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