README.md

metadata

pretty_name: Label Factory RGB-D Dataset 0000
license: other
tags:
  - image
  - video
  - 3d
  - rgb-d
configs:
  - config_name: depth_estimation
    data_files:
      - split: train
        path: '*/data/depth_estimation/train-*.parquet'
  - config_name: instance_segmentation
    data_files:
      - split: train
        path: '*/data/instance_segmentation/train-*.parquet'
  - config_name: object_pose_estimation
    data_files:
      - split: train
        path: '*/data/object_pose_estimation/train-*.parquet'

ABC-iRobotics/Hand_Tools: dataset 0000

Metric RGB-D scene dataset generated with the Label Factory workflow. The files for this capture are stored below the 0000/ directory so multiple numbered datasets can coexist in this repository.

Training configurations

• depth_estimation: RGB input, metric depth target, intrinsics and depth units
• instance_segmentation: RGB input, instance-mask target, boxes and annotations
• object_pose_estimation: RGB-D input, masks, camera transforms and object poses

Contents

• 318 RGB frames and aligned metric depth maps
• Metric camera calibration and world-coordinate camera poses
• Metric reconstructed point cloud
• 4 posed object instances with per-frame masks
• STL models used for pose estimation

Depth images are stored in millimetres. Pose conventions and coordinate-system metadata are recorded in 0000/sam6d_scene/annotations.json and 0000/reconstruction/metric_alignment/camera_poses_metric.json.

Limitations

Annotations are automatically generated and must be independently reviewed for the intended downstream use. Reconstruction, depth-alignment, segmentation and pose-estimation errors may remain.