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"""
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()
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