opencv行人检测图片视频代码

以下是基于OpenCV的行人检测代码：

import cv2

# 加载分类器
pedestrian_cascade = cv2.CascadeClassifier('haarcascade_fullbody.xml')

# 图片行人检测
img = cv2.imread('image.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
pedestrians = pedestrian_cascade.detectMultiScale(gray, 1.1, 4)
for (x, y, w, h) in pedestrians:
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow('Pedestrian Detection', img)
cv2.waitKey()

# 视频行人检测
cap = cv2.VideoCapture('video.mp4')
while True:
    ret, frame = cap.read()
    if not ret:
        break
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    pedestrians = pedestrian_cascade.detectMultiScale(gray, 1.1, 4)
    for (x, y, w, h) in pedestrians:
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
    cv2.imshow('Pedestrian Detection', frame)
    if cv2.waitKey(1) == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

需要注意的是，代码中使用了OpenCV自带的Haar分类器进行行人检测。同时，也可以使用更加先进的深度学习模型进行行人检测，如YOLOv5、SSD等。