#!/usr/bin/env python3 """ Inspect preprocessed DROID data to verify structure and visualize tracks. Checks: 1. Data structure (keys, shapes) 2. Track counts (should be 1105 for both views after reprocessing) 3. Wrist mesh vertices existence 4. Visualize tracked points on sample frames """ import numpy as np import cv2 import sys from pathlib import Path import random # Add parent to path sys.path.insert(0, str(Path(__file__).parent.parent)) def inspect_npz_structure(npz_path): """Print detailed structure of .npz file.""" data = np.load(npz_path, allow_pickle=True) print(f"\n{'='*80}") print(f"File: {npz_path.name}") print(f"{'='*80}") # Print all keys print("\nKeys in file:") for key in sorted(data.keys()): print(f" {key}") # Print shapes print("\nData shapes:") for key in sorted(data.keys()): value = data[key] if hasattr(value, 'shape'): print(f" {key:40s}: {value.shape}") else: print(f" {key:40s}: {type(value).__name__} = {value}") # Check for specific keys print("\nStructure checks:") # Check exterior tracks if 'tracks_exterior' in data: tracks_ext = data['tracks_exterior'] print(f" ✓ Exterior tracks: {tracks_ext.shape} (expected: [T, 1105, 2])") if tracks_ext.shape[1] == 1105: print(f" ✓ Correct point count (1105)") else: print(f" ✗ WRONG point count! Expected 1105, got {tracks_ext.shape[1]}") else: print(f" ✗ Missing 'tracks_exterior'") # Check wrist tracks if 'tracks_wrist' in data: tracks_wrist = data['tracks_wrist'] print(f" ✓ Wrist tracks: {tracks_wrist.shape} (expected: [T, 1105, 2])") if tracks_wrist.shape[1] == 1105: print(f" ✓ Correct point count (1105)") else: print(f" ✗ WRONG point count! Expected 1105, got {tracks_wrist.shape[1]}") else: print(f" ✗ Missing 'tracks_wrist'") # Check wrist mesh vertices (fixed) if 'mesh_vertices_2d_wrist_fixed' in data: mesh_wrist = data['mesh_vertices_2d_wrist_fixed'] print(f" ✓ Wrist fixed mesh: {mesh_wrist.shape} (expected: [T, 7, 2])") else: print(f" ✗ Missing 'mesh_vertices_2d_wrist_fixed'") # Check exterior mesh vertices if 'mesh_vertices_2d_exterior' in data: mesh_ext = data['mesh_vertices_2d_exterior'] print(f" ✓ Exterior mesh: {mesh_ext.shape} (expected: [T, 7, 2])") else: print(f" ✗ Missing 'mesh_vertices_2d_exterior'") return data def visualize_tracks(data, npz_path, output_dir, num_frames=5): """ Visualize tracked points on sample frames. Shows: - Exterior: mesh vertices (blue) + tracked points (green) - Wrist: fixed mesh (cyan) + tracked mesh (magenta) + tracked points (green) """ images_ext = data['images_exterior'] # [T, H, W, 3] images_wrist = data['images_wrist'] tracks_ext = data['tracks_exterior'] # [T, N, 2] tracks_wrist = data['tracks_wrist'] tracks_vis_ext = data['tracks_vis_exterior'] tracks_vis_wrist = data['tracks_vis_wrist'] # Get mesh data mesh_2d_ext = data.get('mesh_vertices_2d_exterior', None) # [T, 7, 2] mesh_vis_ext = data.get('mesh_vertices_vis_exterior', None) # [T, 7] mesh_2d_wrist_fixed = data.get('mesh_vertices_2d_wrist_fixed', None) T = images_ext.shape[0] # Sample frames evenly frame_indices = np.linspace(0, T-1, min(num_frames, T), dtype=int) print(f"\nVisualizing {len(frame_indices)} frames...") output_dir = Path(output_dir) output_dir.mkdir(parents=True, exist_ok=True) for idx, t in enumerate(frame_indices): # Exterior view viz_ext = images_ext[t].copy() # Draw ground truth mesh vertices (blue circles) if mesh_2d_ext is not None and mesh_vis_ext is not None: for i in range(7): if mesh_vis_ext[t, i]: pt = tuple(mesh_2d_ext[t, i].astype(int)) cv2.circle(viz_ext, pt, 5, (255, 0, 0), 2) # Blue hollow cv2.putText(viz_ext, str(i), (pt[0]+6, pt[1]-6), cv2.FONT_HERSHEY_SIMPLEX, 0.3, (255, 0, 0), 1) # Draw all tracked points (green, smaller) for i in range(tracks_ext.shape[1]): if tracks_vis_ext[t, i]: pt = tuple(tracks_ext[t, i].astype(int)) # First 7 points are mesh - draw in red