ubuntu yolov5 deepsort多目标追踪

### 安装依赖库 为了在Ubuntu上使用YOLOv5和DeepSort实现多目标跟踪，需安装必要的Python包和其他依赖项。建议创建虚拟环境来管理项目所需的软件包。 ```bash sudo apt-get update && sudo apt-get install -y python3-pip ffmpeg libsm6 libxext6 protobuf-compiler pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu pip3 install opencv-python-headless numpy matplotlib cython filterpy scipy lap ``` ### 获取源码并配置模型 下载官方仓库中的YOLOv5和DeepSort代码，并按照说明编译所需组件[^1]。 ```bash git clone https://github.com/ultralytics/yolov5.git cd yolov5 pip3 install -r requirements.txt cd .. git clone https://github.com/nwojke/deep_sort_pytorch.git cd deep_sort_pytorch pip3 install -r requirements.txt ``` ### 准备权重文件 获取预训练好的检测器（YOLOv5）以及特征提取网络（DNN用于Re-ID）。可以从相应项目的发布页面找到这些资源链接。 对于YOLOv5： ```bash wget https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5s.pt ``` 对于DeepSORT: ```bash mkdir checkpoints cd checkpoints/ gdown "https://drive.google.com/uc?id=1pdLWfFhIzUoVw8pHnJcYCybPQXZqOaK-" -O osnet_x0_25_msmt17.pth ``` ### 修改配置参数 编辑`deep_sort_pytorch/configs/deep_sort.yaml`设置合适的阈值以及其他超参以适应具体应用场景需求。 ```yaml MIN_CONFIDENCE: 0.4 # 物体置信度下限 MAX_COSINE_DISTANCE: 0.5 # Re-ID相似性距离上限 NN_BUDGET: 100 # 跟踪队列长度限制 ``` ### 运行测试视频或多摄像头实时流处理 通过命令行调用脚本执行对象追踪任务，支持本地视频文件输入或RTSP直播源连接。 ```python from pathlib import Path import cv2 from yolov5.models.experimental import attempt_load from yolov5.utils.general import non_max_suppression, scale_coords from deep_sort_pytorch.deep_sort import DeepSort def main(): weights_path = 'path/to/yolov5s.pt' source_video = 'test.mp4' # 或者 RTSP URL model = attempt_load(weights_path, map_location='cpu') deepsort_tracker = DeepSort('osnet_x0_25', max_dist=0.2) cap = cv2.VideoCapture(source_video) while True: ret, frame = cap.read() if not ret: break results = detect_objects(model, frame) outputs = deepsort_tracker.update(results, frame.shape[:2]) draw_tracks(frame, outputs) if __name__ == '__main__': main() ```