verif_code recognization added

.gitignore

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+.idea/

js/contextMenus.js

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+var effect = null;
+var autoclick = null;
+var autoback = null;
+
+function createAutoClick() {
+    chrome.contextMenus.create({
+        title: "自动点击登录(不稳定)",
+        type: "checkbox",
+        checked: autoclick,
+        contexts: ["browser_action"],
+        onclick: function (info, tab) {
+            autoclick = !autoclick;
+            chrome.storage.sync.set({'autoclick': autoclick});
+        }
+    });
+}
+
+function createAutoBack() {
+    chrome.contextMenus.create({
+        title: "登录失败自动回退",
+        type: "checkbox",
+        checked: autoback,
+        contexts: ["browser_action"],
+        onclick: function (info, tab) {
+            autoback = !autoback;
+            chrome.storage.sync.set({'autoback': autoback});
+        }
+    });
+}
+
+function createEffect() {
+    chrome.contextMenus.create({
+        title: "膜法特效全开",
+        type: "checkbox",
+        checked: effect,
+        contexts: ["browser_action"],
+        onclick: function (info, tab) {
+            effect = !effect;
+            chrome.storage.sync.set({'effect': effect});
+        }
+    });
+}
+
+
+chrome.storage.sync.get({'autoclick': false}, function (result) {
+    autoclick = result.autoclick;
+    chrome.storage.sync.set({'autoclick': autoclick}, createAutoClick);
+});
+
+chrome.storage.sync.get({'autoback': true}, function (result) {
+    autoback = result.autoback;
+    chrome.storage.sync.set({'autoback': autoback}, createAutoBack);
+});
+
+chrome.storage.sync.get({'effect': true}, function (result) {
+    effect = result.effect;
+    chrome.storage.sync.set({'effect': effect}, createEffect);
+});

