import gradio as gr
import os

# Load assets
def load_assets():
    assets_dir = os.path.join(os.path.dirname(__file__), 'assets')
    with open(os.path.join(assets_dir, 'style.css'), 'r') as f:
        css = f.read()
    with open(os.path.join(assets_dir, 'fullscreen.js'), 'r') as f:
        fullscreen_js = f.read()
    return css, fullscreen_js

css, fullscreen_js = load_assets()

# Dummy function for testing
def dummy_process(files, niter, as_pc, refinement, clean):
    if files is None:
        return None, []
    return None, [("Dummy output", "Processing would happen here")]

with gr.Blocks(
    title="Multi-View 3D Reconstruction (MV3DR)", 
    css=css, 
    theme=gr.themes.Base()
) as demo:
    gr.Markdown("# Multi-View 3D Reconstruction (MV3DR)")
    gr.Markdown("**Test UI - No Model Loaded**")

    with gr.Row():
        with gr.Column(scale=1):
            input_files = gr.File(
                file_count="multiple",
                label="Images",
                type="filepath"
            )
            run_btn = gr.Button("Run Inference")
            with gr.Accordion("Settings", open=False):
                n_iterations = gr.Slider(minimum=100, maximum=1000, value=300, step=10, label="Alignment Iterations")
                render_mode = gr.Checkbox(value=True, label="Render as Point Cloud")
                post_proc = gr.Checkbox(value=True, label="Filter Background Points")
                clean_depth = gr.Checkbox(value=True, label="Clean Point Cloud")

        with gr.Column(scale=2):
            output_model = gr.Model3D(label="3D Output", height=600, elem_id="model-container")
            full_screen_btn = gr.Button("Toggle Full Screen ⛶", size="sm")

    gr.Markdown("---")

    with gr.Row():
        with gr.Column():
            gr.Markdown("## RGB | DEPTH | CONFIDENCE")
            artifact_gallery = gr.Gallery(columns=3, height="auto", label="Logs")

    full_screen_btn.click(None, None, None, js=fullscreen_js)

    run_btn.click(
        fn=dummy_process,
        inputs=[input_files, n_iterations, render_mode, post_proc, clean_depth],
        outputs=[output_model, artifact_gallery]
    )

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