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.gitattributes

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 *.7z filter=lfs diff=lfs merge=lfs -text
 *.arrow filter=lfs diff=lfs merge=lfs -text
+*.avro filter=lfs diff=lfs merge=lfs -text
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README.md

@@ -1,3 +1,212 @@
----
-license: mit
----
+---
+license: cc-by-4.0
+pretty_name: "RPX: Robot Perception X"
+task_categories:
+- image-segmentation
+- depth-estimation
+- object-detection
+- visual-question-answering
+language:
+- en
+tags:
+- robotics
+- embodied-ai
+- rgb-d
+- benchmark
+- perception
+- manipulation
+- stereo
+size_categories:
+- 100B<n<1T
+configs:
+- config_name: multi_object
+  description: "MOS scenes (3 phases each), tertile-cut by Effort-Stratified Difficulty."
+  data_files:
+  - split: "easy"
+    path: "splits/easy.txt"
+  - split: "medium"
+    path: "splits/medium.txt"
+  - split: "hard"
+    path: "splits/hard.txt"
+- config_name: single_object
+  description: "SOS scenes (one 360° collection per object); no difficulty split."
+---
+
+# RPX: Robot Perception X
+
+A real-world RGB-D benchmark for evaluating robot perception under
+embodied deployment conditions.
+
+* Code: https://github.com/IRVLUTD/RPX
+
+![RPX teaser](assets/rpx_teaser.png)
+
+[Watch the RPX teaser video](assets/rpx-jumbotron.webm)
+
+## Dataset at a glance
+
+| | |
+|---|---|
+| Multi-object scenes (MOS) | **100** (`scene001` to `scene100`, 3 phases each: clutter / interaction / clean) |
+| Single-object scenes (SOS) | **70 selected objects** (one 360 collection per object) |
+| Frame manifest rows | **110,000** (75,000 MOS + 35,000 selected SOS) |
+| MOS mask-object rows | **2,100** local mask IDs mapped to global object IDs |
+
+Scene renames are documented in `manifest/scene_name_mapping_v1.csv`,
+mapping original scene names to `scene001` through `scene100`.
+
+## Modality inventory
+
+The table below describes this cleaned release. `cam_pose_icp` is not included in this cleaned release.
+Use `manifest/frames_v1.parquet` and the identity manifests under `manifest/`
+as the source of truth.
+
+| modality | files | bytes |
+|---|---:|---:|
+| `cam_pose` | 110,000 | 163.3 MB |
+| `depth` | 110,000 | 16.9 GB |
+| `fisheye` | 220,000 | 63.4 GB |
+| `rgb` | 110,000 | 41.0 GB |
+| `masks` | 110,000 | 341.7 MB |
+
+## Quick start
+
+```bash
+pip install "rpx-benchmark[hub]"
+hf auth login
+```
+
+```python
+from rpx_benchmark.dataset_hub import download_for_task
+
+# Pull just RGB + masks for the Easy difficulty tier — never the whole repo.
+res = download_for_task(task="segmentation", split="easy",
+                          repo_id="IRVLUTD/RPX")
+print(res.local_dir, res.matched_scenes)
+```
+
+```bash
+# Or from the CLI:
+python -m rpx_benchmark.dataset_hub.cli download \
+    --task segmentation --split easy \
+    --repo-id IRVLUTD/RPX
+```
+
+A subsequent call for a different task on the same split (e.g.
+`relative_pose`) reuses the cached RGB tars and only fetches the new
+modality (`cam_pose`) as the delta.
