Update

README.md

@@ -4,9 +4,11 @@ emoji: 🌍
 colorFrom: red
 colorTo: indigo
 sdk: gradio
-sdk_version: 3.19.1
+sdk_version: 3.35.2
+python_version: 3.9.16
 app_file: app.py
 pinned: false
+suggested_hardware: t4-small
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

@@ -7,10 +7,7 @@ import numpy as np
 
 from model import Model
 
-DESCRIPTION = '''# Projected GAN
-
-This is an unofficial demo for [https://github.com/autonomousvision/projected_gan](https://github.com/autonomousvision/projected_gan).
-'''
+DESCRIPTION = '# [Projected GAN](https://github.com/autonomousvision/projected_gan)'
 
 
 def get_sample_image_url(name: str) -> str:
@@ -36,33 +33,33 @@ with gr.Blocks(css='style.css') as demo:
         with gr.TabItem('App'):
             with gr.Row():
                 with gr.Column():
-                    model_name = gr.Dropdown(model.MODEL_NAMES,
-                                             value=model.MODEL_NAMES[8],
-                                             label='Model')
-                    seed = gr.Slider(0,
-                                     np.iinfo(np.uint32).max,
+                    model_name = gr.Dropdown(label='Model',
+                                             choices=model.MODEL_NAMES,
+                                             value=model.MODEL_NAMES[8])
+                    seed = gr.Slider(label='Seed',
+                                     minimum=0,
+                                     maximum=np.iinfo(np.uint32).max,
                                      step=1,
-                                     value=0,
-                                     label='Seed')
-                    psi = gr.Slider(0,
-                                    2,
+                                     value=0)
+                    psi = gr.Slider(label='Truncation psi',
+                                    minimum=0,
+                                    maximum=2,
                                     step=0.05,
-                                    value=0.7,
-                                    label='Truncation psi')
+                                    value=0.7)
                     run_button = gr.Button('Run')
                 with gr.Column():
                     result = gr.Image(label='Result', elem_id='result')
 
         with gr.TabItem('Sample Images'):
             with gr.Row():
-                model_name2 = gr.Dropdown(model.MODEL_NAMES,
-                                          value=model.MODEL_NAMES[0],
-                                          label='Model')
+                model_name2 = gr.Dropdown(label='Model',
+                                          choices=model.MODEL_NAMES,
+                                          value=model.MODEL_NAMES[0])
             with gr.Row():
                 text = get_sample_image_markdown(model_name2.value)
                 sample_images = gr.Markdown(text)
 
-    model_name.change(fn=model.set_model, inputs=model_name, outputs=None)
+    model_name.change(fn=model.set_model, inputs=model_name)
     run_button.click(fn=model.set_model_and_generate_image,
                      inputs=[
                          model_name,
@@ -74,4 +71,4 @@ with gr.Blocks(css='style.css') as demo:
                        inputs=model_name2,
                        outputs=sample_images)
 
-demo.queue().launch(show_api=False)
+demo.queue(max_size=10).launch()

model.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import os
 import pathlib
 import pickle
 import sys
@@ -14,8 +13,6 @@ current_dir = pathlib.Path(__file__).parent
 submodule_dir = current_dir / 'projected_gan'
 sys.path.insert(0, submodule_dir.as_posix())
 
-HF_TOKEN = os.getenv('HF_TOKEN')
-
 
 class Model:
 
@@ -39,9 +36,8 @@ class Model:
         self.model = self._load_model(self.model_name)
 
     def _load_model(self, model_name: str) -> nn.Module:
-        path = hf_hub_download('hysts/projected_gan',
-                               f'models/{model_name}.pkl',
-                               use_auth_token=HF_TOKEN)
+        path = hf_hub_download('public-data/projected_gan',
+                               f'models/{model_name}.pkl')
         with open(path, 'rb') as f:
             model = pickle.load(f)['G_ema']
         model.eval()

requirements.txt

@@ -1,5 +1,5 @@
-numpy==1.22.3
-Pillow==9.0.1
-scipy==1.8.0
+numpy==1.23.5
+Pillow==10.0.0
+scipy==1.10.1
 torch==1.10.2
 torchvision==0.11.3