Update app.py

app.py

@@ -2,7 +2,7 @@ from PIL import Image
 import torch
 import gradio as gr
 
-model = torch.hub.load(
+model2 = torch.hub.load(
     "bryandlee/animegan2-pytorch:main",
     "generator",
     pretrained=True, # or give URL to a pretrained model
@@ -10,13 +10,19 @@ model = torch.hub.load(
     progress=False, # show progress
 )
 
+model1 = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
+
+
 face2paint = torch.hub.load(
     'bryandlee/animegan2-pytorch:main', 'face2paint', 
     size=512, device="cuda"
 )
 
-def inference(img):
-    out = face2paint(model, img)
+def inference(img, ver):
+    if ver == 'version 2':
+        out = face2paint(model2, img)
+    else:
+        out = face2paint(model1, img)
     return out
       
   
@@ -25,4 +31,5 @@ description = "Gradio demo for AnimeGanv2 Face Portrait v2. To use it, simply up
 article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a> | <a href='https://github.com/Kazuhito00/AnimeGANv2-ONNX-Sample' target='_blank'>Github Repo ONNX</a></p><p style='text-align: center'>samples from repo: <img src='https://user-images.githubusercontent.com/26464535/129888683-98bb6283-7bb8-4d1a-a04a-e795f5858dcf.gif' alt='animation'/> <img src='https://user-images.githubusercontent.com/26464535/137619176-59620b59-4e20-4d98-9559-a424f86b7f24.jpg' alt='animation'/></p>"
 
 examples=[['groot.jpeg'],['bill.png'],['tony.png'],['elon.png'],['IU.png'],['billie.png'],['will.png'],['beyonce.jpeg'],['gongyoo.jpeg']]
-gr.Interface(inference, gr.inputs.Image(type="pil"), gr.outputs.Image(type="pil"),title=title,description=description,article=article,enable_queue=True,examples=examples).launch()
+gr.Interface(inference, [gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 1','version 2'], type="value", default='version 2', label='version')
+], gr.outputs.Image(type="pil"),title=title,description=description,article=article,enable_queue=True,examples=examples).launch()