+
+## Repo layout
+
+```
+IRVLUTD/RPX/
+├── manifest/
+│   ├── frames_v1.parquet                 # per-frame metadata
+│   ├── scene_name_mapping_v1.csv         # original scene names to scene001..scene100
+│   ├── selected_sos_objects_v1.csv       # selected 70-object SOS catalog
+│   ├── object_catalog_v1.json            # SOS object/global-ID catalog
+│   ├── mos_raw_mask_object_map_v1.csv    # MOS local mask IDs from sam2 metadata
+│   ├── mos_mask_object_map_v1.csv        # MOS local mask IDs joined to SOS global IDs
+│   ├── mos_mask_object_map_v1.parquet    # parquet copy of the MOS map
+│   └── current.json                      # default version per label modality
+├── splits/
+│   ├── scene_splits.json
+│   ├── easy.txt  medium.txt  hard.txt
+├── scenes/<scene_id>/<phase>/                     # MOS
+│   ├── rgb.tar  depth.tar  fisheye.tar
+│   └── labels/{cam_pose,masks,masks_aux,sam2_meta}/v1.tar
+├── objects/<object_id>/0/                         # SOS
+│   └── (same modality structure)
+├── objects_meta/                                  # questionnaire dedup
+│   ├── _index.json
+│   └── <object_id>/questionnaire.json
+└── README.md   ←  this file
+```
+
+## Object identity manifests
+
+SOS objects use dataset-wide IDs from `manifest/selected_sos_objects_v1.csv`
+and `manifest/object_catalog_v1.json`.
+
+| field | meaning |
+|---|---|
+| `global_object_id` | New integer ID, 1 to 70 |
+| `source_catalog_id` | Original catalog/PDF ID, kept as a string such as `88.2` |
+| `object_id` | Actual folder name, such as `mug.2` |
+| `questionnaire_path` | Linked questionnaire under `objects_meta/<object_id>/questionnaire.json` |
+
+MOS masks use local IDs. A `local_mask_id` is only meaningful within one
+`scene_id + phase`; it is not a global object ID. The raw source is
+`scenes/<scene_id>/<phase_index>/labels/sam2_meta/v1.tar:sam2/mask_to_object.json`.
+
+Use `manifest/mos_mask_object_map_v1.csv` or
+`manifest/mos_mask_object_map_v1.parquet` to join MOS masks to SOS objects:
+
+```csv
+scene_id,phase,local_mask_id,object_id,global_object_id,source_catalog_id,object_name
+scene001,phase0,2,boot.2,11,18.2,boot
+```
+
+That row means `scene001/0` mask ID `2` is `boot.2`, whose global object ID
+is `11`, with questionnaire
+`objects_meta/boot.2/questionnaire.json` and SOS template `objects/boot.2/`.
+
+## Tasks
+
+### Multi-object (use a difficulty split)
+
+| recipe | inputs → labels |
+|---|---|
+| `monocular_depth` | ['rgb'] → ['depth'] |
+| `rgbd_segmentation` | ['depth', 'rgb'] → ['masks'] |
+| `segmentation` | ['rgb'] → ['masks'] |
+| `relative_pose` | ['rgb'] → ['cam_pose'] |
+| `rgbd_relative_pose` | ['depth', 'rgb'] → ['cam_pose'] |
+| `stereo_depth` | ['fisheye'] → ['depth'] |
+| `object_tracking` | ['rgb'] → ['masks'] |
+| `vqa` | ['rgb'] → ['questionnaire', 'vqa'] |
+
+### Single-object (no split — these are object templates)
+
+| recipe | inputs → labels |
+|---|---|
+| `object_templates` | ['rgb'] → ['masks'] |
+| `object_templates_rgbd` | ['depth', 'rgb'] → ['masks'] |
+| `object_pose_library` | ['depth', 'rgb'] → ['cam_pose', 'masks'] |
+
+## Label versioning
+
+Labels live at `labels/<name>/v<N>.tar`. Newer versions land at new
+paths; old versions stay reachable for reproducibility.
