app.py

import gradio as gr

from infer import infer_image, infer_video

input_image = gr.Image(type='pil', label='Input Image')
input_model_image = gr.Radio([('x2', 2), ('x4', 4), ('x8', 8)], type="value", value=4, label="Model Upscale/Enhance Type")
submit_image_button = gr.Button('Submit')
output_image = gr.Image(type="filepath", label="Output Image")

tab_img = gr.Interface(
    fn=infer_image,
    inputs=[input_image, input_model_image],
    outputs=output_image,
    title="Real-ESRGAN Pytorch",
    description="Gradio UI for Real-ESRGAN Pytorch version. To use it, simply upload your image, or click one of examples and choose the model. Read more at the links below. Please click submit only once <br>Credits: [Nick088](https://linktr.ee/Nick088), Xinntao, Tencent, Geeve George, ai-forever, daroche <br><p style='text-align: center'><a href='https://arxiv.org/abs/2107.10833'>Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data</a> | <a href='https://github.com/ai-forever/Real-ESRGAN'>Github Repo</a></p>",
    examples=[
        ["test 1900.jpg", "4"]
    ]
)

input_video = gr.Video(label='Input Video')
input_model_video = gr.Radio([('x2', 2), ('x4', 4), ('x8', 8)], type="value", value=2, label="Model Upscale/Enhance Type")
submit_video_button = gr.Button('Submit')
output_video = gr.Video(label='Output Video')

tab_vid = gr.Interface(
    fn=infer_video,
    inputs=[input_video, input_model_video],
    outputs=output_video,
    title="Real-ESRGAN Pytorch",
    description="Gradio UI for Real-ESRGAN Pytorch version. To use it, simply upload your video, or click one of examples and choose the model. Read more at the links below. Please click submit only once <br>Credits: [Nick088](https://linktr.ee/Nick088), Xinntao, Tencent, Geeve George, ai-forever, daroche <br><p style='text-align: center'><a href='https://arxiv.org/abs/2107.10833'>Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data</a> | <a href='https://github.com/ai-forever/Real-ESRGAN'>Github Repo</a></p>",
    examples=[
        ["1900.mp4", "2"]
    ]
)

demo = gr.TabbedInterface([tab_img, tab_vid], ["Image", "Video"])

demo.launch(debug=True, show_error=True)