Update

.pre-commit-config.yaml

@@ -21,11 +21,11 @@ repos:
   - id: docformatter
     args: ['--in-place']
 - repo: https://github.com/pycqa/isort
-  rev: 5.10.1
+  rev: 5.12.0
   hooks:
     - id: isort
 - repo: https://github.com/pre-commit/mirrors-mypy
-  rev: v0.812
+  rev: v0.991
   hooks:
     - id: mypy
       args: ['--ignore-missing-imports']
@@ -34,13 +34,3 @@ repos:
   hooks:
   - id: yapf
     args: ['--parallel', '--in-place']
-- repo: https://github.com/kynan/nbstripout
-  rev: 0.5.0
-  hooks:
-    - id: nbstripout
-      args: ['--extra-keys', 'metadata.interpreter metadata.kernelspec cell.metadata.pycharm']
-- repo: https://github.com/nbQA-dev/nbQA
-  rev: 1.3.1
-  hooks:
-    - id: nbqa-isort
-    - id: nbqa-yapf

README.md

@@ -4,7 +4,7 @@ emoji: 📈
 colorFrom: green
 colorTo: indigo
 sdk: gradio
-sdk_version: 3.0.11
+sdk_version: 3.19.1
 app_file: app.py
 pinned: false
 ---

app.py

@@ -2,8 +2,6 @@
 
 from __future__ import annotations
 
-import argparse
-
 import gradio as gr
 
 from model import Model
@@ -12,48 +10,19 @@ DESCRIPTION = '''# MangaLineExtraction_PyTorch
 
 This is an unofficial demo for [https://github.com/ljsabc/MangaLineExtraction_PyTorch](https://github.com/ljsabc/MangaLineExtraction_PyTorch).
 '''
-FOOTER = '<img id="visitor-badge" alt="visitor badge" src="https://visitor-badge.glitch.me/badge?page_id=hysts.mangalineextraction_pytorch" />'
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--device', type=str, default='cpu')
-    parser.add_argument('--theme', type=str)
-    parser.add_argument('--share', action='store_true')
-    parser.add_argument('--port', type=int)
-    parser.add_argument('--disable-queue',
-                        dest='enable_queue',
-                        action='store_false')
-    return parser.parse_args()
-
-
-def main():
-    args = parse_args()
-    model = Model(device=args.device)
-
-    with gr.Blocks(theme=args.theme, css='style.css') as demo:
-        gr.Markdown(DESCRIPTION)
-
-        with gr.Row():
-            with gr.Column():
-                with gr.Group():
-                    input_image = gr.Image(label='Input', type='numpy')
-                    run_button = gr.Button(value='Run')
-            with gr.Column():
-                result = gr.Image(label='Result',
-                                  type='numpy',
-                                  elem_id='result')
 
-        gr.Markdown(FOOTER)
+model = Model()
 
-        run_button.click(fn=model.predict, inputs=input_image, outputs=result)
+with gr.Blocks(css='style.css') as demo:
+    gr.Markdown(DESCRIPTION)
 
-    demo.launch(
-        enable_queue=args.enable_queue,
-        server_port=args.port,
-        share=args.share,
-    )
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(label='Input', type='numpy')
+            run_button = gr.Button(value='Run')
+        with gr.Column():
+            result = gr.Image(label='Result', type='numpy', elem_id='result')
 
+    run_button.click(fn=model.predict, inputs=input_image, outputs=result)
 
-if __name__ == '__main__':
-    main()
+demo.queue().launch(show_api=False)

model.py

@@ -16,14 +16,15 @@ sys.path.insert(0, submodule_dir.as_posix())
 
 from model_torch import res_skip
 
-HF_TOKEN = os.environ['HF_TOKEN']
+HF_TOKEN = os.getenv('HF_TOKEN')
 
 MAX_SIZE = 1000
 
 
 class Model:
-    def __init__(self, device: str | torch.device):
-        self.device = torch.device(device)
+    def __init__(self):
+        self.device = torch.device(
+            'cuda:0' if torch.cuda.is_available() else 'cpu')
         self.model = self._load_model()
 
     def _load_model(self) -> nn.Module: