deepsort代码python

DeepSORT是一个目标跟踪算法，使用深度学习进行目标检测，并使用卡尔曼滤波器进行目标跟踪。以下是基于Python的DeepSORT代码示例：

1. 安装相关库

!pip install opencv-python==4.4.0.44
!pip install tensorflow==2.3.0
!pip install keras==2.4.3
!pip install filterpy==1.4.5
!pip install scipy==1.5.2
!pip install numpy==1.18.5
!pip install pillow==7.2.0

2. 导入必要的库

import cv2
import numpy as np
from deep_sort import preprocessing
from deep_sort import nn_matching
from deep_sort.detection import Detection
from deep_sort.tracker import Tracker
from tools import generate_detections as gdet

3. 初始化DeepSORT跟踪器

model_filename = 'model_data/mars-small128.pb'
encoder = gdet.create_box_encoder(model_filename, batch_size=1)
metric = nn_matching.NearestNeighborDistanceMetric("cosine", 0.2, None)
tracker = Tracker(metric)

4. 处理视频帧进行目标检测和跟踪

video_path = 'path/to/video.mp4'
video_capture = cv2.VideoCapture(video_path)

while True:
    ret, frame = video_capture.read()
    
    if ret:
        # 目标检测
        detections = []
        # 使用YOLOv3进行目标检测
        # ...

        # 特征编码
        features = encoder(frame, [d.to_tlbr() for d in detections])
        detections = [Detection(d.to_tlwh(), 1.0, f) for f, d in zip(features, detections)]

        # 目标跟踪
        tracker.predict()
        tracker.update(detections)

        # 绘制目标框和ID
        # ...
    
    else:
        break

video_capture.release()
cv2.destroyAllWindows()

需要注意的是，DeepSORT算法中使用了一个深度学习模型进行目标特征提取，需要先下载模型文件并进行加载。同时还需要实现目标检测部分，可以使用YOLOv3等目标检测算法进行实现。