如何在python3.7中使用yolov2进行语义分割？

pip install opencv-python
pip install numpy
pip install darknetpy

import cv2
import numpy as np
import darknetpy

# 加载Yolov2模型和权重
net = darknetpy.load_net("path/to/yolov2.cfg", "path/to/yolov2.weights", 0)
meta = darknetpy.load_meta("path/to/coco.data")

# 读取图像
image = cv2.imread("path/to/image.jpg")

# 图像预处理
resized_image = cv2.resize(image, (darknetpy.network_width(net), darknetpy.network_height(net)))
resized_image = cv2.cvtColor(resized_image, cv2.COLOR_BGR2RGB)
resized_image = np.transpose(resized_image, (2, 0, 1))
resized_image = np.ascontiguousarray(resized_image, dtype=np.float32)
resized_image /= 255.0

# 进行推理
results = darknetpy.detect_image(net, meta, resized_image)

# 处理检测结果
for result in results:
    x, y, w, h = result[2]
    label = result[0].decode()
    confidence = result[1]
    
    # 绘制边界框和标签
    cv2.rectangle(image, (int(x-w/2), int(y-h/2)), (int(x+w/2), int(y+h/2)), (0, 255, 0), 2)
    cv2.putText(image, label, (int(x-w/2), int(y-h/2-10)), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)

# 显示结果图像
cv2.imshow("Result", image)
cv2.waitKey(0)
cv2.destroyAllWindows()