Python&Auto.js:實現螞蟻森林自動收能量(懶人的高效生活)

我是真的懶,連能量都不想好好收,因此寫了腳本來自動幫我收能量.

Auto.js 這款腳本應用我們在應用市場可以很方便搜索到,它在沒有root的時候可以通過開啓無障礙服務來實現模擬點擊滑動,監聽等等.使用下面這個腳本,可以實現打開支付寶,進入螞蟻森林(你得將它添加到主頁常用子應用中),滑動,查找有能量的好友,進入蒐集

.After that,quit!

不廢話了直接上代碼:

auto();

events.observeNotification();
events.onToast(function (toast) {
    var text = toast.getText();
    var appName = toast.getPackageName();
    var subIdx = text.indexOf("後");

    if (appName == "com.eg.android.AlipayGphone" && subIdx != -1) {
        var sub = text.substring(0, subIdx);
        var idxHour = sub.indexOf("小時");
        var idxMin = sub.indexOf("分");
        var hour = 0;
        var min = 0;
        if (idxHour == -1) {
            var stringMin = sub.substring(0, idxMin);
            min = parseInt(stringMin)
        } else {
            var stringHour = sub.substring(0, idxHour);
            var stringMin = sub.substring(idxHour + 2, idxMin);
            hour = parseInt(stringHour)
            min = parseInt(stringMin)
        }
        var time = (hour*60+min)*60*1000;
        if(nextTime >time){
            nextTime = time;
        }
        log("NextTime="+hour+":"+min+" Microseconds="+nextTime+"ms");
    }

});
//setTimeout(function() {
//}, 1000*1);
// main();s
var end = false;
var nextTime = 900000000000;
main();

function main() {
    // home();
    // sleep(5000)
    //  swipe(540,1600,540,1000,350);
    // startToastListener();
    
    launchApp("支付寶");
    sleep(3000);
    click("螞蟻森林");
    sleep(3000);
    collect();
    swipe(540, 1910, 540, 100, 500)
    swipe(540, 1910, 540, 100, 500)
    swipe(540, 1910, 540, 100, 500)
    click(672, 954); // 查看排行榜
    sleep(2000);
    swipe(540, 1800, 540, 1800 - 240, 500);
    sleep(500);
    toast("開始採集了");
    while (!end) {
        exec();
    }
}

function exec() {
    swipe(540, 1919, 540, 88, 500)
    col();
    swipe(540, 1734, 540, 1734 - 156, 500)
    click(540, 1918);
    sleep(2000);
    swipe(540, 1857, 540, 155, 500);
    sleep(1000);
    col();
}

function col() {
   // toast("Begin col")
    if (!requestScreenCapture()) {
        toast("沒有截圖權限");
        exit();
        end = true;
    }
    var img = captureScreen();
    // var p = findColor(img,"#30bf6c"); // 
    for (var i = 187; i <= 1816; i = i + 200) {
        if (isEnd(img, i)) {
            back();
            sleep(1000);
            back();
            sleep(1000);
            back();
            sleep(1000);
            toast("完成任務啦！")
            end = true
            
        }
        var p = locColor(img, i);
        if (p) {
            log(i + " p.x=" + p.x + " p.y=" + p.y);
            click(1017, p.y + 20);
            sleep(3000);
            collect();
            back();
            sleep(1000);
        } else {
            log(i + " p=null");
        }
    }
}


function locColor(img, y) {
    var p = findColor(img, "#30bf6c", {
        region: [1017, y, 73, 100]
    });
    return p;
}

function isEnd(img, y) {
    var p = findColor(img, "#30bf6c", {
        region: [860, y, 10, 10]
    });
  //  toastLog("Got "+(img==null)+" "+y+" "+(p==null))
    if (p) {
      //  toastLog("Got "+(img==null)+" "+y)
        return true;
    } else {
//toastLog("Got "+(img==null)+" "+y)
        return false;
    }
}


function nextPage() {
    swipe(540, 1910, 540, 59, 5000)
}
function all(startHeight) {
    var eachHeight = 180;
    for (; startHeight < 1920; startHeight = eachHeight + startHeight) {
        toast(startHeight);
        click(540, startHeight);
        sleep(3000);
        collect();
        back();
        sleep(1000);
    }
}

function collect() {
    for (var y = 460; y <= 860; y += 100) {
        for (var x = 185; x <= 890; x += 100) {
            click(x, y);
        }
    }
}

Python中的實現,我們使用android的自動化測試庫uiautomator來實現,使用opencv來實現對截圖的中可蒐集小手的識別,目前還不是很完善,提供一個思路,希望有時間的你來實現,其實Auto.js那個真的好用;-)

#! -*- coding=utf-8 -*-
from uiautomator import Device
from uiautomator import Adb
import os
import cv2
import numpy as np  
from matplotlib import pyplot as plt

def match():
    img = cv2.imread("1.png",0)  
    img2 = img.copy()
    template = cv2.imread("match.png",0)  
    w,h = template.shape[::-1]  
    # method = eval('cv2.TM_CCOEFF')
    method = eval('cv2.TM_CCOEFF_NORMED')
    res = cv2.matchTemplate(img2,template,method)  
    threshold = 0.5

    loc = np.where( res >= threshold)
    arr = []
    for pt in zip(*loc[::-1]):
        cv2.rectangle(img, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
        d = (pt,(pt[0] + w, pt[1] + h),)
        arr.append(d)
    cv2.imwrite('res.png',img)
    return arr

if __name__ == "__main__":
    d = Device("7cba0eb")
    # d.screen.on()   
    # a = Adb()
    # os.system("adb shell am start -n com.eg.android.AlipayGphone/.AlipayLogin")
    # # a.cmd("shell am start -n com.eg.android.AlipayGphone/.AlipayLogin")
    # d(text="螞蟻森林").click()
    # # d(text="種樹").click(
    # print d.info
    # d.wait.idle()
    # d.wait.update()
    # d.screenshot("1.png")
    # d(scrollable=True).fling()
    # web = d(className="com.uc.webview.export.WebView")
    # web = d(className="com.uc.webkit.WebView")
    # web.scroll.toEnd()
    # web.swipe.down()
    # web.click(800,940)
    # d.wait.update()
    # web = d(className="com.uc.webview.export.WebView")
    d.screenshot("1.png")
    loc= match()
    print loc
    # print (tl[0]+br[0])/2,(tl[1]+br[1])/2
    # d.click((tl[0]+br[0])/2,(tl[1]+br[1])/2)    
    # d.wait.update()
    # for y in range(400,870,100):
    #     for x in range(50,1080,100):
    #         d.click(x,y)