请用python代码写一个yolov5的数据集标注工具给我

首先，你需要准备好你的数据集图片和标签，标签通常是一个包含每个目标框的类别、位置和大小信息的文本文件。接下来，你可以使用如下 Python 代码来创建一个 YOLOv5 数据集标注工具：

import cv2
import numpy as np

class YOLOv5AnnotationTool:
    def __init__(self, image_folder, labels):
        self.image_folder = image_folder
        self.labels = labels
        self.current_image_index = 0
        self.current_image_path = self.image_folder[self.current_image_index]
        self.current_image = cv2.imread(self.current_image_path)
        self.current_annotations = []
        self.window_name = "YOLOv5 Annotation Tool"
        cv2.namedWindow(self.window_name)
        cv2.setMouseCallback(self.window_name, self.draw_bounding_box)

    def draw_bounding_box(self, event, x, y, flags, param):
        if event == cv2.EVENT_LBUTTONDOWN:
            # Start drawing the bounding box
            self.start_point = (x, y)
        elif event == cv2.EVENT_LBUTTONUP:
            # End drawing the bounding box
            end_point = (x, y)
            label = self.select_label()
            self.current_annotations.append((self.start_point, end_point, label))
            self.start_point = None

    def select_label(self):
        # Show a list of labels and let the user select one
        print("Select a label:")
        for i, label in enumerate(self.labels):
            print(f"{i}: {label}")
        selected_label = input()
        return self.labels[int(selected_label)]

    def run(self):
        while True:
            # Show the current image and draw the bounding boxes
            image_with_boxes = self.current_image.copy()
            for start_point, end_point, label in self.current_annotations:
                cv2.rectangle(image_with_boxes, start_point, end_point, (0, 255, 0), 2)
            cv2.imshow(self.window_name, image_with_boxes)

            # Wait for the user to press a key
            key = cv2.waitKey(1)

            # Save the current annotations and move to the next image if the user pressed "n"
            if key == ord("n"):
                self.save_current_annotations()
                self.move_