if i < 7: cv2.circle(viz_ext, pt, 3, (0, 0, 255), -1) # Red filled else: cv2.circle(viz_ext, pt, 1, (0, 255, 0), -1) # Green cv2.putText(viz_ext, f"Ext: GT mesh (blue) | Tracked mesh (red) | Others (green) | {tracks_ext.shape[1]} pts", (5, 15), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (255, 255, 255), 1) # Wrist view viz_wrist = images_wrist[t].copy() # Draw TRACKED mesh vertices (first 7 points) - magenta filled circles for i in range(min(7, tracks_wrist.shape[1])): if tracks_vis_wrist[t, i]: pt = tuple(tracks_wrist[t, i].astype(int)) cv2.circle(viz_wrist, pt, 3, (255, 0, 255), -1) # Magenta filled # Draw FIXED mesh vertices (from separate array) - cyan hollow circles if mesh_2d_wrist_fixed is not None: for i in range(7): pt = tuple(mesh_2d_wrist_fixed[t, i].astype(int)) cv2.circle(viz_wrist, pt, 4, (255, 255, 0), 2) # Cyan hollow # Label finger tips and joints if i in [1, 2, 3, 4]: cv2.putText(viz_wrist, str(i), (pt[0]+5, pt[1]-5), cv2.FONT_HERSHEY_SIMPLEX, 0.25, (255, 255, 0), 1) # Draw other tracked points (grid + random, green, smaller) for i in range(7, tracks_wrist.shape[1]): if tracks_vis_wrist[t, i]: pt = tuple(tracks_wrist[t, i].astype(int)) cv2.circle(viz_wrist, pt, 1, (0, 255, 0), -1) # Green cv2.putText(viz_wrist, f"Wrist: Tracked mesh (magenta) | Fixed mesh (cyan) | Others (green) | {tracks_wrist.shape[1]} pts", (5, 15), cv2.FONT_HERSHEY_SIMPLEX, 0.3, (255, 255, 255), 1) # Concatenate side by side combined = np.concatenate([viz_ext, viz_wrist], axis=1) cv2.putText(combined, f"Episode {data['episode_idx']} | Frame {t}/{T}", (combined.shape[1]//2 - 60, 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2) # Save frame output_path = output_dir / f"{npz_path.stem}_frame_{t:03d}.png" cv2.imwrite(str(output_path), combined) print(f" Saved: {output_path.name}") def main(): import argparse parser = argparse.ArgumentParser(description="Inspect preprocessed DROID data") parser.add_argument('--data-dir', type=str, default='/mnt/kevin/data/droid_processed_1000pts', help='Directory with preprocessed .npz files') parser.add_argument('--num-samples', type=int, default=5, help='Number of episodes to sample (default: 5)') parser.add_argument('--num-frames', type=int, default=5, help='Number of frames to visualize per episode (default: 5)') parser.add_argument('--output-dir', type=str, default='/tmp/droid_inspect', help='Output directory for visualizations') parser.add_argument('--specific-episodes', type=int, nargs='+', default=None, help='Specific episode indices to inspect (e.g., 100 200 300)') args = parser.parse_args() data_dir = Path(args.data_dir) / 'data' output_dir = Path(args.output_dir) output_dir.mkdir(parents=True, exist_ok=True) # Get all .npz files npz_files = sorted(data_dir.glob('episode_*.npz')) print(f"Found {len(npz_files)} preprocessed episodes in {data_dir}") if len(npz_files) == 0: print("No .npz files found!") return # Select episodes to inspect if args.specific_episodes: # Use specific episode indices sample_files = [] for ep_idx in args.specific_episodes: ep_file = data_dir / f"episode_{ep_idx:06d}.npz" if ep_file.exists(): sample_files.append(ep_file) else: print(f"Warning: Episode {ep_idx} not found") else: # Random sample sample_files = random.sample(npz_files, min(args.num_samples, len(npz_files))) print(f"\nInspecting {len(sample_files)} episodes...\n") # Inspect each file for npz_path in sample_files: try: # Print structure data = inspect_npz_structure(npz_path) # Visualize tracks visualize_tracks(data, npz_path, output_dir, num_frames=args.num_frames) except Exception as e: print(f"\nError processing {npz_path.name}: {e}") import traceback traceback.print_exc() continue print(f"\n{'='*80}") print(f"Inspection complete!") print(f"Visualizations saved to: {output_dir}") print(f"{'='*80}") if __name__ == '__main__': main()