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 (๐Ÿ”บ robustness,๐Ÿ”ป stylization)': out = face2paint(model2, img) else: out = face2paint(model1, img) return out title = "ๅŠจๆผซ้ฃŽๆ ผ่ฟ็งป" examples=[['groot.jpeg','version 2 (๐Ÿ”บ robustness,๐Ÿ”ป stylization)'],['gongyoo.jpeg','version 1 (๐Ÿ”บ stylization, ๐Ÿ”ป robustness)']] demo = gr.Interface( fn=inference, inputs=[gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 1 (๐Ÿ”บ stylization, ๐Ÿ”ป robustness)','version 2 (๐Ÿ”บ robustness,๐Ÿ”ป stylization)'], type="value", default='version 2 (๐Ÿ”บ robustness,๐Ÿ”ป stylization)', label='version')], outputs=gr.outputs.Image(type="pil"), title=title, examples=examples) demo.launch(server_name = "0.0.0.0", server_port = 7022)