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play.py
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# coding:utf-8
import os
import cv2
import numpy as np
import time
import pylab as pl
import random
import threading
import time
from DobotDemoForPython import DobotDllType as dType
from math import *
CON_STR = {
dType.DobotConnect.DobotConnect_NoError: "DobotConnect_NoError",
dType.DobotConnect.DobotConnect_NotFound: "DobotConnect_NotFound",
dType.DobotConnect.DobotConnect_Occupied: "DobotConnect_Occupied"}
#Load Dll
api = dType.load()
postion=[237.7514,49.2358,-25.7501, 7.1569]
def init():
# dType.SetHOMEParams(api,postion[0],postion[1],postion[2],postion[3], isQueued=1)
speed1=100
speed = 500
coordinate=4000
dType.SetPTPJointParams(api, speed1,speed1,speed1,speed1,speed1,speed1,speed1,speed1, isQueued=1)
# dType.SetPTPCommonParams(api, speed, speed, isQueued=1)
dType.SetPTPCoordinateParams(api,coordinate,coordinate,coordinate,coordinate,isQueued=1)
# Async Home
# dType.SetHOMECmd(api, temp=0, isQueued=1)
def init1():
speed1=100
speed = 500
coordinate=9000
dType.SetPTPJointParams(api, speed1,speed1,speed1,speed1,speed1,speed1,speed1,speed1, isQueued=1)
dType.SetPTPCoordinateParams(api,coordinate,coordinate,coordinate,coordinate,isQueued=1)
def work(press_time):
print("worktime",press_time)
print(type(press_time))
dType.SetQueuedCmdClear(api)
init()
waitTime=press_time*0.001
offset=0;offset1=0
for i in range(0, 5):
print(i)
if i % 4 == 0:
offset = 0;offset1=-70
elif i % 4 == 1:
offset = 0;offset1=0
elif i % 4 == 2:
offset = 20;offset1=0
elif i % 4 == 3:
offset = 0;offset1=0
# time.sleep(2)
lastIndex = dType.SetPTPCmd(api, dType.PTPMode.PTPMOVLXYZMode,postion[0]+offset1,postion[1],postion[2]-offset,postion[3])[0] # 移动
dType.SetWAITCmd(api, waitTime)
dType.SetQueuedCmdStartExec(api)
def work1(press_time):
i=0
print("worktime",press_time)
print(type(press_time))
dType.SetQueuedCmdClear(api)
if press_time<=450:
init1()
else:
init()
waitTime=press_time*0.001
# waitTime=waitTime1
offset=0
for i in range(0, 2):
print(i)
if i % 2 == 0:
offset=20
elif i % 2 == 1:
offset=0
lastIndex = dType.SetPTPCmd(api, dType.PTPMode.PTPMOVLXYZMode,postion[0],postion[1],postion[2]-offset,postion[3])[0] # 移动
dType.SetWAITCmd(api, waitTime)
dType.SetQueuedCmdStartExec(api)
while lastIndex > dType.GetQueuedCmdCurrentIndex(api)[0]:
dType.dSleep(0)
dType.SetQueuedCmdStopExec(api)
dType.SetQueuedCmdClear(api)
def moveForward():
dType.SetQueuedCmdClear(api)
init()
offset=0;offset1=0
lastIndex = dType.SetPTPCmd(api, dType.PTPMode.PTPMOVLXYZMode,postion[0],postion[1],postion[2],postion[3])[0] # 移动
dType.SetQueuedCmdStartExec(api)
while lastIndex > dType.GetQueuedCmdCurrentIndex(api)[0]:
dType.dSleep(0)
dType.SetQueuedCmdStopExec(api)
dType.SetQueuedCmdClear(api)
def moveBack():
dType.SetQueuedCmdClear(api)
init()
lastIndex = dType.SetPTPCmd(api, dType.PTPMode.PTPMOVLXYZMode,postion[0]-70,postion[1],postion[2],postion[3])[0] # 移动
dType.SetQueuedCmdStartExec(api)
while lastIndex > dType.GetQueuedCmdCurrentIndex(api)[0]:
dType.dSleep(0)
#Stop to Execute Command Queued
dType.SetQueuedCmdStopExec(api)
dType.SetQueuedCmdClear(api)
def jump(distance):
# 这个参数还需要针对屏幕分辨率进行优化
coffine=1.19
press_time = int(distance * coffine)
print(distance)
# 生成随机手机屏幕模拟触摸点
# 模拟触摸点如果每次都是同一位置，成绩上传可能无法通过验证
rand = random.randint(0, 9) * 10
cmd = ('adb shell input swipe %i %i %i %i ' + str(press_time)) \
