import torch
import gradio as gr
import pathlib

# TODO：在windows中使用linux中训练好的权重的方式
# temp = pathlib.PosixPath
# pathlib.PosixPath = pathlib.WindowsPath

import os

def modify_file(file_path, old_string, new_string):
    # 读取文件内容
    with open(file_path, 'r') as file:
        file_content = file.read()

    # 替换字符串
    new_content = file_content.replace(old_string, new_string)

    # 写入文件
    with open(file_path, 'w') as file:
        file.write(new_content)

def main():
    # 设置文件路径和需要替换的字符串
    file_path = "/usr/local/lib/python3.10/site-packages/basicsr/data/degradations.py"
    old_string = "from torchvision.transforms.functional_tensor import rgb_to_grayscale"
    new_string = "from torchvision.transforms._functional_tensor import rgb_to_grayscale"

    # 检查文件是否存在
    if os.path.exists(file_path):
        # 进行替换
        modify_file(file_path, old_string, new_string)
        print("替换完成！")
    else:
        print("文件路径不存在！")

if __name__ == "__main__":
    main()


model = torch.hub.load("./yolov5", "custom", path="./yolov5/weights/yolov5x_anchor_ODConv.pt", source="local").to("cpu")
title = "肺结节检测系统"
desc = "这是一个基于Gradio的使用Yolov5实现的肺结节检测系统！"
base_conf, base_iou = 0.25, 0.45


def det_image(img, conf_thres, iou_thres):
    model.conf = conf_thres
    model.iou = iou_thres
    return model(img).render()[0]


# examples中的参数要和inputs中对应
# 获取摄像头拍照检测，修改inputs中的：inputs=[gr.Webcam(),...]就可以了，动态的更新添加属性：live=True
# 如果将launch()更改为launch(share=True)则会将这个代码放在公网进行访问。
gr.Interface(
    inputs=["image", gr.Slider(minimum=0, maximum=1, value=base_conf), gr.Slider(minimum=0, maximum=1, value=base_iou)],
    outputs=["image"],
    fn=det_image,
    title=title,
    description=desc,
    live=True,
    examples=[["./yolov5/data/images/0004.png", base_conf, base_iou],
              ["./yolov5/data/images/0012.png", 0.3, base_iou]]
).launch(share=True)

# 最后要记得将复原修改
# pathlib.PosixPath = temp