Add files

.gitmodules

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+[submodule "MangaLineExtraction_PyTorch"]
+	path = MangaLineExtraction_PyTorch
+	url = https://github.com/ljsabc/MangaLineExtraction_PyTorch

.pre-commit-config.yaml

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+exclude: ^MangaLineExtraction_PyTorch
+repos:
+- repo: https://github.com/pre-commit/pre-commit-hooks
+  rev: v4.2.0
+  hooks:
+  - id: check-executables-have-shebangs
+  - id: check-json
+  - id: check-merge-conflict
+  - id: check-shebang-scripts-are-executable
+  - id: check-toml
+  - id: check-yaml
+  - id: double-quote-string-fixer
+  - id: end-of-file-fixer
+  - id: mixed-line-ending
+    args: ['--fix=lf']
+  - id: requirements-txt-fixer
+  - id: trailing-whitespace
+- repo: https://github.com/myint/docformatter
+  rev: v1.4
+  hooks:
+  - id: docformatter
+    args: ['--in-place']
+- repo: https://github.com/pycqa/isort
+  rev: 5.10.1
+  hooks:
+    - id: isort
+- repo: https://github.com/pre-commit/mirrors-mypy
+  rev: v0.812
+  hooks:
+    - id: mypy
+      args: ['--ignore-missing-imports']
+- repo: https://github.com/google/yapf
+  rev: v0.32.0
+  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

.style.yapf

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+[style]
+based_on_style = pep8
+blank_line_before_nested_class_or_def = false
+spaces_before_comment = 2
+split_before_logical_operator = true

MangaLineExtraction_PyTorch

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+Subproject commit 738ffab9ca4dd14da14b8c684b25278bc22556f8

README.md

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 ---
-title: MangaLineExtraction PyTorch
+title: MangaLineExtraction_PyTorch
 emoji: 📈
 colorFrom: green
 colorTo: indigo
 sdk: gradio
-sdk_version: 3.0.14
+sdk_version: 3.0.11
 app_file: app.py
 pinned: false
 ---

app.py

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+#!/usr/bin/env python
+
+from __future__ import annotations
+
+import argparse
+
+import gradio as gr
+
+from model import Model
+
+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)
+
+        run_button.click(fn=model.predict, inputs=input_image, outputs=result)
+
+    demo.launch(
+        enable_queue=args.enable_queue,
+        server_port=args.port,
+        share=args.share,
+    )
+
+
+if __name__ == '__main__':
+    main()

model.py

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+from __future__ import annotations
+
+import os
+import pathlib
+import sys
+
+import cv2
+import huggingface_hub
+import numpy as np
+import torch
+import torch.nn as nn
+
+current_dir = pathlib.Path(__file__).parent
+submodule_dir = current_dir / 'MangaLineExtraction_PyTorch'
+sys.path.insert(0, submodule_dir.as_posix())
+
+from model_torch import res_skip
+
+HF_TOKEN = os.environ['HF_TOKEN']
+
+MAX_SIZE = 1000
+
+
+class Model:
+    def __init__(self, device: str | torch.device):
+        self.device = torch.device(device)
+        self.model = self._load_model()
+
+    def _load_model(self) -> nn.Module:
+        ckpt_path = huggingface_hub.hf_hub_download(
+            'hysts/MangaLineExtraction_PyTorch',
+            'erika.pth',
+            use_auth_token=HF_TOKEN)
+        state_dict = torch.load(ckpt_path)
+        model = res_skip()
+        model.load_state_dict(state_dict)
+        model.to(self.device)
+        model.eval()
+        return model
+
+    @torch.inference_mode()
+    def predict(self, image: np.ndarray) -> np.ndarray:
+        gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+
+        if max(gray.shape) > MAX_SIZE:
+            scale = MAX_SIZE / max(gray.shape)
+            gray = cv2.resize(gray, None, fx=scale, fy=scale)
+
+        h, w = gray.shape
+        size = 16
+        new_w = (w + size - 1) // size * size
+        new_h = (h + size - 1) // size * size
+
+        patch = np.ones((1, 1, new_h, new_w), dtype=np.float32)
+        patch[0, 0, :h, :w] = gray
+        tensor = torch.from_numpy(patch).to(self.device)
+        out = self.model(tensor)
+
+        res = out.cpu().numpy()[0, 0, :h, :w]
+        res = np.clip(res, 0, 255).astype(np.uint8)
+        return res

requirements.txt

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+numpy==1.22.4
+opencv-python-headless==4.5.5.64
+torch==1.11.0
+torchvision==0.12.0

style.css

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+h1 {
+  text-align: center;
+}
+div#result {
+  max-width: 600px;
+  max-height: 600px;
+}
+img#visitor-badge {
+  display: block;
+  margin: auto;
+}