Python+OpenCV进行不规则多边形ROI区域提取

import cv2
 
import numpy as np
import joblib
 
pts = []  # 用于存放点
 
 
# 统一的：mouse callback function
def draw_roi(event, x, y, flags, param):
    img2 = img.copy()
 
    if event == cv2.EVENT_LBUTTONDOWN:  # 左键点击，选择点
        pts.append((x, y))
 
    if event == cv2.EVENT_RBUTTONDOWN:  # 右键点击，取消最近一次选择的点
        pts.pop()
 
    if event == cv2.EVENT_MBUTTONDOWN:  # 中键绘制轮廓
        mask = np.zeros(img.shape, np.uint8)
        points = np.array(pts, np.int32)
        points = points.reshape((-1, 1, 2))
        # 画多边形
        mask = cv2.polylines(mask, [points], True, (255, 255, 255), 2)
        mask2 = cv2.fillPoly(mask.copy(), [points], (255, 255, 255))  # 用于求 ROI
        mask3 = cv2.fillPoly(mask.copy(), [points], (0, 255, 0))  # 用于 显示在桌面的图像
 
        show_image = cv2.addWeighted(src1=img, alpha=0.8, src2=mask3, beta=0.2, gamma=0)
 
        cv2.imshow("mask", mask2)
        cv2.imshow("show_img", show_image)
 
        ROI = cv2.bitwise_and(mask2, img)
        cv2.imshow("ROI", ROI)
        cv2.waitKey(0)
 
    if len(pts) > 0:
        # 将pts中的最后一点画出来
        cv2.circle(img2, pts[-1], 3, (0, 0, 255), -1)
 
    if len(pts) > 1:
        # 画线
        for i in range(len(pts) - 1):
            cv2.circle(img2, pts[i], 5, (0, 0, 255), -1)  # x ,y 为鼠标点击地方的坐标
            cv2.line(img=img2, pt1=pts[i], pt2=pts[i + 1], color=(255, 0, 0), thickness=2)
 
    cv2.imshow('image', img2)
 
 
# 创建图像与窗口并将窗口与回调函数绑定
img = cv2.imread("111.jpg")
 
cv2.namedWindow('image')
cv2.setMouseCallback('image', draw_roi)
print("[INFO] 单击左键：选择点，单击右键：删除上一次选择的点，单击中键：确定ROI区域")
print("[INFO] 按‘S'确定选择区域并保存")
print("[INFO] 按 ESC 退出")
 
while True:
    key = cv2.waitKey(1) & 0xFF
    if key == 27:
        break
    if key == ord("s"):
        saved_data = {
            "ROI": pts
        }
        joblib.dump(value=saved_data, filename="config.pkl")
        print("[INFO] ROI坐标已保存到本地.")
        break
cv2.destroyAllWindows()

import cv2 as cv2
 
img = cv2.imread('111.jpg')
# 获取图像尺寸和通道数
h, w, channel = img.shape
# 打印获取的数据
print(h, w, channel)
rows = h
cols = w
roi = img[0:int(rows/2), 0:int(cols/2)]#ROI区域是行  列的一半
cv2.imshow("", roi)
cv2.waitKey()