Upload hdf5_to_mp4.py with huggingface_hub

hdf5_to_mp4.py

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+# Copyright (c) 2024-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""
+Script to convert HDF5 demonstration files to MP4 videos.
+
+This script converts camera frames stored in HDF5 demonstration files to MP4 videos.
+It supports multiple camera modalities including RGB, segmentation, and normal maps.
+The output videos are saved in the specified directory with appropriate naming.
+
+required arguments:
+    --input_file         Path to the input HDF5 file.
+    --output_dir         Directory to save the output MP4 files.
+
+optional arguments:
+    --input_keys         List of input keys to process from the HDF5 file. (default: ["table_cam", "wrist_cam", "table_cam_segmentation", "table_cam_normals", "table_cam_shaded_segmentation"])
+    --video_height       Height of the output video in pixels. (default: 704)
+    --video_width        Width of the output video in pixels. (default: 1280)
+    --framerate          Frames per second for the output video. (default: 30)
+"""
+
+# Standard library imports
+import argparse
+import h5py
+import numpy as np
+
+# Third-party imports
+import os
+
+import cv2
+
+# Constants
+DEFAULT_VIDEO_HEIGHT = 704
+DEFAULT_VIDEO_WIDTH = 1280
+DEFAULT_INPUT_KEYS = [
+    "table_cam",
+    "wrist_cam",
+    "table_cam_segmentation",
+    "table_cam_normals",
+    "table_cam_shaded_segmentation",
+    "table_cam_depth",
+]
+DEFAULT_FRAMERATE = 30
+LIGHT_SOURCE = np.array([0.0, 0.0, 1.0])
+MIN_DEPTH = 0.0
+MAX_DEPTH = 1.5
+
+
+def parse_args():
+    """Parse command line arguments."""
+    parser = argparse.ArgumentParser(description="Convert HDF5 demonstration files to MP4 videos.")
+    parser.add_argument(
+        "--input_file",
+        type=str,
+        required=True,
+        help="Path to the input HDF5 file containing demonstration data.",
+    )
+    parser.add_argument(
+        "--output_dir",
+        type=str,
+        required=True,
+        help="Directory path where the output MP4 files will be saved.",
+    )
+
+    parser.add_argument(
+        "--input_keys",
+        type=str,
+        nargs="+",
+        default=DEFAULT_INPUT_KEYS,
+        help="List of input keys to process.",
+    )
+    parser.add_argument(
+        "--video_height",
+        type=int,
+        default=DEFAULT_VIDEO_HEIGHT,
+        help="Height of the output video in pixels.",
+    )
+    parser.add_argument(
+        "--video_width",
+        type=int,
+        default=DEFAULT_VIDEO_WIDTH,
+        help="Width of the output video in pixels.",
+    )
+    parser.add_argument(
+        "--framerate",
+        type=int,
+        default=DEFAULT_FRAMERATE,
+        help="Frames per second for the output video.",
+    )
+
+    args = parser.parse_args()
+
+    return args
+
+
+def write_demo_to_mp4(
+    hdf5_file,
+    demo_id,
+    frames_path,
+    input_key,
+    output_dir,
+    video_height,
+    video_width,
+    framerate=DEFAULT_FRAMERATE,
+):
+    """Convert frames from an HDF5 file to an MP4 video.
+
+    Args:
+        hdf5_file (str): Path to the HDF5 file containing the frames.
+        demo_id (int): ID of the demonstration to convert.
+        frames_path (str): Path to the frames data in the HDF5 file.
+        input_key (str): Name of the input key to convert.
+        output_dir (str): Directory to save the output MP4 file.
+        video_height (int): Height of the output video in pixels.
+        video_width (int): Width of the output video in pixels.
+        framerate (int, optional): Frames per second for the output video. Defaults to 30.
+    """
+    with h5py.File(hdf5_file, "r") as f:
+        # Get frames based on input key type
+        if "shaded_segmentation" in input_key:
+            temp_key = input_key.replace("shaded_segmentation", "segmentation")
+            frames = f[f"data/demo_{demo_id}/obs/{temp_key}"]
+        else:
+            frames = f[frames_path + "/" + input_key]
+
+        # Setup video writer
+        output_path = os.path.join(output_dir, f"demo_{demo_id}_{input_key}.mp4")
+        fourcc = cv2.VideoWriter_fourcc(*"mp4v")
+        if "depth" in input_key:
+            video = cv2.VideoWriter(output_path, fourcc, framerate, (video_width, video_height), isColor=False)
+        else:
+            video = cv2.VideoWriter(output_path, fourcc, framerate, (video_width, video_height))
+
+        # Process and write frames
+        for ix, frame in enumerate(frames):
+            # Convert normal maps to uint8 if needed
+            if "normals" in input_key:
+                frame = (frame * 255.0).astype(np.uint8)
+
+            # Process shaded segmentation frames
+            elif "shaded_segmentation" in input_key:
+                seg = frame[..., :-1]
+                normals_key = input_key.replace("shaded_segmentation", "normals")
+                normals = f[f"data/demo_{demo_id}/obs/{normals_key}"][ix]
+                shade = 0.5 + (normals * LIGHT_SOURCE[None, None, :]).sum(axis=-1) * 0.5
+                shaded_seg = (shade[..., None] * seg).astype(np.uint8)
+                frame = np.concatenate((shaded_seg, frame[..., -1:]), axis=-1)
+
+            # Convert RGB to BGR
+            if "depth" not in input_key:
+                frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
+            else:
+                frame = (frame[..., 0] - MIN_DEPTH) / (MAX_DEPTH - MIN_DEPTH)
+                frame = np.where(frame < 0.01, 1.0, frame)
+                frame = 1.0 - frame
+                frame = (frame * 255.0).astype(np.uint8)
+
+            # Resize to video resolution
+            frame = cv2.resize(frame, (video_width, video_height), interpolation=cv2.INTER_CUBIC)
+            video.write(frame)
+
+        video.release()
+
+
+def get_num_demos(hdf5_file):
+    """Get the number of demonstrations in the HDF5 file.
+
+    Args:
+        hdf5_file (str): Path to the HDF5 file.
+
+    Returns:
+        int: Number of demonstrations found in the file.
+    """
+    with h5py.File(hdf5_file, "r") as f:
+        return len(f["data"].keys())
+
+
+def main():
+    """Main function to convert all demonstrations to MP4 videos."""
+    # Parse command line arguments
+    args = parse_args()
+
+    # Create output directory if it doesn't exist
+    os.makedirs(args.output_dir, exist_ok=True)
+
+    # Get number of demonstrations from the file
+    num_demos = get_num_demos(args.input_file)
+    print(f"Found {num_demos} demonstrations in {args.input_file}")
+
+    # Convert each demonstration
+    for i in range(num_demos):
+        frames_path = f"data/demo_{str(i)}/obs"
+        for input_key in args.input_keys:
+            write_demo_to_mp4(
+                args.input_file,
+                i,
+                frames_path,
+                input_key,
+                args.output_dir,
+                args.video_height,
+                args.video_width,
+                args.framerate,
+            )
+
+
+if __name__ == "__main__":
+    main()