yolov8 bot_sort代码

以下是一个使用YOLOv4和SORT（Simple Online and Realtime Tracking）算法进行目标检测和跟踪的示例代码，您可以参考：

import cv2
import numpy as np
from sort import *

# 加载YOLOv4模型
net = cv2.dnn.readNet("yolov4.weights", "yolov4.cfg")

# 获取模型输出层的名称
layer_names = net.getLayerNames()
output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]

# 加载类别标签
classes = []
with open("coco.names", "r") as f:
    classes = [line.strip() for line in f.readlines()]

# 初始化跟踪器
tracker = Sort()

# 打开视频文件
video = cv2.VideoCapture("test.mp4")

while True:
    ret, frame = video.read()
    if not ret:
        break
    
    height, width, channels = frame.shape

    # 图像预处理
    blob = cv2.dnn.blobFromImage(frame, 0.00392, (416, 416), (0, 0, 0), True, crop=False)
    
    # 将图像输入到网络中进行目标检测
    net.setInput(blob)
    outs = net.forward(output_layers)
    
    class_ids = []
    confidences = []
    boxes = []
    
    # 解析模型输出
    for out in outs:
        for detection in out:
            scores = detection[5:]
            class_id = np.argmax(scores)
            confidence = scores[class_id]
            
            if confidence > 0.5:
                center_x = int(detection[0] * width)
                center_y = int(detection[1] * height)
                w = int(detection[2] * width)
                h = int(detection[3] * height)
                
                x = int(center_x - w / 2)
                y = int(center_y - h / 2)
                
                boxes.append([x, y, w, h])
                confidences.append(float(confidence))
                class_ids.append(class_id)
    
    # 应用非极大值抑制获取最终的检测结果
    indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
    
    # 更新跟踪器
    detections = []
    for i in range(len(boxes)):
        if i in indexes:
            x, y, w, h = boxes[i]
            label = str(classes[class_ids[i]])
            detections.append([x, y, x+w, y+h])
    
    trackers = tracker.update(np.array(detections))
    
    for d in trackers:
        x1, y1, x2, y2, track_id = d.astype(np.int32)
        cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
        cv2.putText(frame, str(track_id), (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
    
    cv2.imshow("Tracking", frame)
    
    if cv2.waitKey(1) == ord('q'):
        break

video.release()
cv2.destroyAllWindows()

请注意，这只是一个示例代码，您需要根据您的实际环境和需求进行适当的修改和调整。此外，您需要确保已经下载了YOLOv4的权重文件（yolov4.weights）、配置文件（yolov4.cfg）和类别标签文件（coco.names）。