+
+| modality | current version |
+|---|---|
+| `masks` | `v1` |
+| `masks_aux` | `v1` |
+| `sam2_meta` | `v1` |
+| `cam_pose` | `v1` |
+
+To pin to a specific version:
+
+```python
+download_for_task(
+    task="relative_pose", split="easy", repo_id="itaykadosh/RPX",
+    label_versions={"cam_pose": "v1"},   # don't auto-upgrade to v2
+)
+```
+
+## Citation
+
+```bibtex
+@misc{rpx2026,
+    title  = {RPX: Robot Perception X — A real-world RGB-D benchmark for
+              embodied perception},
+    author = {IRVL UT Dallas},
+    year   = 2026,
+    url    = {https://huggingface.co/datasets/itaykadosh/RPX},
+}
+```
+
+## License
+
+Released under the **cc-by-4.0** license.

manifest/current.json

@@ -0,0 +1,60 @@
+{
+  "label_versions": {
+    "masks": "v1",
+    "masks_aux": "v1",
+    "sam2_meta": "v1",
+    "cam_pose": "v1"
+  },
+  "schema_version": "v1",
+  "manifests": {
+    "frames": "manifest/frames_v1.parquet",
+    "scene_name_mapping": "manifest/scene_name_mapping_v1.csv",
+    "selected_sos_objects": "manifest/selected_sos_objects_v1.csv",
+    "object_catalog": "manifest/object_catalog_v1.json",
+    "mos_raw_mask_object_map": "manifest/mos_raw_mask_object_map_v1.csv",
+    "mos_mask_object_map_csv": "manifest/mos_mask_object_map_v1.csv",
+    "mos_mask_object_map_parquet": "manifest/mos_mask_object_map_v1.parquet",
+    "mos_mask_object_map": "manifest/mos_mask_object_map_v1.parquet"
+  },
+  "sos": {
+    "schema_version": "v1",
+    "selected_object_count": 70,
+    "objects_dir": "objects",
+    "objects_meta_dir": "objects_meta",
+    "selected_objects": "manifest/selected_sos_objects_v1.csv",
+    "object_catalog": "manifest/object_catalog_v1.json",
+    "objects_meta_index": "objects_meta/_index.json"
+  },
+  "mos": {
+    "schema_version": "v1",
+    "scene_count": 100,
+    "phase_count": 300,
+    "mask_object_row_count": 2100,
+    "local_mask_id_scope": "scene_id + phase",
+    "raw_mask_object_map": "manifest/mos_raw_mask_object_map_v1.csv",
+    "mask_object_map_csv": "manifest/mos_mask_object_map_v1.csv",
+    "mask_object_map_parquet": "manifest/mos_mask_object_map_v1.parquet",
+    "raw_source": "scenes/<scene_id>/<phase_index>/labels/sam2_meta/v1.tar:sam2/mask_to_object.json",
+    "phase_values": [
+      "phase0",
+      "phase1",
+      "phase2"
+    ],
+    "phase_directory_values": [
+      "0",
+      "1",
+      "2"
+    ],
+    "joins_to_sos": {
+      "selected_objects": "manifest/selected_sos_objects_v1.csv",
+      "object_catalog": "manifest/object_catalog_v1.json",
+      "objects_meta_index": "objects_meta/_index.json"
+    }
+  },
+  "metadata_versions": {
+    "scene_name_mapping": "v1",
+    "selected_sos_objects": "v1",
+    "object_catalog": "v1",
+    "mos_mask_object_map": "v1"
+  }
+}

manifest/object_catalog_v1.json

@@ -0,0 +1,1003 @@
+{
+  "schema_version": "v1",
+  "source": {
+    "catalog_pdf": "test_set_catalog.pdf",
+    "selection_count": 70
+  },
+  "id_policy": {
+    "source_catalog_id": "Original catalog ID from the PDF, stored as a string. Decimal suffix denotes selected instance and is not used as a numeric code ID.",
+    "object_name": "Object name exactly as parsed from the PDF.",
+    "object_id": "Actual SOS folder name in objects/ and objects_meta/.",
+    "global_object_id": "1-based contiguous integer assigned in PDF order for the selected 70-object subset.",
+    "sos_data_path": "Relative path to the selected SOS object data directory.",
+    "questionnaire_path": "Relative path to the selected object questionnaire JSON.",
+    "class_name": "Object class name used for schema compatibility; currently equal to object_name.",
+    "sos_path": "Alias for sos_data_path, kept for schema compatibility."
