import os import gradio as gr os.system("gdown https://drive.google.com/uc?id=12ElLliRlgGZqPOhUcqJtNVsa7rmzSI5L") os.system("gdown https://drive.google.com/uc?id=1-79oBWGFQXrKYw9oxX7t468Zrp87NoWn") def inference(content, style): os.system("""python style_transfer_folder.py --size 1024 --ckpt ./blendgan.pt --psp_encoder_ckpt ./psp_encoder.pt --style_img_path """+style.name+""" --input_img_path """+content.name) return "out.jpg" title = "AnimeGANv2" description = "Gradio Demo for AnimeGanv2 Face Portrait v2. 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 = "

Github Repo Pytorch | Github Repo ONNX

samples from repo: animation animation

" examples=[['groot.jpeg','version 2 (🔺 robustness,🔻 stylization)'],['bill.png','version 1 (🔺 stylization, 🔻 robustness)'],['tony.png','version 1 (🔺 stylization, 🔻 robustness)'],['elon.png','version 2 (🔺 robustness,🔻 stylization)'],['IU.png','version 1 (🔺 stylization, 🔻 robustness)'],['billie.png','version 2 (🔺 robustness,🔻 stylization)'],['will.png','version 2 (🔺 robustness,🔻 stylization)'],['beyonce.jpeg','version 1 (🔺 stylization, 🔻 robustness)'],['gongyoo.jpeg','version 1 (🔺 stylization, 🔻 robustness)']] gr.Interface(inference, [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') ], gr.outputs.Image(type="pil"),title=title,description=description,article=article,enable_queue=True,examples=examples,allow_flagging=False).launch()