Upload with huggingface_hub

DESCRIPTION.md

@@ -0,0 +1 @@
+Recreate the viral AnimeGAN image transformation demo.

README.md

@@ -1,7 +1,7 @@
 
 ---
 title: animeganv2 
-emoji: 🤗
+emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio

app.py

@@ -1,11 +1,7 @@
-# URL: https://huggingface.co/spaces/gradio/animeganv2
-# DESCRIPTION: Recreate the viral AnimeGAN image transformation demo.
-# imports
 import gradio as gr
 from PIL import Image
 import torch
 
-# load the models
 model2 = torch.hub.load(
     "AK391/animegan2-pytorch:main",
     "generator",
@@ -18,7 +14,6 @@ face2paint = torch.hub.load(
     size=512,side_by_side=False
 )
 
-# define the core function
 def inference(img, ver):
     if ver == 'version 2 (🔺 robustness,🔻 stylization)':
         out = face2paint(model2, img)
@@ -26,13 +21,11 @@ def inference(img, ver):
         out = face2paint(model1, img)
     return out
 
-# define the title, description and examples
 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>"
 examples=[['groot.jpeg','version 2 (🔺 robustness,🔻 stylization)'],['gongyoo.jpeg','version 1 (🔺 stylization, 🔻 robustness)']]
 
-# define the interface
 demo = 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')], 
@@ -42,5 +35,4 @@ demo = gr.Interface(
     article=article,
     examples=examples)
 
-# launch    
 demo.launch()