app.py

import gradio as gr
import cv2
import os

css = """
#img-display-container {
    max-height: 100vh;
    }
#img-display-input {
    max-height: 80vh;
    }
#img-display-output {
    max-height: 80vh;
    }
"""


title = "# Depth Anything Video Demo"
description = """Depth Anything on full video files."""

with gr.Blocks(css=css) as demo:
    gr.Markdown(title)
    gr.Markdown(description)
    gr.Markdown("### Video Depth Prediction demo")

    with gr.Row():
        input_video = gr.Video(label="Input Video")
        model_type = gr.Dropdown(["vits", "vitb", "vitl"], type="value", label='Model Type')
    submit = gr.Button("Submit")
    processed_video = gr.Video(label="Processed Video")

    def on_submit(uploaded_video,model_type):
                
        # Process the video and get the path of the output video
        #output_video_path = make_video(uploaded_video,encoder=model_type)
        pass
        #return output_video_path

    submit.click(on_submit, inputs=[input_video, model_type], outputs=processed_video)

    #example_files = os.listdir('assets/examples_video')
    #example_files.sort()
    #example_files = [os.path.join('assets/examples_video', filename) for filename in example_files]
    #examples = gr.Examples(examples=example_files, inputs=[input_video], outputs=processed_video, fn=on_submit, cache_examples=True)
    

if __name__ == '__main__':
    demo.queue().launch()