Update app.py

app.py

@@ -1,42 +1,26 @@
-from PIL import Image
 import torch
 import gradio as gr
 
-model2 = torch.hub.load(
-    "AK391/animegan2-pytorch:main",
-    "generator",
-    pretrained=True,
-    device="cuda",
-    progress=False
-)
-
-model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1",  device="cuda")
-face2paint = torch.hub.load(
-    'AK391/animegan2-pytorch:main', 'face2paint', 
-    size=512, device="cuda",side_by_side=False
-)
+model2 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained=True, device="cuda", progress=False)
+model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1", device="cuda")
+face2paint = torch.hub.load('AK391/animegan2-pytorch:main', 'face2paint', size=512, device="cuda", side_by_side=False)
 
 def inference(img, ver):
-    if ver == 'version 2 (🔺 robustness,🔻 stylization)':
-        out = face2paint(model2, img)
-    else:
-        out = face2paint(model1, img)
-    return out
-  
+    model = model2 if ver == 'version 2 (🔺 robustness,🔻 stylization)' else model1
+    return face2paint(model, img)
+
 title = "AnimeGANv2"
-description = "Gradio Demo for AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below."
-article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
+description = "Gradio Demo for AnimeGanv2 Face Portrait. Upload your image and select the version (🔺 robustness,🔻 stylization) to generate an anime-style portrait."
+article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p>"
 
 gr.Interface(
     fn=inference,
     inputs=[
         gr.inputs.Image(type="pil"),
-        gr.inputs.Radio(
-            ['version 1 (🔺 stylization, 🔻 robustness)', 'version 2 (🔺 robustness,🔻 stylization)'],
-            type="value",
-            default='version 2 (🔺 robustness,🔻 stylization)',
-            label='version'
-        )
+        gr.inputs.Radio(['version 1 (🔺 stylization, 🔻 robustness)', 'version 2 (🔺 robustness,🔻 stylization)'],
+                        type="value",
+                        default='version 2 (🔺 robustness,🔻 stylization)',
+                        label='version')
     ],
     outputs=gr.outputs.Image(type="pil"),
     title=title,