Update app.py

app.py

@@ -10,7 +10,6 @@ sys.path.append("projected_gan")
 
 """Generate images using pretrained network pickle."""
 
-import os
 import re
 from typing import List, Optional, Tuple, Union
 
@@ -22,6 +21,8 @@ import torch
 
 import legacy
 
+from huggingface_hub import hf_hub_url
+
 #----------------------------------------------------------------------------
 
 def parse_range(s: Union[str, List]) -> List[int]:
@@ -69,7 +70,9 @@ def make_transform(translate: Tuple[float,float], angle: float):
 #----------------------------------------------------------------------------
 
 device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
-with dnnlib.util.open_url('https://s3.eu-central-1.amazonaws.com/avg-projects/projected_gan/models/pokemon.pkl') as f:
+
+config_file_url = hf_hub_url("autonomousvision/Projected_GAN_Pokemon", filename="pokemon.pkl")
+with dnnlib.util.open_url(config_file_url) as f:
     G = legacy.load_network_pkl(f)['G_ema'].to(device) # type: ignore
     
 def generate_images(seeds):
@@ -121,6 +124,6 @@ description = "Gradio demo for Projected GANs Converge Faster, Pokemon. To use i
 
 article = "<p style='text-align: center'><a href='http://www.cvlibs.net/publications/Sauer2021NEURIPS.pdf' target='_blank'>Projected GANs Converge Faster</a> | <a href='https://github.com/autonomousvision/projected_gan' target='_blank'>Github Repo</p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_projected_gan' alt='visitor badge'></center>"
 
-gr.Interface(inference,gr.inputs.Slider(label="Seed",minimum=0, maximum=5000, step=1, default=0),"pil",title=title,description=description,article=article, examples=[
+gr.Interface(inference,gr.inputs.Slider(label="Seed",minimum=0, maximum=1000, step=1, default=0),"pil",title=title,description=description,article=article, examples=[
     [0],[1],[10],[20],[30],[42],[50],[60],[77],[102]
     ]).launch(enable_queue=True,cache_examples=True)