openpi / droid /scripts /visualize_droid_episode.py
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"""
Simple DROID Episode Visualizer
Just loads and displays DROID episodes to verify data format.
No tracking, no projection - pure visualization.
"""
import sys
import numpy as np
import tensorflow_datasets as tfds
from pathlib import Path
import argparse
import cv2
from tqdm import tqdm
def visualize_episode(droid_path: str, episode_index: int = 0, output_dir: str = '/tmp/droid_viz'):
"""
Load and visualize a DROID episode.
Args:
droid_path: Path to DROID RLDS dataset
episode_index: Which episode to visualize
output_dir: Output directory for videos
"""
print(f"Loading episode {episode_index} from {droid_path}...")
# Load DROID
builder = tfds.builder_from_directory(droid_path)
dataset = builder.as_dataset(split='train')
# Create output directory
output_path = Path(output_dir)
output_path.mkdir(parents=True, exist_ok=True)
# Find episode
for idx, episode in enumerate(dataset):
if idx != episode_index:
continue
print(f"✓ Found episode {episode_index}")
# Extract steps
steps = list(episode['steps'])
print(f" Total steps: {len(steps)}")
# Get metadata
try:
recording_path = episode['episode_metadata']['recording_folderpath'].numpy().decode('utf-8')
print(f" Recording: {recording_path}")
except:
recording_path = "unknown"
try:
language = steps[0]['language_instruction'].numpy().decode('utf-8')
print(f" Task: {language}")
except:
language = "No instruction"
# Save info
with open(output_path / 'episode_info.txt', 'w') as f:
f.write(f"Episode: {episode_index}\n")
f.write(f"Steps: {len(steps)}\n")
f.write(f"Recording: {recording_path}\n")
f.write(f"Task: {language}\n")
# Process frames
valid_frames_ext = []
valid_frames_wrist = []
print("\nProcessing frames...")
for step_idx, step in enumerate(tqdm(steps)):
# Try to decode images
try:
# Exterior camera
img_ext_bytes = step['observation']['exterior_image_1_left'].numpy()
img_ext = cv2.imdecode(np.frombuffer(img_ext_bytes, dtype=np.uint8), cv2.IMREAD_COLOR)
# Wrist camera
img_wrist_bytes = step['observation']['wrist_image_left'].numpy()
img_wrist = cv2.imdecode(np.frombuffer(img_wrist_bytes, dtype=np.uint8), cv2.IMREAD_COLOR)
if img_ext is not None and img_wrist is not None:
# Resize for consistency
img_ext = cv2.resize(img_ext, (448, 448))
img_wrist = cv2.resize(img_wrist, (448, 448))
# Add info text
cv2.putText(img_ext, f"Frame {step_idx}/{len(steps)}", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
cv2.putText(img_wrist, f"Frame {step_idx}/{len(steps)}", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
valid_frames_ext.append(img_ext)
valid_frames_wrist.append(img_wrist)
else:
if step_idx == 0:
print(f" ⚠ Frame {step_idx}: decode returned None")
except Exception as e:
if step_idx == 0:
print(f" ⚠ Frame {step_idx}: decode failed - {e}")
print(f"\n✓ Successfully decoded {len(valid_frames_ext)} frames out of {len(steps)}")
if len(valid_frames_ext) == 0:
print("✗ No valid frames found. This episode may be corrupted.")
print(" Try a different episode with --episode-index N")
return False
# Save videos
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
video_ext = cv2.VideoWriter(
str(output_path / 'exterior_camera.mp4'),
fourcc, 10, (448, 448)
)
video_wrist = cv2.VideoWriter(
str(output_path / 'wrist_camera.mp4'),
fourcc, 10, (448, 448)
)
for frame_ext, frame_wrist in zip(valid_frames_ext, valid_frames_wrist):
video_ext.write(frame_ext)
video_wrist.write(frame_wrist)
video_ext.release()
video_wrist.release()
# Save first frame as image
cv2.imwrite(str(output_path / 'frame_0_exterior.png'), valid_frames_ext[0])
cv2.imwrite(str(output_path / 'frame_0_wrist.png'), valid_frames_wrist[0])
print(f"\n✓ Saved videos to {output_path}:")
print(f" exterior_camera.mp4")
print(f" wrist_camera.mp4")
print(f" frame_0_exterior.png")
print(f" frame_0_wrist.png")
# Print joint info
try:
joints = steps[0]['observation']['joint_position'].numpy()
print(f"\n✓ Joint positions (first frame): {joints}")
cart_pos = steps[0]['observation']['cartesian_position'].numpy()
print(f"✓ Cartesian position (first frame): {cart_pos}")
except Exception as e:
print(f"⚠ Could not read robot state: {e}")
return True
print(f"✗ Episode {episode_index} not found in dataset")
return False
def main():
parser = argparse.ArgumentParser(description="Visualize DROID episode")
parser.add_argument(
'--droid-path',
type=str,
default='/mnt/kevin/data/droid/droid/1.0.0',
help='Path to DROID RLDS dataset'
)
parser.add_argument(
'--episode-index',
type=int,
default=0,
help='Episode index to visualize (try different indices if one fails)'
)
parser.add_argument(
'--output-dir',
type=str,
default='/tmp/droid_viz',
help='Output directory'
)
args = parser.parse_args()
print("=" * 60)
print("DROID Episode Visualizer")
print("=" * 60 + "\n")
success = visualize_episode(args.droid_path, args.episode_index, args.output_dir)
if not success:
print("\nTry a different episode:")
print(" python visualize_droid_episode.py --episode-index 1")
print(" python visualize_droid_episode.py --episode-index 10")
print(" python visualize_droid_episode.py --episode-index 100")
return 1
print("\n" + "=" * 60)
print("Visualization Complete!")
print("=" * 60)
return 0
if __name__ == "__main__":
sys.exit(main())