Add files

.gitmodules

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+[submodule "Anime2Sketch"]
+	path = Anime2Sketch
+	url = https://github.com/Mukosame/Anime2Sketch

Anime2Sketch

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+Subproject commit 46342c2c7c19a15f907f2b5005721b13636b659a

app.py

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+#!/usr/bin/env python
+
+from __future__ import annotations
+
+import argparse
+import functools
+import os
+import sys
+
+import gradio as gr
+import huggingface_hub
+import PIL.Image
+import torch
+import torch.nn as nn
+
+sys.path.insert(0, 'Anime2Sketch')
+
+from data import read_img_path, tensor_to_img
+from model import UnetGenerator
+
+TITLE = 'Mukosame/Anime2Sketch'
+DESCRIPTION = 'This is a demo for https://github.com/Mukosame/Anime2Sketch.'
+ARTICLE = None
+
+TOKEN = os.environ['TOKEN']
+
+
+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('--live', action='store_true')
+    parser.add_argument('--share', action='store_true')
+    parser.add_argument('--port', type=int)
+    parser.add_argument('--disable-queue',
+                        dest='enable_queue',
+                        action='store_false')
+    parser.add_argument('--allow-flagging', type=str, default='never')
+    parser.add_argument('--allow-screenshot', action='store_true')
+    return parser.parse_args()
+
+
+def load_model(device: torch.device) -> nn.Module:
+    norm_layer = functools.partial(nn.InstanceNorm2d,
+                                   affine=False,
+                                   track_running_stats=False)
+    model = UnetGenerator(3,
+                          1,
+                          8,
+                          64,
+                          norm_layer=norm_layer,
+                          use_dropout=False)
+
+    path = huggingface_hub.hf_hub_download('hysts/Anime2Sketch',
+                                           'netG.pth',
+                                           use_auth_token=TOKEN)
+    ckpt = torch.load(path)
+    for key in list(ckpt.keys()):
+        if 'module.' in key:
+            ckpt[key.replace('module.', '')] = ckpt[key]
+            del ckpt[key]
+    model.load_state_dict(ckpt)
+    model.to(device)
+    model.eval()
+    return model
+
+
+@torch.inference_mode()
+def run(image_file,
+        model: nn.Module,
+        device: torch.device,
+        load_size: int = 512) -> PIL.Image.Image:
+    tensor, orig_size = read_img_path(image_file.name, load_size)
+    tensor = tensor.to(device)
+    out = model(tensor)
+    res = tensor_to_img(out)
+    res = PIL.Image.fromarray(res)
+    res = res.resize(orig_size, PIL.Image.Resampling.BICUBIC)
+    return res
+
+
+def main():
+    gr.close_all()
+
+    args = parse_args()
+    device = torch.device(args.device)
+
+    model = load_model(device)
+
+    func = functools.partial(run, model=model, device=device)
+    func = functools.update_wrapper(func, run)
+
+    examples = [['Anime2Sketch/test_samples/madoka.jpg']]
+
+    gr.Interface(
+        func,
+        gr.inputs.Image(type='file', label='Input'),
+        gr.outputs.Image(type='pil', label='Output'),
+        examples=examples,
+        title=TITLE,
+        description=DESCRIPTION,
+        article=ARTICLE,
+        theme=args.theme,
+        allow_screenshot=args.allow_screenshot,
+        allow_flagging=args.allow_flagging,
+        live=args.live,
+    ).launch(
+        enable_queue=args.enable_queue,
+        server_port=args.port,
+        share=args.share,
+    )
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

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+numpy==1.22.3
+Pillow==9.1.0
+torch==1.11.0
+torchvision==0.12.0