python识别围棋定位棋盘位置
目录[*]效果图
[*]思路分析
[*]源码：定位棋盘位置
最近必要做一个围棋识别的项目，首先要将棋盘位置定位出来，效果图如下：
效果图
原图
http://img.jbzj.com/file_images/article/202107/2021072610400167.jpg
中间处理效果
http://img.jbzj.com/file_images/article/202107/2021072610400168.jpg
最终结果
http://img.jbzj.com/file_images/article/202107/2021072610400169.jpg
思路分析
我们使用python opencv的相关函数进行操纵实现，根据棋盘颜色的特性，寻找到相关特性，将棋盘区域抠出来。最好从原始图像中将棋盘位置截取出来。
源码：定位棋盘位置
from PIL import ImageGrabimport numpy as npimport cv2from glob import globimglist = sorted(glob("screen/*.jpg"))for i in imglist:# while 1: img = cv2.imread(i) image = img.copy() w,h,c = img.shape img2 =np.zeros((w,h,c), np.uint8) img3 =np.zeros((w,h,c), np.uint8) # img = ImageGrab.grab() #bbox specifies specific region (bbox= x,y,width,height *starts top-left) hsv=cv2.cvtColor(img,cv2.COLOR_BGR2HSV) lower = np.array() upper = np.array() mask = cv2.inRange(hsv,lower,upper) erodeim = cv2.erode(mask,None,iterations=2)# 腐蚀 dilateim = cv2.dilate(erodeim,None,iterations=2) img = cv2.bitwise_and(img,img,mask=dilateim) frame = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) ret, dst = cv2.threshold(frame, 100, 255, cv2.THRESH_BINARY) contours,hierarchy = cv2.findContours(dst, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) cv2.imshow("0",img) i = 0 maxarea = 0 nextarea = 0 maxint = 0 for c in contours: if cv2.contourArea(c)>maxarea: maxarea = cv2.contourArea(c) maxint = i i+=1 #多边形拟合 epsilon = 0.02*cv2.arcLength(contours,True) if epsilonmaxarea: maxarea = cv2.contourArea(c) maxint = i i+=1 #多边形拟合 epsilon = 0.02*cv2.arcLength(contours,True) if epsilon
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