python识别围棋定位棋盘位置 python识别围棋定位棋盘位置

效果图
思路分析
源码：定位棋盘位置

最近需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

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中间处理效果

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最终结果

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思路分析我们利用python opencv的相关函数进行操作实现，根据棋盘颜色的特征，寻找到相关特征，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.shapeimg2 =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([10,0,0])upper = np.array([40,255,255])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 = 0maxarea = 0nextarea = 0maxint = 0for c in contours:if cv2.contourArea(c)>maxarea:maxarea = cv2.contourArea(c)maxint = ii+=1#多边形拟合epsilon = 0.02*cv2.arcLength(contours[maxint],True)if epsilon<1:continue#多边形拟合approx = cv2.approxPolyDP(contours[maxint],epsilon,True)[[x1,y1]] = approx[0][[x2,y2]] = approx[2]checkerboard = image[y1:y2,x1:x2]cv2.imshow("1",checkerboard)cv2.waitKey(1000)cv2.destroyAllWindows()

带保存图像

from PIL import ImageGrabimport numpy as npimport cv2from glob import globimport osimglist = sorted(glob("screen/*.jpg"))a=0for i in imglist:# while 1:a=a+1img = cv2.imread(i)image = img.copy()w,h,c = img.shapeimg2 =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([10,0,0])upper = np.array([40,255,255])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)# 保存图片的地址img_file_1 = "./temp"# 确认上述地址是否存在if not os.path.exists(img_file_1):os.mkdir(img_file_1)cv2.imshow("0",img)cv2.imwrite(img_file_1 + "/" + 'temp_%d.jpg'%a, img)i = 0maxarea = 0nextarea = 0maxint = 0for c in contours:if cv2.contourArea(c)>maxarea:maxarea = cv2.contourArea(c)maxint = ii+=1#多边形拟合epsilon = 0.02*cv2.arcLength(contours[maxint],True)if epsilon<1:continue#多边形拟合approx = cv2.approxPolyDP(contours[maxint],epsilon,True)[[x1,y1]] = approx[0][[x2,y2]] = approx[2]checkerboard = image[y1:y2,x1:x2]cv2.imshow("1",checkerboard)cv2.waitKey(1000)# 保存图片的地址img_file_2 = "./checkerboard"# 确认上述地址是否存在if not os.path.exists(img_file_2):os.mkdir(img_file_2)cv2.imwrite(img_file_2 + "/" + 'checkerboard_%d.jpg'%a, checkerboard)cv2.destroyAllWindows()

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