Revert to working minimal version

app.py

@@ -1,380 +1,16 @@
-import json
-import os
-import html
-from pathlib import Path
-from typing import Dict, List
-from functools import lru_cache
-
-import gradio as gr
-import plotly.graph_objects as go
-import plotly.io as pio
-
-def get_data_dir():
-    """Get data directory path."""
-    try:
-        return Path(__file__).parent / "data"
-    except:
-        return Path("data")
-
-METRIC_LABELS = {
-    "x_cm": "X (cm)",
-    "y_cm": "Y (cm)",
-    "z_cm": "Z (cm)",
-    "yaw_deg": "Yaw (°)",
-    "pitch_deg": "Pitch (°)",
-    "roll_deg": "Roll (°)",
-}
-
-PLOT_GRID = [
-    ["x_cm", "y_cm", "z_cm"],
-    ["yaw_deg", "pitch_deg", "roll_deg"],
-]
-
-PLOT_ORDER = [metric for row in PLOT_GRID for metric in row]
-
-CUSTOM_CSS = """
-:root, .gradio-container, body {
-    background-color: #050a18 !important;
-    color: #f8fafc !important;
-    font-family: 'Inter', 'Segoe UI', system-ui, sans-serif;
-}
-.side-panel {
-    background: #0f172a;
-    padding: 20px;
-    border-radius: 18px;
-    border: 1px solid #1f2b47;
-    min-height: 100%;
-}
-.stats-card ul {
-    list-style: none;
-    padding: 0;
-    margin: 0;
-    font-size: 0.92rem;
-}
-.stats-card li {
-    margin-bottom: 10px;
-    color: #e2e8f0;
-}
-.stats-card span {
-    display: inline-block;
-    margin-right: 6px;
-    color: #7dd3fc;
-}
-.main-panel {
-    padding-top: 8px;
-}
-.instruction-card {
-    background: #0f172a;
-    padding: 18px 20px;
-    border-radius: 18px;
-    border: 1px solid #1f2b47;
-}
-.instruction-label {
-    font-size: 0.75rem;
-    letter-spacing: 0.12em;
-    text-transform: uppercase;
-    color: #94a3b8;
-    margin-bottom: 10px;
-}
-.instruction-text {
-    font-size: 1.1rem;
-    line-height: 1.5;
-}
-.video-card {
-    background: #0f172a;
-    border: 1px solid #1f2b47;
-    border-radius: 18px;
-    padding: 18px 20px;
-    margin-top: 18px;
-}
-.video-title {
-    font-size: 0.78rem;
-    text-transform: uppercase;
-    letter-spacing: 0.18em;
-    color: #94a3b8;
-    margin-bottom: 8px;
-}
-.video-panel video {
-    border-radius: 12px;
-    border: 1px solid #1f2b47;
-    background: #030712;
-}
-.download-button button {
-    border-radius: 999px;
-    border: 1px solid #334155;
-    background: #1e293b;
-    color: #f8fafc;
-    font-size: 0.85rem;
-    padding: 8px 24px;
-}
-.download-button button:hover {
-    border-color: #67e8f9;
-    color: #67e8f9;
-}
-.plots-wrap {
-    margin-top: 18px;
-}
-.plots-wrap .gr-row {
-    gap: 16px;
-}
-.plot-html {
-    background: #111a2c;
-    border-radius: 12px;
-    padding: 10px;
-    border: 1px solid #1f2b47;
-    min-height: 320px;
-}
-.plot-html iframe {
-    width: 100%;
-    height: 300px;
-    border: none;
-}
 """
-
-
-@lru_cache(maxsize=1)
-def load_data():
-    """Load all data files."""
-    data_dir = get_data_dir()
-    metadata_path = data_dir / "metadata.json"
-    end_effector_path = data_dir / "end_effector.json"
-    hands_2d_path = data_dir / "hands_2d.json"
-    
-    metadata = {}
-    end_effector = {}
-    hands_2d = {}
-    
-    if metadata_path.exists():
-        with open(metadata_path, 'r') as f:
-            metadata = json.load(f)
-    
-    if end_effector_path.exists():
-        with open(end_effector_path, 'r') as f:
-            end_effector = json.load(f)
-    
-    if hands_2d_path.exists():
-        with open(hands_2d_path, 'r') as f:
-            hands_2d = json.load(f)
-    
-    return metadata, end_effector, hands_2d
-
-
-def build_state_dataframe(metadata: dict, end_effector: dict, hand: str = "left"):
-    """Build state dataframe from JSON data."""
-    fps = metadata.get('fps', 60)
-    
-    try:
-        frame_keys = sorted([int(k) for k in end_effector.keys() if str(k).isdigit()])
-    except:
-        frame_keys = []
-    
-    timestamps = []
-    state_data = {
-        'wrist_x_cm': [],
-        'wrist_y_cm': [],
-        'wrist_z_cm': [],
-        'wrist_yaw_deg': [],
-        'wrist_pitch_deg': [],
-        'wrist_roll_deg': [],
-    }
-    
