python实现连连看辅助之图像识别延伸

from aip import AipImageSearch """ 你的 APPID AK SK """ APP_ID = '***' API_KEY = '***' SECRET_KEY = '***' client = AipImageSearch(APP_ID, API_KEY, SECRET_KEY) with open("{}-{}.jpg".format(1, 1), "rb") as f: im = f.read() # im = self.image_list[row][col] # 将图片与百度云自建相似图库中的图片对比相似度 res = client.similarSearch(im) for r in res["result"]: if r["score"] > 0.9: print(r["brief"])

import win32gui import time from PIL import ImageGrab , Image import numpy as np from pymouse import PyMouse from aip import AipImageSearch class GameAuxiliaries(object): def __init__(self): self.wdname = r'宠物连连看经典版2,宠物连连看经典版2小游戏,4399小游戏 www.4399.com - Google Chrome' # self.wdname = r'main.swf - PotPlayer' self.image_list = {} self.m = PyMouse() self.APP_ID = '15633871' self.API_KEY = 'LNMuXHmULcZM0PRKX8ZT4OnB' self.SECRET_KEY = 'IwvyYxeDLIR5XvEmnX3ENWoVzMITkdBL' self.client = AipImageSearch(self.APP_ID, self.API_KEY, self.SECRET_KEY) def find_game_wd(self,wdname): # 取得窗口句柄 hdwd = win32gui.FindWindow(0,wdname) # 设置为最前显示 win32gui.SetForegroundWindow(hdwd) time.sleep(1) def get_img(self): image = ImageGrab.grab((417, 289, 884, 600)) # image = ImageGrab.grab((417, 257, 885, 569)) image.save('1.jpg','JPEG') for x in range(1,9): self.image_list[x] = {} for y in range(1,13): top = (x - 1) * 38 + (x-2) left =(y - 1) * 38 +(y-2) right = y * 38 + (y-1) bottom = x * 38 +(x -1) if top < 0: top = 0 if left < 0 : left = 0 im_temp = image.crop((left,top,right,bottom)) im = im_temp.crop((1,1,37,37)) im.save('{}-{}.jpg'.format(x,y)) self.image_list[x][y]=im def compare_img_baiduapi(self,im): '''将图片与百度云自建相似图库中的图片对比相似度''' pass # 判断两个图片是否相同。汉明距离，平均哈希 def compare_img(self,im1,im2): img1 = im1.resize((20, 20), Image.ANTIALIAS).convert('L') img2 = im2.resize((20, 20), Image.ANTIALIAS).convert('L') pi1 = list(img1.getdata()) pi2 = list(img2.getdata()) avg1 = sum(pi1) / len(pi1) avg2 = sum(pi2) / len(pi2) hash2 = "".join(map(lambda p: "1" if p > avg1 else "0", pi1)) hash3 = "".join(map(lambda p: "1" if p > avg2 else "0", pi2)) match = 0 for i in range(len(hash2)): if hash2[i] != hash3[i]: match += 1 # match = sum(map(operator.ne, hash2, hash3)) # match 值越小，相似度越高 return match # 将图片矩阵转换成数字矩阵 def create_array(self): array = np.zeros((10,14),dtype=np.int32) img_type_list = [] for row in range(1,len(self.image_list)+1): for col in range(1,len(self.image_list[1])+1): # im = Image.open('{}-{}.jpg'.format(row,col)) with open("{}-{}.jpg".format(row,col), "rb") as f: im = f.read() # im = self.image_list[row][col] # 将图片与百度云自建相似图库中的图片对比相似度 res = self.client.similarSearch(im) while len(res) == 2: res = self.client.similarSearch(im) print(res) print(row, col) time.sleep(0.2) print(row,col) for r in res["result"]: if r["score"] > 0.9: array[row][col]=r["brief"] return array def row_zero(self,x1,y1,x2,y2,array): '''相同的图片中间图标全为空''' if x1 == x2: min_y = min(y1,y2) max_y = max(y1,y2) if max_y - min_y == 1: return True for y in range(min_y+1,max_y): if array[x1][y] != 0 : return False return True else: return False def col_zero(self,x1,y1,x2,y2,array): '''相同的图片同列''' if y1 == y2: min_x = min(x1,x2) max_x = max(x1,x2) if max_x - min_x == 1: return True for x in range(min_x+1,max_x): if array[x][y1] != 0 : return False return True else: return False def two_line(self,x1,y1,x2,y2,array): '''两条线相连，转弯一次''' for row in range(1,9): for col in range(1,13): if row == x1 and col == y2 and array[row][col]==0 and self.row_zero(x1,y1,row,col,array) and self.col_zero(x2,y2,row,col,array): return True if row == x2 and col == y1 and array[row][col]==0 and self.row_zero(x2,y2,row,col,array) and self.col_zero(x1,y1,row,col,array): return True return False def three_line(self,x1,y1,x2,y2,array): '''三条线相连，转弯两次''' for row1 in range(10): for col1 in range(14): for row2 in range(10): for col2 in range(14): if array[row1][col1] == array[row2][col2] == 0 and self.row_zero(x1,y1,row1,col1,array) and self.row_zero(x2,y2,row2,col2,array) and self.col_zero(row1,col1,row2,col2,array): return True if array[row1][col1] == array[row2][col2] == 0 and self.col_zero(x1,y1,row1,col1,array) and self.col_zero(x2,y2,row2,col2,array) and self.row_zero(row1,col1,row2,col2,array): return True if array[row1][col1] == array[row2][col2] == 0 and self.row_zero(x2,y2,row1,col1,array) and self.row_zero(x1,y1,row2,col2,array) and self.col_zero(row1,col1,row2,col2,array): return True if array[row1][col1] == array[row2][col2] == 0 and self.col_zero(x2,y2,row1,col1,array) and self.col_zero(x1,y1,row2,col2,array) and self.row_zero(row1,col1,row2,col2,array): return True return False def mouse_click(self,x,y): top = (x - 1) * 38 + (x - 2) left = (y - 1) * 38 + (y - 2) right = y * 38 + (y - 1) bottom = x * 38 + (x - 1) if top < 0: top = 0 if left < 0: left = 0 self.m.press(int(417+(left+right)/2) ,int(289+(top+bottom)/2) ) def find_same_img(self,array): for x1 in range(1,9): for y1 in range(1,13): if array[x1][y1] == 0: continue for x2 in range(1,9): for y2 in range(1,13): if x1==x2 and y1 == y2: continue if array[x2][y2] == 0 : continue if array[x1][y1] != array[x2][y2] : continue if array[x1][y1] ==array[x2][y2] and (self.row_zero(x1,y1,x2,y2,array) or self.col_zero(x1,y1,x2,y2,array) or self.two_line(x1,y1,x2,y2,array) or self.three_line(x1,y1,x2,y2,array)): print("可消除！x{}y{} 和 x{}y{}".format(x1,y1,x2,y2)) self.mouse_click(x1,y1) time.sleep(0.1) self.mouse_click(x2,y2) time.sleep(0.1) array[x1][y1]=array[x2][y2]=0 def run(self): #找到游戏运行窗口 self.find_game_wd(self.wdname) # 截图，切割成小图标 self.get_img() print("切割完成") # 将图片矩阵转换成数字矩阵 array = self.create_array() print(array) # 遍历矩阵，找到可消除项，点击消除 for i in range(10): self.find_same_img(array) print(array) if __name__ == '__main__': ga = GameAuxiliaries() ga.run()

相关阅读