python識(shí)別圍棋定位棋盤位置

更新時(shí)間：2021年07月26日 10:44:57 作者：翟羽嚄

最近需要做一個(gè)圍棋識(shí)別的項(xiàng)目，本文就介紹了棋盤位置定位，文中通過(guò)示例代碼介紹的非常詳細(xì)，具有一定的參考價(jià)值，感興趣的小伙伴們可以參考一下

效果圖

原圖

在這里插入圖片描述

中間處理效果

在這里插入圖片描述

最終結(jié)果

在這里插入圖片描述

思路分析

我們利用python opencv的相關(guān)函數(shù)進(jìn)行操作實(shí)現(xiàn)，根據(jù)棋盤顏色的特征，尋找到相關(guān)特征，將棋盤區(qū)域摳出來(lái)。最好從原始圖像中將棋盤位置截取出來(lái)。

源碼：定位棋盤位置

from PIL import ImageGrab
import numpy as np
import cv2
from glob import glob

imglist = 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([10,0,0])
    upper = np.array([40,255,255])
    mask = cv2.inRange(hsv,lower,upper)
    erodeim = cv2.erode(mask,None,iterations=2)  # 腐蝕 
    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

    #多邊形擬合
    epsilon = 0.02*cv2.arcLength(contours[maxint],True)
    if epsilon<1:
        continue
    
    #多邊形擬合
    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()

帶保存圖像

from PIL import ImageGrab
import numpy as np
import cv2
from glob import glob
import os

imglist = sorted(glob("screen/*.jpg"))
a=0
for i in imglist:
# while 1:
    a=a+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([10,0,0])
    upper = np.array([40,255,255])
    mask = cv2.inRange(hsv,lower,upper)
    erodeim = cv2.erode(mask,None,iterations=2)  # 腐蝕 
    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)

    # 保存圖片的地址
    img_file_1 = "./temp"
    # 確認(rèn)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 = 0
    maxarea = 0
    nextarea = 0
    maxint = 0
    for c in contours:
        if cv2.contourArea(c)>maxarea:
            maxarea = cv2.contourArea(c)
            maxint = i
        i+=1

    #多邊形擬合
    epsilon = 0.02*cv2.arcLength(contours[maxint],True)
    if epsilon<1:
        continue
    
    #多邊形擬合
    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)
    # 保存圖片的地址
    img_file_2 = "./checkerboard"
    # 確認(rèn)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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