| from PIL import Image | |
| import torch | |
| import gradio | |
| Instructuction = "Select a Unique Portrait Image of yourself" | |
| title="I am something of a Painter, Anime-Edition (AnimeGAN-V2)" | |
| description = "Drag/Drop or Upload a cute portrait Image of yourself or anyone you find interesting 😉, then observe how this Generative model\ | |
| is able to Generate a cute Anime-Cartoon version of your Image." | |
| article = """ | |
| - Select an image from the examples provided as demo image, | |
| - Click submit to Generate Image, | |
| - Tips: Quality Images with Great brightness/without pre-existing filters work better (Image Noise). | |
| - Privacy: No user data is collected or saved, | |
| - Credits to akhaliq/AnimeGANv2 for original AnimeGanV2""" | |
| model = torch.hub.load( | |
| "AK391/animegan2-pytorch:main", | |
| "generator", | |
| pretrained=True, | |
| device="cuda", | |
| progress=False | |
| ) | |
| face2paint = torch.hub.load( | |
| 'AK391/animegan2-pytorch:main', 'face2paint', | |
| size=512, device="cuda",side_by_side=False | |
| ) | |
| def inference(img): | |
| return face2paint(model, img) | |
| gradio.Interface(inference, | |
| inputs=gradio.Image(type='pil'), | |
| outputs=gradio.Image(type='pil'), | |
| Instructuction=Instructuction, title=title, description=description, article=article, | |
| examples=['/content/Upload Xty.png', | |
| '/content/Upload Tg.png']).launch() |