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406662d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 | # Copyright (c) 2024-2026, 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 create a new dataset by combining existing HDF5 demonstrations with visually augmented MP4 videos.
This script takes an existing HDF5 dataset containing demonstrations and a directory of MP4 videos
that are visually augmented versions of the original demonstration videos (e.g., with different lighting,
color schemes, or visual effects). It creates a new HDF5 dataset that preserves all the original
demonstration data (actions, robot state, etc.) but replaces the video frames with the augmented versions.
required arguments:
--input_file Path to the input HDF5 file containing original demonstrations.
--output_file Path to save the new HDF5 file with augmented videos.
--videos_dir Directory containing the visually augmented MP4 videos.
"""
import argparse
import glob
import os
import cv2
import h5py
import numpy as np
def parse_args():
"""Parse command line arguments."""
parser = argparse.ArgumentParser(description="Create a new dataset with visually augmented videos.")
parser.add_argument(
"--input_file",
type=str,
required=True,
help="Path to the input HDF5 file containing original demonstrations.",
)
parser.add_argument(
"--videos_dir",
type=str,
required=True,
help="Directory containing the visually augmented MP4 videos.",
)
parser.add_argument(
"--output_file",
type=str,
required=True,
help="Path to save the new HDF5 file with augmented videos.",
)
args = parser.parse_args()
return args
def get_frames_from_mp4(video_path, target_height=None, target_width=None):
"""Extract frames from an MP4 video file.
Args:
video_path (str): Path to the MP4 video file.
target_height (int, optional): Target height for resizing frames. If None, no resizing is done.
target_width (int, optional): Target width for resizing frames. If None, no resizing is done.
Returns:
np.ndarray: Array of frames from the video in RGB format.
"""
# Open the video file
video = cv2.VideoCapture(video_path)
# Get video properties
frame_count = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
# Read all frames into a numpy array
frames = []
for _ in range(frame_count):
ret, frame = video.read()
if not ret:
break
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
if target_height is not None and target_width is not None:
frame = cv2.resize(frame, (target_width, target_height), interpolation=cv2.INTER_LINEAR)
frames.append(frame)
# Convert to numpy array
frames = np.array(frames).astype(np.uint8)
# Release the video object
video.release()
return frames
def process_video_and_demo(f_in, f_out, video_path, orig_demo_id, new_demo_id):
"""Process a single video and create a new demo with augmented video frames.
Args:
f_in (h5py.File): Input HDF5 file.
f_out (h5py.File): Output HDF5 file.
video_path (str): Path to the augmented video file.
orig_demo_id (int): ID of the original demo to copy.
new_demo_id (int): ID for the new demo.
"""
# Get original demo data
actions = f_in[f"data/demo_{str(orig_demo_id)}/actions"]
eef_pos = f_in[f"data/demo_{str(orig_demo_id)}/obs/eef_pos"]
eef_quat = f_in[f"data/demo_{str(orig_demo_id)}/obs/eef_quat"]
gripper_pos = f_in[f"data/demo_{str(orig_demo_id)}/obs/gripper_pos"]
wrist_cam = f_in[f"data/demo_{str(orig_demo_id)}/obs/wrist_cam"]
# Get original video resolution
orig_video = f_in[f"data/demo_{str(orig_demo_id)}/obs/table_cam"]
target_height, target_width = orig_video.shape[1:3]
# Extract frames from video with original resolution
frames = get_frames_from_mp4(video_path, target_height, target_width)
# Create new datasets
f_out.create_dataset(f"data/demo_{str(new_demo_id)}/actions", data=actions, compression="gzip")
f_out.create_dataset(f"data/demo_{str(new_demo_id)}/obs/eef_pos", data=eef_pos, compression="gzip")
f_out.create_dataset(f"data/demo_{str(new_demo_id)}/obs/eef_quat", data=eef_quat, compression="gzip")
f_out.create_dataset(f"data/demo_{str(new_demo_id)}/obs/gripper_pos", data=gripper_pos, compression="gzip")
f_out.create_dataset(
f"data/demo_{str(new_demo_id)}/obs/table_cam", data=frames.astype(np.uint8), compression="gzip"
)
f_out.create_dataset(f"data/demo_{str(new_demo_id)}/obs/wrist_cam", data=wrist_cam, compression="gzip")
# Copy attributes
f_out[f"data/demo_{str(new_demo_id)}"].attrs["num_samples"] = f_in[f"data/demo_{str(orig_demo_id)}"].attrs[
"num_samples"
]
def main():
"""Main function to create a new dataset with augmented videos."""
# Parse command line arguments
args = parse_args()
# Get list of MP4 videos
search_path = os.path.join(args.videos_dir, "*.mp4")
video_paths = glob.glob(search_path)
video_paths.sort()
print(f"Found {len(video_paths)} MP4 videos in {args.videos_dir}")
# Create output directory if it doesn't exist
os.makedirs(os.path.dirname(args.output_file), exist_ok=True)
with h5py.File(args.input_file, "r") as f_in, h5py.File(args.output_file, "w") as f_out:
# Copy all data from input to output
f_in.copy("data", f_out)
# Get the largest demo ID to start new demos from
demo_ids = [int(key.split("_")[1]) for key in f_in["data"].keys()]
next_demo_id = max(demo_ids) + 1 # noqa: SIM113
print(f"Starting new demos from ID: {next_demo_id}")
# Process each video and create new demo
for video_path in video_paths:
# Extract original demo ID from video filename
video_filename = os.path.basename(video_path)
orig_demo_id = int(video_filename.split("_")[1])
process_video_and_demo(f_in, f_out, video_path, orig_demo_id, next_demo_id)
next_demo_id += 1
print(f"Augmented data saved to {args.output_file}")
if __name__ == "__main__":
main()
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