---
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.