到现在为止,我们通过前面几篇博文的描述和分析,已经可以自动实现棋子、棋盘位置的准确判断,计算一下两个中心点之间的距离,并绘制在图形上,效果如下。
效果
图中的棋子定位采用hsv颜色识别,棋盘定位采用轮廓分割的方法获得,感兴趣的同学可以对其它的定位方法自行验证。
代码
python" id="highlighter_145612">
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# -*- coding: utf-8 -*- #vs2017+python3.6+opencv3.4 #2018.02.03 #作者:艾克思 import cv2 import numpy as np import math def hsv(frame): lower_blue = np.array([ 115 , 75 , 75 ]) #设定蓝色的阈值 upper_blue = np.array([ 130 , 255 , 125 ]) r = 0 #初始半径=0 x,y = 0 , 0 hsv = cv2.cvtcolor(frame, cv2.color_bgr2hsv) #转到hsv空间 mask_blue = cv2.inrange(hsv, lower_blue, upper_blue) cnts = cv2.findcontours(mask_blue, cv2.retr_external, cv2.chain_approx_simple)[ - 2 ] if len (cnts) > 0 : c = max (cnts, key = cv2.contourarea) #找到面积最大的轮廓 ((x, y), radius) = cv2.minenclosingcircle(c) #确定面积最大的轮廓的外接圆 center = ( int (x), int (y)) return center def thresh(img): x,y,w,h,x1,y1,w1,h1,x2,y2,w2,h2 = 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 gray = cv2.cvtcolor(img, cv2.color_bgr2gray) #gray=cv2.gaussianblur(gray,(13,13),0)#转化为灰度图 h0,w0 = img.shape[: 2 ] top = gray[h0 / / 3 , 1 ] bottom = gray[h0 * 2 / / 3 , 1 ] #min_vale=min(top,bottom) #max_vale=max(top,bottom) thresh1 = cv2.threshold(gray,top, 255 , cv2.thresh_binary)[ 1 ] thresh2 = cv2.threshold(gray, 175 , 255 , cv2.thresh_binary_inv)[ 1 ] img1 = thresh1[h0 / / 3 :h0 * 2 / / 3 , 0 :w0] img2 = thresh2[h0 / / 3 :h0 * 2 / / 3 , 0 :w0] cnts1, hierarchy1, rr1 = cv2.findcontours(img1,cv2.retr_external,cv2.chain_approx_simple) cnts2, hierarchy2, rr2 = cv2.findcontours(img2,cv2.retr_external,cv2.chain_approx_simple) aim1 = 0 y_min = h0 / / 3 for c in hierarchy1: if hierarchy1 = = none: x1,y1,w1,h1 = w0 / / 2 ,h0 / / 3 ,w0 / / 3 ,h0 / / 3 break else : x,y,w,h = cv2.boundingrect(c) if y< = y_min: y_min = y aim1 = c x1,y1,w1,h1 = cv2.boundingrect(aim1) #cv2.rectangle(img,(x1,y1+h0//3),(x1+w1,y1+h1+h0//3),(0,0,255),2) aim2 = 0 y_min = h0 / / 3 for c in hierarchy2: if hierarchy2 = = none: x2,y2,w2,h2 = w0 / / 2 ,h0 / / 3 ,w0 / / 3 ,h0 / / 3 break else : x,y,w,h = cv2.boundingrect(c) if y< = y_min: y_min = y aim2 = c x2,y2,w2,h2 = cv2.boundingrect(aim2) #cv2.rectangle(img,(x2,y2+h0//3),(x2+w2,y2+h2+h0//3),(0,255,255),2) if y1 + h1 / / 2 < = y2 + h2 / / 2 : x,y,w,h = x1,y1,w1,h1 else : x,y,w,h = x2,y2,w2,h2 cv2.imshow( 'img1' ,thresh1) cv2.imshow( 'img2' ,thresh2) return (x + w / / 2 ,y + h0 / / 3 + h / / 2 ) def length(pt1,pt2): x1,y1 = pt1 x2,y2 = pt2 length = math.sqrt((x2 - x1) * * 2 + (y2 - y1) * * 2 ) return int (length) def main(): filepath = 'e:/python/jump/hsv/007.png' video = 'e:/python/jump/blackwhite/jumpnew.avi' cap = cv2.videocapture(video) ret = cap.isopened() ret = true while ret: #ret,img=cap.read() #读入帧 img = cv2.imread(filepath) if not ret:cv2.waitkey( 0 ) point1 = hsv(img) point2 = thresh(img) len = length(point1,point2) cv2.circle(img,point1, 3 ,( 0 , 0 , 255 ), - 1 ) cv2.circle(img,point1, 15 ,( 0 , 0 , 255 ), 2 ) cv2.circle(img,point2, 3 ,( 0 , 0 , 255 ), - 1 ) cv2.circle(img,point2, 15 ,( 0 , 0 , 255 ), 2 ) cv2.line(img,point1,point2,( 255 , 255 , 255 ), 2 ) cv2.puttext(img, '{}' . format ( len ) ,(point2[ 0 ] - 10 ,point2[ 1 ] - 20 ), cv2.font_hershey_simplex, 0.6 , ( 0 , 0 , 255 ), 2 ,cv2.line_8, 0 ) cv2.imshow( 'img' ,img) #cv2.imwrite(filepath,img) cv2.waitkey( 0 ) cap.release() cv2.destroyallwindows() if __name__ = = '__main__' : main() |
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服务器之家。
原文链接:http://blog.csdn.net/m0_37606112/article/details/79248699