CVPR/TokenCut

1import os2import gradio as gr3from pathlib import Path4 	5 	6os.system("git clone https://github.com/YangtaoWANG95/TokenCut.git")7os.chdir("TokenCut")8os.system("wget https://raw.githubusercontent.com/YangtaoWANG95/TokenCut/master/examples/VOC07_000064.jpg -O parrot.jpg")9 	10def inference(img):11    os.system("python main_tokencut.py --image_path "+img+" --visualize all --resize 320")12    filename = Path(img).stem13    return "./outputs/TokenCut-vit_small16_k/"+filename+"_TokenCut_attn.jpg","./outputs/TokenCut-vit_small16_k/"+filename+"_TokenCut_pred.jpg"14  15title="TokenCut"16description="Gradio demo for TokenCut: Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut. To use it, simply upload your image or click on one of the examples to load them. We resize the smaller edge of the image to 320 to accelerate inference time. Read more at the links below"17 18article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2202.11539' target='_blank'>Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut</a> | <a href='https://github.com/YangtaoWANG95/TokenCut' target='_blank'>Github Repo</a></p>"19 20examples=[['parrot.jpg']]21gr.Interface(inference,gr.inputs.Image(type="filepath"),[gr.outputs.Image(type="filepath",label="TokenCut_attn"),gr.outputs.Image(type="filepath",label="TokenCut_predication")],title=title,description=description,article=article,examples=examples).launch(enable_queue=True)22 23