-    for frame_idx in frame_keys:
-        frame_key = str(frame_idx)
-        t = frame_idx / fps
-        timestamps.append(t)
-        
-        ee_data = end_effector.get(frame_key, {}) or {}
-        hand_data = ee_data.get(hand + "_hand")
-        
-        if hand_data and isinstance(hand_data, dict):
-            pose = hand_data.get('pose_6dof')
-            if pose and len(pose) >= 6:
-                state_data['wrist_x_cm'].append(pose[0] * 100)  # m to cm
-                state_data['wrist_y_cm'].append(pose[1] * 100)
-                state_data['wrist_z_cm'].append(pose[2] * 100)
-                state_data['wrist_roll_deg'].append(pose[3] * 57.3)  # rad to deg
-                state_data['wrist_pitch_deg'].append(pose[4] * 57.3)
-                state_data['wrist_yaw_deg'].append(pose[5] * 57.3)
-            else:
-                for k in state_data:
-                    state_data[k].append(None)
-        else:
-            for k in state_data:
-                state_data[k].append(None)
-    
-    return timestamps, state_data
-
-
-def build_plot_fig(timestamps: List[float], state_data: Dict, metric: str) -> go.Figure:
-    """Build Plotly figure for a metric."""
-    col_name = f"wrist_{metric}"
-    if col_name not in state_data:
-        return go.Figure()
-    
-    fig = go.Figure()
-    fig.add_trace(
-        go.Scatter(
-            x=timestamps,
-            y=state_data[col_name],
-            mode="lines",
-            name="Wrist",
-        )
-    )
-    fig.update_layout(
-        margin=dict(l=20, r=20, t=30, b=20),
-        height=250,
-        template="plotly_dark",
-        legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
-        xaxis_title="Time (s)",
-        yaxis_title=METRIC_LABELS[metric],
-    )
-    fig.update_xaxes(showgrid=True, gridwidth=0.5, gridcolor="rgba(255,255,255,0.1)")
-    fig.update_yaxes(showgrid=True, gridwidth=0.5, gridcolor="rgba(255,255,255,0.1)")
-    return fig
-
-
-def build_plot_html(timestamps: List[float], state_data: Dict, metric: str) -> str:
-    """Build Plotly HTML for a metric."""
-    fig = build_plot_fig(timestamps, state_data, metric)
-    return pio.to_html(fig, include_plotlyjs="cdn", full_html=False)
-
-
-def format_instruction_html(text: str) -> str:
-    safe_text = html.escape(text)
-    return (
-        '<div class="instruction-card">'
-        '<p class="instruction-label">Language Instruction</p>'
-        f'<p class="instruction-text">{safe_text}</p>'
-        "</div>"
-    )
-
-
-def build_interface():
-    """Build Gradio interface."""
-    try:
-        metadata, end_effector, hands_2d = load_data()
-    except Exception as e:
-        print(f"Error loading data: {e}")
-        metadata, end_effector, hands_2d = {}, {}, {}
-    
-    total_frames = len(metadata.get('poses', []))
-    fps = metadata.get('fps', 60)
-    hand_detection_rate = len(hands_2d) / max(1, total_frames) * 100 if total_frames > 0 else 0
-    
-    left_poses = sum(1 for f in end_effector.values() if f and isinstance(f, dict) and f.get('left_hand'))
-    right_poses = sum(1 for f in end_effector.values() if f and isinstance(f, dict) and f.get('right_hand'))
-    
-    video_path = get_data_dir() / "video.mp4"
-    
-    # Build data for left hand
-    try:
-        left_timestamps, left_state = build_state_dataframe(metadata, end_effector, "left")
-        left_figs = {metric: build_plot_html(left_timestamps, left_state, metric) for metric in METRIC_LABELS.keys()}
-    except Exception as e:
-        print(f"Error building left hand plots: {e}")
-        left_figs = {metric: "<p>Plot unavailable</p>" for metric in METRIC_LABELS.keys()}
-    
-    # Build data for right hand
-    try:
-        right_timestamps, right_state = build_state_dataframe(metadata, end_effector, "right")
-        right_figs = {metric: build_plot_html(right_timestamps, right_state, metric) for metric in METRIC_LABELS.keys()}
-    except Exception as e:
-        print(f"Error building right hand plots: {e}")
-        right_figs = {metric: "<p>Plot unavailable</p>" for metric in METRIC_LABELS.keys()}