+  },
+  "objects": [
+    {
+      "global_object_id": 1,
+      "source_catalog_id": "1",
+      "source_category_id": "1",
+      "source_instance_id": null,
+      "object_name": "air_duster_can",
+      "object_id": "air_duster_can",
+      "sos_data_path": "objects/air_duster_can/",
+      "questionnaire_path": "objects_meta/air_duster_can/questionnaire.json",
+      "class_name": "air_duster_can",
+      "sos_path": "objects/air_duster_can/"
+    },
+    {
+      "global_object_id": 2,
+      "source_catalog_id": "3",
+      "source_category_id": "3",
+      "source_instance_id": null,
+      "object_name": "alarm_clock",
+      "object_id": "alarm_clock",
+      "sos_data_path": "objects/alarm_clock/",
+      "questionnaire_path": "objects_meta/alarm_clock/questionnaire.json",
+      "class_name": "alarm_clock",
+      "sos_path": "objects/alarm_clock/"
+    },
+    {
+      "global_object_id": 3,
+      "source_catalog_id": "5",
+      "source_category_id": "5",
+      "source_instance_id": null,
+      "object_name": "apple",
+      "object_id": "apple",
+      "sos_data_path": "objects/apple/",
+      "questionnaire_path": "objects_meta/apple/questionnaire.json",
+      "class_name": "apple",
+      "sos_path": "objects/apple/"
+    },
+    {
+      "global_object_id": 4,
+      "source_catalog_id": "7.1",
+      "source_category_id": "7",
+      "source_instance_id": "1",
+      "object_name": "baking_tray",
+      "object_id": "baking_tray.1",
+      "sos_data_path": "objects/baking_tray.1/",
+      "questionnaire_path": "objects_meta/baking_tray.1/questionnaire.json",
+      "class_name": "baking_tray",
+      "sos_path": "objects/baking_tray.1/"
+    },
+    {
+      "global_object_id": 5,
+      "source_catalog_id": "9",
+      "source_category_id": "9",
+      "source_instance_id": null,
+      "object_name": "banana",
+      "object_id": "banana",
+      "sos_data_path": "objects/banana/",
+      "questionnaire_path": "objects_meta/banana/questionnaire.json",
+      "class_name": "banana",
+      "sos_path": "objects/banana/"
+    },
+    {
+      "global_object_id": 6,
+      "source_catalog_id": "10",
+      "source_category_id": "10",
+      "source_instance_id": null,
+      "object_name": "baseball_ball",
+      "object_id": "baseball_ball",
+      "sos_data_path": "objects/baseball_ball/",
+      "questionnaire_path": "objects_meta/baseball_ball/questionnaire.json",
+      "class_name": "baseball_ball",
+      "sos_path": "objects/baseball_ball/"
+    },
+    {
+      "global_object_id": 7,
+      "source_catalog_id": "11.1",
+      "source_category_id": "11",
+      "source_instance_id": "1",
+      "object_name": "basting_brush",
+      "object_id": "basting_brush.1",
+      "sos_data_path": "objects/basting_brush.1/",
+      "questionnaire_path": "objects_meta/basting_brush.1/questionnaire.json",
+      "class_name": "basting_brush",
+      "sos_path": "objects/basting_brush.1/"
+    },
+    {
+      "global_object_id": 8,
+      "source_catalog_id": "13.2",
+      "source_category_id": "13",
+      "source_instance_id": "2",
+      "object_name": "beanie",
+      "object_id": "beanie.2",
+      "sos_data_path": "objects/beanie.2/",
+      "questionnaire_path": "objects_meta/beanie.2/questionnaire.json",
+      "class_name": "beanie",
+      "sos_path": "objects/beanie.2/"
+    },
+    {
+      "global_object_id": 9,
+      "source_catalog_id": "14.1",
