app.py

import gradio as gr
import torch
import uvd
import decord


def proc_video(video, preprocessor_name):
    frame_original_res = decord.VideoReader(video)[:].asnumpy()
    indices = uvd.get_uvd_subgoals(
        video, preprocessor_name.lower().replace("-", ""),
        device="cuda" if torch.cuda.is_available() else "cpu",
        return_indices=True,
    )
    subgoals = frame_original_res[indices]
    return [(img, f"No. {i+1} subgoal") for i, img in enumerate(subgoals)]


with gr.Blocks() as demo:
    with gr.Row():
        input_video = gr.Video(height=224, scale=3)
        preprocessor_name = gr.Dropdown(
            ["VIP", "R3M", "LIV", "CLIP", "DINO-v2", "VC-1", "ResNet"],
            label="Preprocessor",
            value="VIP",
            scale=1,
        )
        output = gr.Gallery(label="UVD SubGoals", height=224, preview=True, scale=4)
    with gr.Row():
        submit = gr.Button("Submit")
        clr = gr.ClearButton(components=[input_video, output])
    submit.click(proc_video, inputs=[input_video, preprocessor_name], outputs=[output])


demo.queue().launch(share=True, show_error=True)