Add Label Factory dataset card

README.md

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+---
+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"
+  - split: validation
+    path: "*/data/depth_estimation/validation-*.parquet"
+  - split: test
+    path: "*/data/depth_estimation/test-*.parquet"
+- config_name: instance_segmentation
+  data_files:
+  - split: train
+    path: "*/data/instance_segmentation/train-*.parquet"
+  - split: validation
+    path: "*/data/instance_segmentation/validation-*.parquet"
+  - split: test
+    path: "*/data/instance_segmentation/test-*.parquet"
+- config_name: object_pose_estimation
+  data_files:
+  - split: train
+    path: "*/data/object_pose_estimation/train-*.parquet"
+  - split: validation
+    path: "*/data/object_pose_estimation/validation-*.parquet"
+  - split: test
+    path: "*/data/object_pose_estimation/test-*.parquet"
+---
+
+# KarolyArmin/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
+
+Every configuration provides deterministic `train`, `validation`, and `test`
+splits. Adding another numbered capture appends rows through the wildcard paths;
+it does not replace earlier datasets.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("KarolyArmin/Hand_tools", "object_pose_estimation")
+train = dataset["train"]
+validation = dataset["validation"]
+test = dataset["test"]
+
+# PNG payloads are stored directly in Parquet.
+from io import BytesIO
+from PIL import Image
+rgb = Image.open(BytesIO(train[0]["image_png"]))
+depth = Image.open(BytesIO(train[0]["depth_png"]))
+mask = Image.open(BytesIO(train[0]["instance_mask_png"]))
+```
+
+## 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.