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opencv|python处理缺陷图象返回缺陷面积数量

opencvPython

import cv2 import numpy as np import os global allmin global allmax global allarea global allnum allmin=50000 allmax=0 allarea=0 allnum=0 def Change(img): # 改黑白图为白黑图，也可以用cvThreshold函数 sp = img.shape height = sp[0]# height(rows) of image width = sp[1]# width(colums) of image size = (width, height) iTmp = np.zeros(img.shape, np.uint8) for i in range(height): for j in range(width): iTmp[i, j] = 255 - img[i, j] cv2.imwrite(path, iTmp)# 覆盖原黑白图 print("图像 %s 覆盖成功！" % (path))# 消除微小区域 def Big(contour): c_max = [] for i in range(len(contour)): cnt = contours[i] area = cv2.contourArea(cnt) if area < 30: contour.append(contour[i]) c_min = [] c_min.append(cnt) # thickness不为-1时，表示画轮廓线，thickness的值表示线的宽度。 cv2.drawContours(img, c_min, -1, (0, 0, 0), thickness=-1) continue c_max.append(cnt) cv2.drawContours(img, c_max, -1, (255, 255, 255), thickness=-1) cv2.imwrite(path, img) print("图像 %s 修改成功！" % (path))def areaCal(contour): global allmin global allmax global allarea global allnum area = 0 min=111111 max=0for i in range(len(contour)): if cv2.contourArea(contour[i])>10: if cv2.contourArea(contour[i])>max: max=cv2.contourArea(contour[i]) if cv2.contourArea(contour[i])# print(len(contour)) print("共 %d 个区域，第 %d 个区域的面积为： %d" %(len(contour),i+1,cv2.contourArea(contour[i]))) if area == 0: min = 0 if min < allmin and min > 0: allmin = min if max > allmax: allmax = max allarea +=area allnum += len(contour) print("区域总面积为：%d,最大面积为： %d，最小面积为： %d" % (area,max,min)) #计算缺陷周长 def perimeterCal(contour):perimeter=0 for i in range(len(contour)): if cv2.arcLength(contour[i],True)>10: perimeter += cv2.arcLength(contour[i],True) # print("共 %d 个缺陷，第 %d 个缺陷的周长为： %d" % (len(contour), i+1, cv2.arcLength(contour[i],True))) print("区域总周长为：%d" % perimeter)num=0 filenum = 0 print("程序开始运行......") # if num==668: while num<1600: num += 1 path='E:/cvtest/'+ str(num) +'.bmp' if os.path.exists(path): filenum += 1 img = cv2.imread(path) print("图像 %s 加载成功！" %(path)) # Change(img) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) ret, binary = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY) # 轮廓检测函数 binary,contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # 绘制轮廓 cv2.drawContours(img, contours, -1, (0, 0, 255), 3) # Big(contours) areaCal(contours) perimeterCal(contours) cv2.imshow("binary", binary) cv2.imshow("outline", img) cv2.waitKey(0) cv2.destroyAllWindows()averagearea = allarea/allnum averagenum = allnum/filenum print("区域最大面积为：%d" % (allmax)) print("区域最小面积为：%d" % (allmin)) print("区域平均面积为：%d" % (averagearea)) print("区域平均数量为：%d" % (averagenum)) print("区域总数量为：%d" % (allnum)) print("图像总数量为：%d" % (filenum))

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