+      "source_category_id": "14",
+      "source_instance_id": "1",
+      "object_name": "bear",
+      "object_id": "bear.1",
+      "sos_data_path": "objects/bear.1/",
+      "questionnaire_path": "objects_meta/bear.1/questionnaire.json",
+      "class_name": "bear",
+      "sos_path": "objects/bear.1/"
+    },
+    {
+      "global_object_id": 10,
+      "source_catalog_id": "17.3",
+      "source_category_id": "17",
+      "source_instance_id": "3",
+      "object_name": "book",
+      "object_id": "book.3",
+      "sos_data_path": "objects/book.3/",
+      "questionnaire_path": "objects_meta/book.3/questionnaire.json",
+      "class_name": "book",
+      "sos_path": "objects/book.3/"
+    },
+    {
+      "global_object_id": 11,
+      "source_catalog_id": "18.2",
+      "source_category_id": "18",
+      "source_instance_id": "2",
+      "object_name": "boot",
+      "object_id": "boot.2",
+      "sos_data_path": "objects/boot.2/",
+      "questionnaire_path": "objects_meta/boot.2/questionnaire.json",
+      "class_name": "boot",
+      "sos_path": "objects/boot.2/"
+    },
+    {
+      "global_object_id": 12,
+      "source_catalog_id": "20.1",
+      "source_category_id": "20",
+      "source_instance_id": "1",
+      "object_name": "bowl",
+      "object_id": "bowl.1",
+      "sos_data_path": "objects/bowl.1/",
+      "questionnaire_path": "objects_meta/bowl.1/questionnaire.json",
+      "class_name": "bowl",
+      "sos_path": "objects/bowl.1/"
+    },
+    {
+      "global_object_id": 13,
+      "source_catalog_id": "23",
+      "source_category_id": "23",
+      "source_instance_id": null,
+      "object_name": "cable",
+      "object_id": "cable",
+      "sos_data_path": "objects/cable/",
+      "questionnaire_path": "objects_meta/cable/questionnaire.json",
+      "class_name": "cable",
+      "sos_path": "objects/cable/"
+    },
+    {
+      "global_object_id": 14,
+      "source_catalog_id": "25.1",
+      "source_category_id": "25",
+      "source_instance_id": "1",
+      "object_name": "candy_bar",
+      "object_id": "candy_bar.1",
+      "sos_data_path": "objects/candy_bar.1/",
+      "questionnaire_path": "objects_meta/candy_bar.1/questionnaire.json",
+      "class_name": "candy_bar",
+      "sos_path": "objects/candy_bar.1/"
+    },
+    {
+      "global_object_id": 15,
+      "source_catalog_id": "34",
+      "source_category_id": "34",
+      "source_instance_id": null,
+      "object_name": "cleaning_brush",
+      "object_id": "cleaning_brush",
+      "sos_data_path": "objects/cleaning_brush/",
+      "questionnaire_path": "objects_meta/cleaning_brush/questionnaire.json",
+      "class_name": "cleaning_brush",
+      "sos_path": "objects/cleaning_brush/"
+    },
+    {
+      "global_object_id": 16,
+      "source_catalog_id": "36",
+      "source_category_id": "36",
+      "source_instance_id": null,
+      "object_name": "coffee_bottle",
+      "object_id": "coffee_bottle",
+      "sos_data_path": "objects/coffee_bottle/",
+      "questionnaire_path": "objects_meta/coffee_bottle/questionnaire.json",
+      "class_name": "coffee_bottle",
+      "sos_path": "objects/coffee_bottle/"
+    },
+    {
+      "global_object_id": 17,
+      "source_catalog_id": "37.1",
+      "source_category_id": "37",
+      "source_instance_id": "1",
+      "object_name": "coffee_can",
+      "object_id": "coffee_can.1",
+      "sos_data_path": "objects/coffee_can.1/",
