python实现连连看辅助–图像识别延伸（百度AI），供大家参考，具体内容如下百度AI平台提
python实现连连看辅助–图像识别延伸（百度AI），供大家参考，具体内容如下
百度AI平台提供图片相似检索API接口，并有详细的API文档说明，可以更好的实现图片识别。
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"])百度AI平台提供非常多的API接口，值得研究。
代码
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)
hash1 = "".join(map(lambda p: "1" if p > avg1 else "0", pi1))
hash2 = "".join(map(lambda p: "1" if p > avg2 else "0", pi2))
match = 0
for i in range(len(hash1)):
if hash1[i] != hash2[i]:
match += 1
# match = sum(map(operator.ne, hash1, hash2))
# 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()以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。
python 连连看 图像识别