                };
                image.src = url;
            });
        }


        let size = await getImageSize(imgUrl);
        w = size.width;
        h = size.height


        let img = document.createElement('img');
        img.style.cssText = ` width:${w}px; height:${h}px; `;
        imgDiv.append(img);

        img.setAttribute('src', imgUrl)
        img.setAttribute('crossOrigin', 'anonymous');

        canvas.style.cssText = `position:fixed; top:0px; left:0px; z-index:999`;
        let body = document.querySelector('body');
        body.append(canvas);

        GM_log(w, h);
        //将canvas的宽和高设置一下
        canvas.width = w;
        canvas.height = h;

        await sleep(200)
        ctx.drawImage(img, 0, 0);


        //这是原始像素数据
        let dataOrigin = ctx.getImageData(0, 0, w, h).data;
        return dataOrigin
    };

    let data = await drawAndGetData();
    console.log('origin pixel data', data);
    function addElement(type, others) {
        if (type == 'script') {
            let dom = document.createElement('script');
            //dom.setAttribute('defer');
            dom.src = others.src;
            body.appendChild(dom);
            return
        }
        if (type == 'css') {
            let dom = document.createElement('link');
            dom.setAttribute('ref', 'stylesheet');
            dom.href = others.href;
            body.appendChild(dom);
            return
        }
        if (type == 'py-env') {
            let dom = document.createElement('py-env');
            dom.innerHTML = others.env;
            body.appendChild(dom);
            return
        }
        if (type == 'div') {
            let dom = document.createElement('div');
            dom.setAttribute(others.type, others.name);
            // dom.href = `${website}`;
            body.appendChild(dom);
            return
        }
        if (type == 'py-script') {
            let dom = document.createElement('py-script');
            dom.setAttribute(others.type, others.name);
            dom.innerHTML = others.pyScript;
            body.appendChild(dom);
            return
        }
        if (type == 'py-config') {
            let dom = document.createElement('py-config');
            dom.setAttribute('type', 'json');
            dom.innerHTML = others.config;
            body.appendChild(dom);
            return
        }



    };
    let body = document.querySelector("body"), head = document.querySelector("head");
    //load pyodide
    function need() {
        addElement('py-env', {
            env: `
                - numpy
                - opencv_python
                - Pillow
                `
        });
        addElement('css', { href: 'https://pyscript.net/latest/pyscript.css' });
        //latest可以换成某个版本，/v0.20.0及之前不支持非纯py库opencv_python，参考https://github.com/pyodide/pyodide/discussions/2424
        addElement('script', { src: 'https://pyscript.net/latest/pyscript.js' });
        console.log('----------------正在加载包和环境------------');
    }
    need();


    //add output element
    addElement('div', {
        type: 'id',
        name: 'plot'
    });
    //add pyscript
    addElement('py-script', {
        type: 'output',
        name: 'plot',
        pyScript: `
        import js
        from pyodide import create_proxy, to_js
        import numpy as np
        import cv2
        from PIL import Image


        def maxGray(img):
            h, w = img.shape[0:2]
            # 自定义空白单通道图像，用于存放灰度图
            gray = np.zeros((h, w), dtype=img.dtype)
            # 对原图像进行遍历，然后分别对B\G\R按比例灰度化
            for i in range(h):
                for j in range(w):
                    gray[i, j] = max(img[i, j, 0], img[i, j, 1],
                                     img[i, j, 2])  # 求3通道中最大的值
            return gray

        def gammaGray(img):
            h, w = img.shape[0:2]
            print('[h,w]',[h,w])
            # 自定义空白单通道图像，用于存放灰度图
            gray = np.zeros((h, w), dtype=img.dtype)
            # 对原图像进行遍历，然后分别对B\G\R按比例灰度化
            for i in range(h):
                for j in range(w):
                    a = img[i, j, 2]**(2.2)+1.5*img[i, j, 1]**(2.2) + \
                        0.6*img[i, j, 0]**(2.2)  # 分子
                    b = 1+1.5**(2.2)+0.6**(2.2)  # 分母
                    gray[i, j] = pow(a/b, 1.0/2.2)  # 开2.2次方根
            return gray


        def getMserImg(gray,draw,d=10):
            max=60+d
            min=60-d
            draw=draw.copy()
            mser = cv2.MSER_create()
            regions, boxes = mser.detectRegions(gray)
            for index, box in enumerate(boxes):
                x, y, w, h = box
                if w < max and h < max and w > min and h > min:
                    print([x,y])
                    cv2.rectangle(draw, (x, y), (x+w, y+h), (0, 255, 0), 1)
            return draw

        def then():
            data= ${data}
            data=list(data)
            w=${w}
            h=${h}
            t=[]
            for i,e in enumerate(data):
                if i%4 ==0:
                    t.append(data[i:i+3])
            t1=[]
            for i,e in enumerate(t):
                if i%w == 0:
                    t1.append(t[i:i+w])
            data = np.array(t1).astype(np.uint8)
            img=Image.fromarray(data)
            img=np.asarray(img)
            img_copy=img.copy()
            kernel = np.array([[-1, -1, -1],
                [-1, 8, -1],
                [-1, -1, -1]])
            img = cv2.filter2D(img, -1, kernel)
            gray=gammaGray(img)
            # gray = cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB)
            draw = getMserImg(gray,img_copy,10)
            pd=np.array(draw.flatten()).tolist()
            pyscript.write('plot',pd)
            return pd
        # 导出then函数到js环境中(名为then_js)
        js.createObject(create_proxy(then), "then_js")
        `
    });




})();