Voxel51/CitrusFarm-Sample

CitrusFarm sample → FiftyOne (Native Multimodal MCAP)

One sequence of CitrusFarm, the multimodal agricultural robotics dataset from the ARCS Lab at the University of California Riverside, converted from ROS 1 bags to a native multimodal MCAP episode.

A Clearpath Jackal drives the rows of citrus trees at the university's Agricultural Experimental Station carrying a FLIR Blackfly monochrome camera, a FLIR ADK thermal camera, a Mapir Survey3 camera that sees red, green and near-infrared, a Stereolabs ZED 2i stereo camera with its depth, a Velodyne LiDAR, a Microstrain inertial unit and a Piksi GPS-RTK receiver, and records its own wheel odometry. The release holds seven sequences from three fields, 1.3 TB in all; this sample is the smallest of them, 06_14B_Jackal, from field 14B.

5m 03s of driving over 357 m, 3,026 monochrome, 3,024 thermal, 3,025 red-green-NIR and 3,022 ZED frames, 2,998 LiDAR scans and 3,024 GPS-RTK fixes.

Installation

pip install fiftyone

Usage

import fiftyone as fo
import fiftyone.utils.huggingface as fouh

dataset = fouh.load_from_hub(
    "Voxel51/CitrusFarm-Sample",
    name="CitrusFarm-Sample",
    persistent=True,
)
fo.launch_app(dataset)

What you get

The episode contains:

• /mono, the Blackfly monochrome camera at 1440x1080, as foxglove.CompressedVideo
• /thermal, the ADK thermal camera at 640x512, as foxglove.CompressedVideo
• /rgn, the Survey3 camera's red, green and near-infrared channels at 1280x720, as foxglove.CompressedVideo
• /zed-left and /zed-right, the ZED's rectified color images at 1280x720, as foxglove.CompressedVideo
• /zed-depth, the ZED's depth registered to its left image, as foxglove.CompressedImage (16-bit PNG, millimetres, 0 where the ZED gives no depth)
• a -calibration topic beside each camera, as foxglove.CameraCalibration
• /lidar-points, the Velodyne scans, as foxglove.PointCloud with x, y, z, intensity and ring
• /imu.plot, the Microstrain inertial unit
• /gnss, the GPS-RTK fixes, as foxglove.LocationFix
• /wheel-odometry and /zed-odometry, the robot's and the ZED's own pose estimates, as foxglove.PoseInFrame, each with its position on a .plot channel
• /ground-truth.plot, the release's ground-truth trajectory
• /tf, the sensors' poses from the release's calibration, as foxglove.FrameTransform
• /sequence, naming the sequence and its field

The episode carries the fields sequence, field, recorded, duration, num_mono_frames, num_thermal_frames, num_rgn_frames, num_zed_frames, num_depth_frames, num_lidar_scans, num_lidar_points, num_gnss_fixes, valid_depth_fraction and ground_truth_path_m. valid_depth_fraction is the share of ZED depth pixels holding a value, and ground_truth_path_m the length of the ground-truth trajectory in metres.

Notes on the conversion

The release splits each sequence into ROS 1 bags by sensor group and by size; every bag of the sequence was read together, in time order, without a ROS install. The cameras are re-encoded to Annex-B H.264 without B-frames, one access unit per frame, on each frame's own timestamp. The release records the ZED depth as 32-bit floats in metres, which are carried as 16-bit PNG in millimetres, rounded, with 0 where the ZED reports none.

The calibration is the release's: Kalibr's intrinsics for the five cameras, and its extrinsics chained through the cameras, the inertial unit, the LiDAR, the GPS antenna and the robot's base. Kalibr's camera chain and its camera-to-IMU result map points from one frame into the next, so /tf carries their inverse, each frame's pose in its parent; the LiDAR results are carried as the release gives them, the child's pose in the parent. The ground-truth file gives positions only, so it is carried as a position track. The ZED's confidence map and inertial unit, both magnetometers and the GPS receiver's state are not carried.

License & attribution

CitrusFarm is distributed under the Creative Commons Attribution-ShareAlike 4.0 International license (CC-BY-SA-4.0), and this conversion is distributed under the same license. Cite:

@inproceedings{teng2023multimodal,
  title={Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms},
  author={Teng, Hanzhe and Wang, Yipeng and Song, Xiaoao and Karydis, Konstantinos},
  booktitle={International Symposium on Visual Computing},
  pages={571--582},
  year={2023}
}

Changes from the source: one of the release's seven sequences, converted from ROS 1 bags to the FiftyOne MCAP flavor, H.264 encoding of the five camera streams, the ZED depth carried as 16-bit millimetres, the release's calibration carried as camera intrinsics and transforms with Kalibr's inverted, and the confidence map, the ZED inertial unit, the magnetometers and the receiver state left out.