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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 |