init

app.py

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+#!/usr/bin/env python
+
+from __future__ import annotations
+import argparse
+import functools
+import os
+import pathlib
+import sys
+from typing import Callable
+
+
+import gradio as gr
+import huggingface_hub
+import numpy as np
+import PIL.Image
+
+from io import BytesIO
+from fastai.vision import *
+from fastai.vision import load_learner
+
+ORIGINAL_REPO_URL = 'https://github.com/vijishmadhavan/ArtLine'
+TITLE = 'vijishmadhavan/ArtLine'
+DESCRIPTION = f"""This is a demo for {ORIGINAL_REPO_URL}.
+
+"""
+ARTICLE = """
+
+"""
+
+
+MODEL_REPO = 'hylee/artline_model'
+
+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():
+    dir = 'model'
+    name = 'ArtLine_650.pkl'
+    model_path = huggingface_hub.hf_hub_download(MODEL_REPO,
+                                                      name,
+                                                      cache_dir=dir,
+                                                      force_filename=name)
+    return model_path
+
+
+
+def run(
+    image,
+    learn,
+) -> tuple[PIL.Image.Image]:
+
+    img = PIL.Image.open(image.name)
+    img_t = T.ToTensor()(img)
+    img_fast = PIL.Image(img_t)
+
+    p, img_hr, b = learn.predict(img_fast)
+    r = PIL.Image(img_hr)
+    
+    return r
+
+learn = None
+def main():
+    gr.close_all()
+
+    args = parse_args()
+
+    model_path = load_model()
+
+    # singleton start
+    def load_pkl(self) -> Any:
+        global learn
+        path = Path("model")
+        learn = load_learner(path, 'ArtLine_650.pkl')
+
+    PklLoader = type('PklLoader', (), {"load_pkl": load_pkl})
+    pl = PklLoader()
+    pl.load_pkl()
+
+
+    func = functools.partial(run, learn=learn)
+    func = functools.update_wrapper(func, run)
+
+    
+    gr.Interface(
+        func,
+        [
+            gr.inputs.Image(type='file', label='Input Image'),
+        ],
+        [
+            gr.outputs.Image(
+                type='pil',
+                label='Result'),
+        ],
+        #examples=examples,
+        theme=args.theme,
+        title=TITLE,
+        description=DESCRIPTION,
+        article=ARTICLE,
+        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()

packages.txt

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+
+

requirements.txt

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+opencv-python-headless==4.5.5.62
+Pillow==9.0.1
+scipy==1.7.3
+fastai==1.0.61
+numpy==1.17.2
+pandas==1.1.2
+torch==1.6.0
+torchvision===0.7.0