# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md). # All rights reserved. # # SPDX-License-Identifier: BSD-3-Clause """Script to visualize navigation datasets. Loads a navigation dataset and generates plots showing paths, poses and obstacles. Args: dataset: Path to the HDF5 dataset file containing recorded demonstrations. output_dir: Directory path where visualization plots will be saved. figure_size: Size of the generated figures (width, height). demo_filter: If provided, only visualize specific demo(s). Can be a single demo name or comma-separated list. """ import argparse import os import h5py import matplotlib.pyplot as plt def main(): """Main function to process dataset and generate visualizations.""" # add argparse arguments parser = argparse.ArgumentParser( description="Visualize navigation dataset from locomanipulation sdg demonstrations." ) parser.add_argument( "--input_file", type=str, help="Path to the HDF5 dataset file containing recorded demonstrations." ) parser.add_argument("--output_dir", type=str, help="Directory path where visualization plots will be saved.") parser.add_argument( "--figure_size", type=int, nargs=2, default=[20, 20], help="Size of the generated figures (width, height). Default: [20, 20]", ) parser.add_argument( "--demo_filter", type=str, default=None, help="If provided, only visualize specific demo(s). Can be a single demo name or comma-separated list.", ) # parse the arguments args = parser.parse_args() # Validate inputs if not os.path.exists(args.input_file): raise FileNotFoundError(f"Dataset file not found: {args.input_file}") # Create output directory if it doesn't exist os.makedirs(args.output_dir, exist_ok=True) # Load dataset dataset = h5py.File(args.input_file, "r") demos = list(dataset["data"].keys()) # Filter demos if specified if args.demo_filter: filter_demos = [d.strip() for d in args.demo_filter.split(",")] demos = [d for d in demos if d in filter_demos] if not demos: print(f"Warning: No demos found matching filter '{args.demo_filter}'") return print(f"Visualizing {len(demos)} demonstrations...") for i, demo in enumerate(demos): print(f"Processing demo {i + 1}/{len(demos)}: {demo}") replay_data = dataset["data"][demo]["locomanipulation_sdg_output_data"] path = replay_data["base_path"] base_pose = replay_data["base_pose"] object_pose = replay_data["object_pose"] start_pose = replay_data["start_fixture_pose"] end_pose = replay_data["end_fixture_pose"] obstacle_poses = replay_data["obstacle_fixture_poses"] plt.figure(figsize=args.figure_size) plt.plot(path[0, :, 0], path[0, :, 1], "r-", label="Target Path", linewidth=2) plt.plot(base_pose[:, 0], base_pose[:, 1], "g--", label="Base Pose", linewidth=2) plt.plot(object_pose[:, 0], object_pose[:, 1], "b--", label="Object Pose", linewidth=2) plt.plot(obstacle_poses[0, :, 0], obstacle_poses[0, :, 1], "ro", label="Obstacles", markersize=8) # Add start and end markers plt.plot(start_pose[0, 0], start_pose[0, 1], "gs", label="Start", markersize=12) plt.plot(end_pose[0, 0], end_pose[0, 1], "rs", label="End", markersize=12) plt.legend(loc="upper right", ncol=1, fontsize=12) plt.axis("equal") plt.grid(True, alpha=0.3) plt.title(f"Navigation Visualization - {demo}", fontsize=16) plt.xlabel("X Position (m)", fontsize=14) plt.ylabel("Y Position (m)", fontsize=14) output_path = os.path.join(args.output_dir, f"{demo}.png") plt.savefig(output_path, dpi=150, bbox_inches="tight") plt.close() # Close the figure to free memory dataset.close() print(f"Visualization complete! Plots saved to: {args.output_dir}") if __name__ == "__main__": main()