本脚本支持仅19201080 像素分辨率的机子上面正常运行。*

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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);

}

}

}

image.gif

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)

image.gif