% (320 + rand, 410 + rand, 320 + rand, 410 + rand)
os.system(cmd)
print(cmd)
print("press_time: ",press_time)
return press_time
# os.remove("last.png")
def get_center(img_canny, ):
# 利用边缘检测的结果寻找物块的上沿和下沿
# 进而计算物块的中心点
startY=520
linewith1=np.nonzero([max(row) for row in img_canny[startY:]])
y_center=0
x_center=0
maxl=0
cnt=0
cnt0=0
l=0; r = 0
maxl1=0
flag=False
for i in range(len(linewith1[0])):
# print(i)
y0_temp = linewith1[0][i] + startY
x0_list = np.nonzero(canny_img[y0_temp])[0]
if x0_list[-1]-x0_list[0]<20:
continue
if flag and x0_list[-1]-x0_list[0]-maxl>150:
print("-1 len(x0_list[0]) :", len(x0_list), "x0_list: ", x0_list)
cnt0+=1
if cnt0>20 :
cnt=0
maxl=x0_list[-1]-x0_list[0]
x_center = int((x0_list[-1] + x0_list[0]) / 2)
y_center = y0_temp
continue
if x0_list[-1]-x0_list[0]>maxl :
print("0 len(x0_list[0]) :",len(x0_list),"x0_list: ",x0_list)
cnt=0
flag=True
cnt0=0
maxl=x0_list[-1]-x0_list[0]
l=x0_list[0];r=x0_list[-1]
x_center=int((x0_list[-1]+x0_list[0])/2)
y_center=y0_temp
if x0_list[-1]-x0_list[0]<=maxl and maxl>50 :
print("1 len(x0_list[0]) :", len(x0_list), "x0_list: ", x0_list)
# break
cnt0=0
cnt+=1
if cnt>3:
break
print("l is ",l,'\t','r is' , r , '\t','x_c is ',x_center)
print("x_center,y_center: ",x_center,y_center)
return img_canny,x_center,y_center
def find4point(points):
lt = None
rt = None
lb = None
rb = None
# points = points[np.argsort(points[:][0])]
points = points[points[:, 0].argsort()]
print(points)
if points[0][1] > points[1][1]:
lt = points[1]
lb = points[0]
else:
lt = points[0]
lb = points[1]
if points[2][1] > points[3][1]:
rt = points[3]
rb = points[2]
else:
rt = points[2]
rb = points[3]
return ((lt[0], lt[1]), (lb[0], lb[1]), (rt[0], rt[1]), (rb[0], rb[1]))
def getScreen(img_rgb):
img0=img_rgb
# img_rgb = cv2.GaussianBlur(img_rgb, (11,11), 0)
img_rgb = cv2.bilateralFilter(img_rgb,7, 80, 80)
# img_rgb = cv2.medianBlur(img_rgb, 7)
# cv2.imwrite("a11.png",img_rgb)
# img_rgb =cv2.GaussianBlur(img_rgb, (9,9), 0)
canny_img = cv2.Canny(img_rgb, 10, 28)
# canny_img = cv2.GaussianBlur(canny_img, (11,11), 0)
img_rgb=canny_img
# gray_lap = cv2.Laplacian(img_rgb,cv2.CV_32F,ksize = 3)
# img_rgb = cv2.convertScaleAbs(gray_lap)
img_rgb = cv2.GaussianBlur(img_rgb, (9,13), 0)
# cv2.imwrite("ccc.png",img_rgb)
gray=img_rgb
# img=gray
ret, binary = cv2.threshold(gray,0,255,cv2.THRESH_BINARY)
_,contours0, hierarchy = cv2.findContours(binary, cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
size_rectangle_max = 0;
maxi=0
for i in range(len(contours0)):
#aproximate countours to polygons
approximation = cv2.approxPolyDP(contours0[i], 20, True)
size_rectangle = cv2.contourArea(approximation)
#store the biggest
if size_rectangle> size_rectangle_max:
size_rectangle_max = size_rectangle
big_rectangle = approximation
maxi=i
cv2.drawContours(canny_img,contours0,maxi,(0,0,0),40)
# for con in contours0[maxi][:,0]:
# cv2.circle(img0,tuple(con),10,255,-1)
# _=pl.imshow(img0)
# pl.show()
pentagram = contours0[maxi]
cnt=pentagram
rect = cv2.minAreaRect(cnt) # 最小外接矩形
box = np.int0(cv2.boxPoints(rect)) # 矩形的四个角点取整
print(box)
cv2.drawContours((img0), [box], 0, (255, 0, 0), 2)
lu,ld,ru,rd=find4point(box)
print(lu,ru,ld,rd)
#warp
# 原图中卡片的四个角点
pts1 = np.float32([lu,ru, ld, rd])
# 变换后分别在左上、右上、左下、右下四个点
pts2 = np.float32([[0, 0], [1080, 0], [0, 1920], [1080, 1920]])
# 生成透视变换矩阵
M = cv2.getPerspectiveTransform(pts1, pts2)
