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| from PIL import Image | |
| import torch | |
| import gradio as gr | |
| model2 = torch.hub.load( | |
| "AK391/animegan2-pytorch:main", | |
| "generator", | |
| pretrained=True, | |
| device="cpu", | |
| progress=False | |
| ) | |
| model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="celeba_distill", device="cpu") | |
| face2paint = torch.hub.load( | |
| 'AK391/animegan2-pytorch:main', 'face2paint', | |
| size=1024, device="cpu",side_by_side=False | |
| ) | |
| def inference(img): | |
| 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>" | |
| gr.Interface(inference, [gr.inputs.Image(type="pil") | |
| ], gr.outputs.Image(type="pil"),title=title,description=description,article=article,allow_flagging=False,allow_screenshot=False).launch() |