Create app.py

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+import torch
+
+model2 = torch.hub.load(
+    "AK391/animegan2-pytorch:main",
+    "generator",
+    pretrained=True,
+    progress=False
+)
+model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
+face2paint = torch.hub.load(
+    'AK391/animegan2-pytorch:main', 'face2paint',
+    size=512,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
+
+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)']]
+
+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')],
+    outputs=gr.outputs.Image(type="pil"),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples)
+
+demo.launch()