Python&Auto.js:实现蚂蚁森林自动收能量(懒人的高效生活)

本脚本支持仅1920*1080 像素分辨率的机子上面正常运行。

-------------------------------------------------------------------------------

我是真的懒,连能量都不想好好收,因此写了脚本来自动帮我收能量.

Auto.js 这款脚本应用我们在应用市场可以很方便搜索到,它在没有root的时候可以通过开启无障碍服务来实现模拟点击滑动,监听等等.使用下面这个脚本,可以实现打开支付宝,进入蚂蚁森林(你得将它添加到主页常用子应用中),滑动,查找有能量的好友,进入收集。

好好享用，那么上代码：

/**
 * 
 * @name 支付宝自动收能量脚本
 * @author Oliver
 * @description 需要您的设备分辨率为1920*1080；小米8上，截图需要手动允许，需要点击 “立即开始”; 开始运行时请保证支付宝已经处于首页
 */

auto();
main();

/**
 * 下面注释代码可以进一步完善，读取到可以收取的时间，做个记录，然后到时间自动进去收集
 * 
events.observeNotification();
events.onToast(function (toast) {
    var text = toast.getText();
    var appName = toast.getPackageName();
    var subIdx = text.indexOf("后");

    if (appName == "com.eg.android.AlipayGphone" && subIdx != -1) {
        var sub = text.substring(0, subIdx);
        var idxHour = sub.indexOf("小时");
        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();

var nextTime = 900000000000;
 */

var end = false;

function main() {
    toast("程序开始运行！");
    launchApp("支付宝");
    sleep(3000);
    click("蚂蚁森林"); //为了这后面正常运行，将蚂蚁森林放在支付宝首页中
    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("现在开始收集能量了！");
    while (!end) {
        execute();
    }
}

function execute() {
    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() {
    if (!requestScreenCapture()) {
        toast("没有截图权限，程序退出！");
        exit();
        end = true;
    }
    var img = captureScreen();
    for (var i = 187; i <= 1816; i = i + 200) {
        if (isEnd(img, i)) {
            back();
            sleep(1000);
            back();
            sleep(1000);
            back();
            sleep(1000);
            toast("完成任务啦！")
            end = true

        }
        var p = getColor(img, i);
        if (p) {
            click(1017, p.y + 20);
            sleep(3000);
            collect();
            back();
            sleep(1000);
        } else {
            log(i + " p=null");
        }
    }
}

function getColor(img, y) {
    var p = findColor(img, "#30bf6c", {
        region: [1017, y, 63, 100]
    });
    return p;
}

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

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

 

Python中的实现,我们使用android的自动化测试库uiautomator来实现,使用opencv来实现对截图的中可搜集小手的识别,目前还不是很完善,提供一个思路,希望有时间的你来实现,其实Auto.js那个真的好用;-)

 

#! -*- 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="蚂蚁森林").click()
    # # d(text="种树").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)