# 进行透视变换
dst = cv2.warpPerspective(canny_img, M, (1080, 1920))
dst0 = cv2.warpPerspective(img0, M, (1080,1920))
# plt.subplot(121), plt.imshow(img[:, :, ::-1]), plt.title('input')
# plt.subplot(122), plt.imshow(dst[:, :, ::-1]), plt.title('output')
# plt.show()
return dst0,dst
class wechatJump(QtCore.QObject):
"""wechatJump Logic and Motion Part"""
runSig = QtCore.pyqtSignal()
runFlag= True
def runSigCall(self):
"""accept signal from AllForOne to stop jump"""
self.runFlag = False
def main(self,w_length,h_length,sig):
self.runFlag=True
self.runSig.connect(self.runSigCall)
state = dType.ConnectDobot(api, "", 115200)[0]
# 匹配小跳棋的模板
temp1 = cv2.imread('temp_player.jpg', 0)
w1, h1 = temp1.shape[::-1]
# 匹配游戏结束画面的模板
temp_end = cv2.imread('temp_end.jpg', 0)
# 匹配中心小圆点的模板
temp_white_circle = cv2.imread('temp_white_circle.jpg', 0)
w2, h2 = temp_white_circle.shape[::-1]
# 循环直到游戏失败结束
for i in range(10000):
# get_screenshot(0)
if not self.runFlag:
break
img_rgb = cv2.imread('phone.png', 0)
img_rgb = np.transpose(img_rgb);
img_rgb = cv2.flip(img_rgb, 0);
# cv2.imwrite("imgs/"+str(i)+"_origin.png",img_rgb)
# 如果在游戏截图中匹配到带"再玩一局"字样的模板，则循环中止
res_end = cv2.matchTemplate(img_rgb, temp_end, cv2.TM_CCOEFF_NORMED)
if cv2.minMaxLoc(res_end)[1] > 0.8:
print('Game over!')
break
img_rgb, canny_img = getScreen(img_rgb)
# cv2.imwrite("pre.png", img_rgb)
cv2.imwrite("imgs/"+str(i)+"_pre.png",img_rgb)
# 模板匹配截图中小跳棋的位置
# canny_img=pre_process(canny_img)
res1 = cv2.matchTemplate(img_rgb, temp1, cv2.TM_CCOEFF_NORMED)
min_val1, max_val1, min_loc1, max_loc1 = cv2.minMaxLoc(res1)
print(max_val1)
if(max_val1<0.5):
continue
if state == dType.DobotConnect.DobotConnect_NoError:
print("ccc")
moveForward()
print("ddd")
left_top = max_loc1 # 左上角
right_bottom = (left_top[0] + w1, left_top[1] + h1) # 右下角
center1_loc = (int((left_top[0] + right_bottom[0]) / 2), int((left_top[1] + right_bottom[1]) / 2) + int(h1 / 2))
print(center1_loc)
cv2.rectangle(img_rgb, left_top, right_bottom, 255, 2)
# 先尝试匹配截图中的中心原点，
# 如果匹配值没有达到0.95，则使用边缘检测匹配物块上沿
res2 = cv2.matchTemplate(img_rgb, temp_white_circle, cv2.TM_CCOEFF_NORMED)
min_val2, max_val2, min_loc2, max_loc2 = cv2.minMaxLoc(res2)
if max_val2 > 0.91:
print('found white circle!')
x_center, y_center = max_loc2[0] + w2 // 2, max_loc2[1] + h2 // 2
else:
# 边缘检测
H, W = canny_img.shape
# cv2.imwrite("canny.png", canny_img)
# 消去小跳棋轮廓对边缘检测结果的干扰
for k in range(left_top[1], right_bottom[1]):
for b in range(left_top[0], right_bottom[0]):
canny_img[k][b] = 0
img_rgb, x_center, y_center = get_center(canny_img)
# 将图片输出以供调试
img_rgb = cv2.circle(img_rgb, (x_center, y_center), 10, 255, -1)
img_rgb = cv2.circle(img_rgb, center1_loc, 10, 255, -1)
# cv2.rectangle(canny_img, max_loc1, center1_loc, 255, 2)
cv2.imwrite('last.png', img_rgb)
cv2.imwrite("imgs/"+str(i)+'_last.png',img_rgb)
print("last write down")
distance = (center1_loc[0] - x_center) ** 2 + (center1_loc[1] - y_center) ** 2
distance = distance ** 0.5
print("distance:", distance)
press_time = jump(distance)
sig.emit(press_time)
# file.writelines(str(distance)+'\t'+str(press_time)+'\n')
if state == dType.DobotConnect.DobotConnect_NoError:
work1(press_time)
time.sleep(1.7)
moveBack()
time1=0.2
time.sleep(time1)
divide = 500.0
if press_time/divide<time1:
time.sleep(time1)
else:
time.sleep(press_time / divide)
print(press_time/divide)
# Disconnect Dobot
dType.DisconnectDobot(api)