-    
-    stats_html = f"""
-<div class="stats-card">
-  <ul>
-    <li><span>Number of samples/frames:</span> {total_frames:,}</li>
-    <li><span>Hand detection rate:</span> {hand_detection_rate:.1f}%</li>
-    <li><span>Left hand poses:</span> {left_poses}</li>
-    <li><span>Right hand poses:</span> {right_poses}</li>
-    <li><span>Frames per second:</span> {fps:.1f}</li>
-  </ul>
-</div>
+Minimal test version
 """
-    
-    instruction_text = "LiDAR-based egocentric hand tracking for robot training data"
-    
-    theme = gr.themes.Soft(
-        primary_hue="cyan", secondary_hue="blue", neutral_hue="slate"
-    ).set(
-        body_background_fill="#0c1424",
-        body_text_color="#f8fafc",
-        block_background_fill="#111a2c",
-        block_title_text_color="#f8fafc",
-        input_background_fill="#151f33",
-        border_color_primary="#1f2b47",
-        shadow_drop="none",
-    )
-    
-    with gr.Blocks(theme=theme, css=CUSTOM_CSS) as demo:
-        gr.Markdown("# 🤖 Dynamic Intelligence - Human Demo Visualizer")
-        gr.Markdown(
-            "Egocentric hand tracking dataset for humanoid robot training. "
-            "Pipeline: iPhone LiDAR → MediaPipe → 6DoF End-Effector → Robot Training Data"
-        )
-        
-        with gr.Row(equal_height=True):
-            with gr.Column(scale=1, min_width=260, elem_classes=["side-panel"]):
-                gr.HTML(stats_html)
-            with gr.Column(scale=2, min_width=640, elem_classes=["main-panel"]):
-                instruction_box = gr.HTML(
-                    format_instruction_html(instruction_text),
-                    label="Language Instruction",
-                )
-                with gr.Column(elem_classes=["video-card"]):
-                    gr.HTML('<div class="video-title">RGB Video</div>')
-                    video = gr.Video(
-                        height=360,
-                        value=str(video_path) if video_path.exists() else None,
-                        elem_classes=["video-panel"],
-                        show_label=False,
-                        show_download_button=False,
-                    )
-                    download_button = gr.DownloadButton(
-                        label="Download",
-                        value=str(video_path) if video_path.exists() else None,
-                        elem_classes=["download-button"],
-                    )
-        
-        plot_outputs_left = []
-        gr.Markdown("### Left Hand Trajectories", elem_classes=["plots-title"])
-        with gr.Column(elem_classes=["plots-wrap"]):
-            for row in PLOT_GRID:
-                with gr.Row():
-                    for metric in row:
-                        plot = gr.HTML(value=left_figs[metric], elem_classes=["plot-html"])
-                        plot_outputs_left.append(plot)
-        
-        plot_outputs_right = []
-        gr.Markdown("### Right Hand Trajectories", elem_classes=["plots-title"])
-        with gr.Column(elem_classes=["plots-wrap"]):
-            for row in PLOT_GRID:
-                with gr.Row():
-                    for metric in row:
-                        plot = gr.HTML(value=right_figs[metric], elem_classes=["plot-html"])
-                        plot_outputs_right.append(plot)
-    
-    return demo
-
+import gradio as gr
+from pathlib import Path
 
-def main():
-    demo = build_interface()
-    demo.queue().launch(show_api=False)
+DATA_DIR = Path(__file__).parent / "data"
+video_path = DATA_DIR / "video.mp4"
 
+with gr.Blocks() as demo:
+    gr.Markdown("# Test")
+    gr.Video(value=str(video_path) if video_path.exists() else None)
 
 if __name__ == "__main__":
-    main()
+    demo.launch()
 
-# For Gradio Spaces
-try:
-    demo = build_interface()
-except Exception as e:
-    print(f"Error building interface: {e}")
-    import traceback
-    traceback.print_exc()
-    # Fallback minimal demo
-    with gr.Blocks() as demo:
-        gr.Markdown("# Error loading visualizer")
-        gr.Markdown(f"Error: {str(e)}")