python目标检测IOU的概念与示例

import cv2
import numpy as np
def CountIOU(RecA, RecB):
    xA = max(RecA[0], RecB[0])
    yA = max(RecA[1], RecB[1])
    xB = min(RecA[2], RecB[2])
    yB = min(RecA[3], RecB[3])
    # 计算交集部分面积
    interArea = max(0, xB - xA + 1) * max(0, yB - yA + 1)
    # 计算预测值和真实值的面积
    RecA_Area = (RecA[2] - RecA[0] + 1) * (RecA[3] - RecA[1] + 1)
    RecB_Area = (RecB[2] - RecB[0] + 1) * (RecB[3] - RecB[1] + 1)
    # 计算IOU
    iou = interArea / float(RecA_Area + RecB_Area - interArea)
    return iou
img = np.zeros((512,512,3), np.uint8)   
img.fill(255)
RecA = [50,50,300,300]
RecB = [60,60,320,320]
cv2.rectangle(img, (RecA[0],RecA[1]), (RecA[2],RecA[3]), (0, 255, 0), 5)
cv2.rectangle(img, (RecB[0],RecB[1]), (RecB[2],RecB[3]), (255, 0, 0), 5)
IOU = CountIOU(RecA,RecB)
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,"IOU = %.2f"%IOU,(130, 190),font,0.8,(0,0,0),2)
cv2.imshow("image",img)
cv2.waiTKEy()
cv2.destroyAllwindows()