我有一个脚本可以检测行人所在的危险区域，但我需要检测行人是否在危险区域内。
我的危险区域是一个多边形，而检测到的人是用一个矩形框表示的！
检测一个矩形是否在多边形内部的最佳方法是什么？
脚本示例：
# -*- coding: utf-8 -*-import numpy as npimport cv2import timeimport mathclass DetectorAPI: cap = cv2.VideoCapture("VideoCone.MOV") while True: r, img = cap.read() #定义视频中模型将要作用的区域 #img = img[10:1280, 230:1280] img = cv2.resize(img, (800, 600)) overlay = img.copy() #帧检测红区 vermelho_inicio = np.array([0, 9, 178]) vermelho_fim = np.array([255, 40, 255]) #颜色模型的检测掩膜 mask = cv2.inRange(img, vermelho_inicio, vermelho_fim) #点和多边形的绘制（激光检测到的对象） np_points = np.transpose(np.nonzero(mask)) points = np.fliplr(np_points) # opencv使用翻转的x,y坐标 approx = cv2.convexHull(points) DangerArea = cv2.fillPoly(img, [approx], (0,0,255)) #透明度 cv2.addWeighted(overlay,0.3,img,1-0.65,0,img); edges = cv2.Canny(mask,30,120) #在激光（锥形）上绘制线条 lines = cv2.HoughLinesP(edges, 5, np.pi/180, 30, maxLineGap=50) a,b,c = lines.shape if lines is not None: for line in lines: x1, y1, x2, y2 = line[0] cv2.line(img, (x1, y1), (x2, y2), (0, 255, 0), 1) #捕获帧的信息 height, width, channels = img.shape #分割以捕获图像的中心 upper_left = (int(width / 2), int(height / 4)) bottom_right = (int(width * 2 / 2), int(height * 3 / 4)) #在视频中心绘制矩形 cv2.rectangle(img,(100,150), (200,250),(0,152,112),1); cv2.rectangle(img,(500,150), (420,250),(0,100,255),1); #在危险区域写入文本 #cv2.putText(DangerArea,'Danger Area',(int(width / 4),int(height * 3 / 4)), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(255,255,255),2,cv2.LINE_AA) #cv2.addWeighted(overlay,0.3,img,1-0.4,0,img); #在控制台打印图像的中心 print('Upper_Left: '+str(upper_left)+' bottom_right: '+str(bottom_right)); #显示视频 cv2.imshow("edges", edges) cv2.imshow("Detectar Pessoas", img) key = cv2.waitKey(1) if key & 0xFF == ord('q'): break回答：
p0 = (10,10)p1 = (400,400)is_p0_ok = cv2.pointPolygonTest(approx, p0, False) < 0is_p1_ok = cv2.pointPolygonTest(approx, p1, False) < 0print(is_p0_ok)>>> Trueprint(is_p1_ok)>>> False根据您的实现，您可能需要使用cv2.pointPolygonTest检查矩形的中心，或者检查它的所有角点。
编辑
如何将矩形框的坐标传递给变量p0和p1？因为矩形框有四个值cv2.rectangle(img,(box[1],box[0]),(box[3],box[2]),(255,0,0),2)，我需要检查整个矩形是否在多边形内部
p0 = (box[1],box[0])p1 = (box[1], box[2])p2 = (box[3],box[2])p3 = (box[3], box[0])rect = [p0,p1,p2,p3]rect_pts_inside = [cv2.pointPolygonTest(approx, pt, False) < 0 for pt in rect]whole_rect_inside_polygon = all(rect_pts_inside)part_of_rect_inside_polygon = any(rect_pts_inside)