废话不多说，直接上代码吧！

# -*- coding: utf-8 -*-import cv2import numpy as np # -----------------------鼠标操作相关------------------------------------------lsPointsChoose = []tpPointsChoose = []pointsCount = 0count = 0pointsMax = 10def on_mouse(event, x, y, flags, param): global img, point1, point2, count, pointsMax global lsPointsChoose, tpPointsChoose # 存入选择的点 global pointsCount # 对鼠标按下的点计数 global img2, ROI_bymouse_flag img2 = img.copy() # 此行代码保证每次都重新再原图画 避免画多了 # ----------------------------------------------------------- # count=count+1 # print("callback_count",count) # -------------------------------------------------------------- if event == cv2.EVENT_LBUTTONDOWN: # 左键点击 pointsCount = pointsCount + 1 # 感觉这里没有用？2018年8月25日20:06:42 # 为了保存绘制的区域，画的点稍晚清零 # if (pointsCount == pointsMax + 1): # pointsCount = 0 # tpPointsChoose = [] print('pointsCount:', pointsCount) point1 = (x, y) print (x, y) # 画出点击的点 cv2.circle(img2, point1, 10, (0, 255, 0), 2) # 将选取的点保存到list列表里 lsPointsChoose.append([x, y]) # 用于转化为darry 提取多边形ROI tpPointsChoose.append((x, y)) # 用于画点 # ---------------------------------------------------------------------- # 将鼠标选的点用直线连起来 print(len(tpPointsChoose)) for i in range(len(tpPointsChoose) - 1): print('i', i) cv2.line(img2, tpPointsChoose[i], tpPointsChoose[i + 1], (0, 0, 255), 2) # ---------------------------------------------------------------------- # ----------点击到pointMax时可以提取去绘图---------------- if (pointsCount == pointsMax): # -----------绘制感兴趣区域----------- ROI_byMouse() ROI_bymouse_flag = 1 lsPointsChoose = [] cv2.imshow('src', img2) # -------------------------右键按下清除轨迹----------------------------- if event == cv2.EVENT_RBUTTONDOWN: # 右键点击 print("right-mouse") pointsCount = 0 tpPointsChoose = [] lsPointsChoose = [] print(len(tpPointsChoose)) for i in range(len(tpPointsChoose) - 1): print('i', i) cv2.line(img2, tpPointsChoose[i], tpPointsChoose[i + 1], (0, 0, 255), 2) cv2.imshow('src', img2) def ROI_byMouse(): global src, ROI, ROI_flag, mask2 mask = np.zeros(img.shape, np.uint8) pts = np.array([lsPointsChoose], np.int32) # pts是多边形的顶点列表（顶点集） pts = pts.reshape((-1, 1, 2)) # 这里 reshape 的第一个参数为-1, 表明这一维的长度是根据后面的维度的计算出来的。 # OpenCV中需要先将多边形的顶点坐标变成顶点数×1×2维的矩阵，再来绘制 # --------------画多边形--------------------- mask = cv2.polylines(mask, [pts], True, (255, 255, 255)) ##-------------填充多边形--------------------- mask2 = cv2.fillPoly(mask, [pts], (255, 255, 255)) cv2.imshow('mask', mask2) cv2.imwrite('mask.jpg', mask2) ROI = cv2.bitwise_and(mask2, img) #cv2.imwrite('ROI.bmp', ROI) #cv2.imshow('ROI', ROI) # -----------------------定点ROI绘制，程序中未使用-------------------def fixed_ROI(): mask = np.zeros(img.shape, np.uint8) pts = np.array([[x1, y1], [x2, y2], [x3, y3], [x4, y4]], np.int32) # 顶点集 pts = pts.reshape((-1, 1, 2)) mask = cv2.polylines(mask, [pts], True, (255, 255, 255)) mask2 = cv2.fillPoly(mask, [pts], (255, 255, 255)) cv2.imshow('mask', mask2) # cv2.imwrite('mask.bmp', mask2) # cv2.drawContours(mask,points,-1,(255,255,255),-1) ROI = cv2.bitwise_and(mask2, img) cv2.imshow('ROI', ROI) # cv2.imwrite('ROI.bmp', ROI) img = cv2.imread('yuantu.jpg')# ---------------------------------------------------------# --图像预处理，设置其大小# height, width = img.shape[:2]# size = (int(width * 0.3), int(height * 0.3))# img = cv2.resize(img, size, interpolation=cv2.INTER_AREA)# ------------------------------------------------------------ROI = img.copy()cv2.namedWindow('src')cv2.setMouseCallback('src', on_mouse)cv2.imshow('src', img)cv2.waitKey(0)

以上这篇python3+opencv生成不规则黑白mask实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。