import os import cv2 os.system("hub install UGATIT_100w==1.0.0") import gradio as gr import paddlehub as hub model = hub.Module(name='UGATIT_100w', use_gpu=False) def inference(image): result = model.style_transfer(images=[cv2.imread(image.name)]) return result title = "UGATIT-selfie2anime" description = "Gradio demo for DeOldify. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below." article = "
" examples=[['lunch.jpeg']] iface = gr.Interface(inference, inputs=gr.inputs.Image(type="file"), outputs=gr.outputs.Image(type="numpy"),examples=examples,enable_queue=True,title=title,article=article,description=description) iface.launch()