一、使用yolov10模型检测视频中出现的行人，并保存为图片，detect_person.py代码如下：
from ultralytics import YOLOv10
import glob
import os
import cv2
import argparsedef detect_person(videoPath, savePath):if not os.path.exists(savePath):os.mkdir(savePath)# YOLOV10模型路径modelpath = r'q:\yolov10-main\weights\yolov10m.pt'print("------------------",videoPath,savePath)model = YOLOv10(modelpath)timeF = 0image_count = 0# filenames = glob.glob(os.path.join(videoPath, '*.avi'))# 遍历视频文件夹for root, dirs, files in os.walk(videoPath):print("======",root)print("++++++",dirs)print("------",files,len(files))# 遍历视频文件for filename in files:# if(not filename.endswith(".avi")):# continueif(filename.split('.')[-1] not in ['avi','mp4']):continueimg = 1videofile = os.path.join(root, filename)video = cv2.VideoCapture(videofile)frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT))# 遍历视频每一帧for _ in range(frames):ret, frame = video.read()timeF += 1if ret:results = model.predict(frame)[0]personcount = 0for box in results.boxes:if box.cls == 0 and box.conf > 0.5:personcount += 1# 图片中出现大于2人，且间隔15帧，保存图片if personcount >= 2 and timeF > 15 :cv2.imwrite(os.path.join(savePath, filename.split('\\')[-1][:-4] + '_' + str(img) + '.jpg'),frame)if image_count % 100 == 0:print("image_count : ",image_count)timeF = 0img += 1# 释放资源video.release()# 删除视频源文件，不想删除可以注释掉os.remove(videofile)if __name__ == '__main__':parse = argparse.ArgumentParser(description='使用yolov10模型检测视频中出现的行人，并保存为图片')parse.add_argument('--videoDir',required=True,help='视频文件夹')parse.add_argument('--imageDir',required=True,help='保存图片文件夹')args = parse.parse_args()detect_person(args.videoDir, args.imageDir)
二、在终端执行以上代码的命令
python.exe detect_person.py --videoDir Q:\DATAS\adas-data\video-person\20250708 --imageDir Q:\DATAS\adas-data\video-person\images-20250718