js/lib/image.js

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+function noiseDetect(data, x, y, width, height) {
+    var vector = [[0, -1], [0, 1], [1, -1], [1, 1], [-1, -1], [-1, 1], [1, 0], [-1, 0]];
+    var all = 0;
+    for (var i = 0; i < 8; i++) {
+        var xx = x + vector[i][0];
+        var yy = y + vector[i][1];
+        if (xx >= 0 && xx < height && yy >= 0 && yy < width) {
+            if (data[xx * width + yy] == 1) {
+                all++;
+            }
+        }
+    }
+    var threshold = 1;
+    if (width == 60)
+        threshold = 0;
+    if (all <= threshold)
+        return true;
+    return false;
+}
+
+function preprocessImg(imgdata) {
+    var data = Array();
+    var width = imgdata.width;
+    var height = imgdata.height;
+    var t1 = 340, t2 = 150;
+    if (width == 60) {
+        t1 = 430, t2 = 220;
+    }
+    for (var i = 0, j = 0; i < width * height * 4; i += 4, j++) {
+        a = imgdata[i], b = imgdata[i + 1], c = imgdata[i + 2];
+        if (a + b + c <= t1 && (!(a == b && b == c)) && (a <= t2 || b <= t2 || c <= t2))
+            data[j] = 1;
+        else
+            data[j] = 0;
+    }
+    var todo = [];
+
+    for (var i = 0; i < height; i++) {
+        for (var j = 0; j < width; j++) {
+            if (data[i * width + j] == 0)
+                continue;
+            if (i == 0 || j == 0) {
+                todo.push([i, j]);
+                continue;
+            }
+            if (noiseDetect(data, i, j, width, height))
+                todo.push([i, j]);
+        }
+    }
+    for (var i = 0; i < todo.length; i++) {
+        x = todo[i][0], y = todo[i][1];
+        data[x * width + y] = 0;
+    }
+    return data;
+}
+
+function split(l, data, width) {
+    if (width == 60) {
+        b = [];
+        for (var i = 0; i < 20; i++) {
+            a = [];
+            for (var j = 0; j < 60; j++)
+                a.push(data[i * 60 + j]);
+            b.push(a.join(' '));
+        }
+        console.log(b.join('\n'));
+        var ret = [];
+        var pos = [[6, 13], [19, 26], [32, 39], [45, 52]];
+        for (var i = 0; i < 4; i++) {
+            var char = new Array();
+            var a = pos[i];
+            for (var p = 0; p < 12; p++) {
+                for (var q = 0; q < 8; q++)
+                    char[p * 8 + q] = [data[(p + 4) * width + (a[0] + q)]];
+            }
+            ret.push(char);
+        }
+        return [true, ret];
+    }
+    b = [];
+    for (var i = 0; i < 22; i++) {
+        a = [];
+        for (var j = 0; j < 55; j++)
+            a.push(data[i * 55 + j]);
+        b.push(a.join(' '));
+    }
+    console.log(b.join('\n'));
+
+    //清除上下区域的噪点
+    var row = Array();
+    for (var i = 0; i < 22; i++) {
+        row[i] = 0;
+        for (var j = 0; j < 55; j++)
+            row[i] += data[i * 55 + j];
+    }
+    var rthreshold = 17;
+    var r0 = 0, r1 = 21;
+    for (var i = 11; i >= 0; i--) {
+        if (row[i] < 2) {
+            r0 = i + 1;
+            break
+        }
+    }
+    for (var i = 11; i < 22; i++) {
+        if (row[i] < 2) {
+            r1 = i - 1;
+            break
+        }
+    }
+    var r = r1 - r0 + 1;
+    if (r > rthreshold) {
+        r1 -= (r - rthreshold) / 2;
+        r0 += (r - rthreshold) - (r - rthreshold) / 2;
+    }
+    for (var i = 0; i < r0; i++) {
+        for (var j = 0; j < 55; j++)
+            data[i * 55 + j] = 0;
+    }
+    for (var i = r1 + 1; i < 22; i++) {
+        for (var j = 0; j < 55; j++) {
+            data[i * 55 + j] = 0;
+        }
+    }
+
+    //清除左右区域的噪点
+    var col = Array();
+    for (var i = 0; i < 55; i++) {
+        col[i] = 0;
+        for (var j = 0; j < 22; j++)
+            col[i] += data[j * 55 + i];
+    }
+    var cthreshold = 17;
+    var c0 = 0, c1 = 54;
+    for (var i = 0; i < 27; i++) {
+        if (col[i] > 0) {
+            c0 = i;
+            break
+        }
+    }
+    for (var i = 54; i > 27; i--) {
+        if (col[i] > 0) {
+            c1 = i;
+            break
+        }
+    }
+
+    //字符切割
+    for (var i = 0; i < 55; i++) {
+        col[i] = 0;
+        for (var j = 0; j < 22; j++)
+            col[i] += data[j * 55 + i];
+    }
+    var pos = [];
+    var front = c0;
+    for (var i = c0 + 1; i <= c1; i++) {
+        if (i <= front)
+            continue;
+        if (col[i] != 0 && i - front > 16) {
+            var p = argmin(col, front + 5, i) + front + 5;
+            pos.push([front, p]);
+            front = p;
+        }
+        if (col[i] == 0 || i == c1) {
+            if (i - front <= 3 && argsum(col, front, i) < 10) {
+            }
+            else if (i - front <= 16) {
+                pos.push([front, i - 1]);
+            }
+            else if (i - front > 16) {
+                p = argmin(col, front + 5, i - 5) + front + 5;
+                pos.push([front, p]);
+                pos.push([p, i - 1]);
+            }
+            front = i + 1;
+            while (front <= c1 && col[front] == 0)
+                front++;
+        }
+    }
+
+    if (pos.length != l)
+        return [false, false]
+
+    var ret = [];
+    for (var i = 0; i < 4; i++) {
+        var a = pos[i];
+        var char = new Array();
+        for (var p = 0; p < rthreshold; p++) {
+            for (var q = 0; q < cthreshold; q++) {
+                char[p * cthreshold + q] = [0];
+                if (p + r0 <= r1 && q + a[0] <= a[1])
+                    char[p * cthreshold + q][0] = data[(p + r0) * 55 + q + a[0]];
+            }
+        }
+        ret.push(char);
+    }
+    return [true, ret];
+}
+
+
+function getImgEle() {
+    var img = document.getElementById('imgRandom');//dean student
+    if (img == null) {//genearch
+        if (document.getElementById('RandomPhoto'))
+            img = document.getElementById('RandomPhoto').firstElementChild;
+    }
+    if (img == null) {//network
+        img = document.getElementsByTagName('img')[0];
+    }
+    var canvas = document.createElement("canvas");
+    width = img.naturalWidth;
+    height = img.naturalHeight;
+    canvas.width = width
+    canvas.height = height
+    ctx = canvas.getContext("2d");
+    ctx.drawImage(img, 0, 0);
+    imgdata = ctx.getImageData(0, 0, width, height).data;
+    imgdata.width = width;
+    imgdata.height = height;
+    return imgdata;
+}
+
+function recognize(ws, bs, x) {
+    function sigmoid(a) {
+        for (var i = 0; i < a.length; i++)
+            a[i][0] = 1.0 / (1.0 + Math.exp(-a[i][0]));
+        return a;
+    }
+
+    for (var i = 0; i < ws.length; i++) {
+        x = sigmoid(mat_add(mat_mul(ws[i], x), bs[i]));
+    }
+    return argmax(x, 0, ws[ws.length - 1].length);
+}
+
+function img2string(l, name, callback1) {
+    var imgdata = getImgEle();
+    var data = preprocessImg(imgdata);
+    var ret = split(l, data, imgdata.width);
+    var base = 65;
+    if (name == "network.json")
+        base = 48;
+    if (!ret[0]) {
+        callback1(false);
+        return;
+    }
+    x = ret[1];
+    getData(name, function (data) {
+        var ws = data["weights"];
+        var bs = data["biases"];
+        verif_code = [];
+        for (var i = 0; i < l; i++)
+            verif_code.push(String.fromCharCode(base + recognize(ws, bs, x[i])));
+        callback1(verif_code.join(''));
+    });
+}

js/lib/json.js

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+function getData(name, callback) {
+    id = chrome.runtime.id;
+    url = chrome.runtime.getURL("data/" + name);
+    var json_req = new XMLHttpRequest();
+    json_req.overrideMimeType("applicatoin/json");
+    json_req.open("get", url, true);
+    json_req.onreadystatechange = function () {
+        if (json_req.readyState == 4) {
+            data = JSON.parse(json_req.responseText);
+            callback(data);
+        }
+    };
+    json_req.send();
+}