+      "questionnaire_path": "objects_meta/coffee_can.1/questionnaire.json",
+      "class_name": "coffee_can",
+      "sos_path": "objects/coffee_can.1/"
+    },
+    {
+      "global_object_id": 18,
+      "source_catalog_id": "38",
+      "source_category_id": "38",
+      "source_instance_id": null,
+      "object_name": "cracker_box",
+      "object_id": "cracker_box",
+      "sos_data_path": "objects/cracker_box/",
+      "questionnaire_path": "objects_meta/cracker_box/questionnaire.json",
+      "class_name": "cracker_box",
+      "sos_path": "objects/cracker_box/"
+    },
+    {
+      "global_object_id": 19,
+      "source_catalog_id": "40.1",
+      "source_category_id": "40",
+      "source_instance_id": "1",
+      "object_name": "cup",
+      "object_id": "cup.1",
+      "sos_data_path": "objects/cup.1/",
+      "questionnaire_path": "objects_meta/cup.1/questionnaire.json",
+      "class_name": "cup",
+      "sos_path": "objects/cup.1/"
+    },
+    {
+      "global_object_id": 20,
+      "source_catalog_id": "43.1",
+      "source_category_id": "43",
+      "source_instance_id": "1",
+      "object_name": "doll",
+      "object_id": "doll.1",
+      "sos_data_path": "objects/doll.1/",
+      "questionnaire_path": "objects_meta/doll.1/questionnaire.json",
+      "class_name": "doll",
+      "sos_path": "objects/doll.1/"
+    },
+    {
+      "global_object_id": 21,
+      "source_catalog_id": "49.1",
+      "source_category_id": "49",
+      "source_instance_id": "1",
+      "object_name": "fry_pan",
+      "object_id": "fry_pan.1",
+      "sos_data_path": "objects/fry_pan.1/",
+      "questionnaire_path": "objects_meta/fry_pan.1/questionnaire.json",
+      "class_name": "fry_pan",
+      "sos_path": "objects/fry_pan.1/"
+    },
+    {
+      "global_object_id": 22,
+      "source_catalog_id": "50",
+      "source_category_id": "50",
+      "source_instance_id": null,
+      "object_name": "food_bag",
+      "object_id": "food_bag",
+      "sos_data_path": "objects/food_bag/",
+      "questionnaire_path": "objects_meta/food_bag/questionnaire.json",
+      "class_name": "food_bag",
+      "sos_path": "objects/food_bag/"
+    },
+    {
+      "global_object_id": 23,
+      "source_catalog_id": "55",
+      "source_category_id": "55",
+      "source_instance_id": null,
+      "object_name": "game_controller",
+      "object_id": "game_controller",
+      "sos_data_path": "objects/game_controller/",
+      "questionnaire_path": "objects_meta/game_controller/questionnaire.json",
+      "class_name": "game_controller",
+      "sos_path": "objects/game_controller/"
+    },
+    {
+      "global_object_id": 24,
+      "source_catalog_id": "57.2",
+      "source_category_id": "57",
+      "source_instance_id": "2",
+      "object_name": "glove",
+      "object_id": "glove.2",
+      "sos_data_path": "objects/glove.2/",
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+    "apple": 3,
+    "baking_tray.1": 4,
+    "banana": 5,
+    "baseball_ball": 6,
+    "basting_brush.1": 7,
+    "beanie.2": 8,
+    "bear.1": 9,
+    "book.3": 10,
+    "boot.2": 11,
+    "bowl.1": 12,
+    "cable": 13,
+    "candy_bar.1": 14,
+    "cleaning_brush": 15,
+    "coffee_bottle": 16,
+    "coffee_can.1": 17,
+    "cracker_box": 18,
+    "cup.1": 19,
+    "doll.1": 20,
+    "fry_pan.1": 21,
+    "food_bag": 22,
+    "game_controller": 23,
+    "glove.2": 24,
+    "glue_bottle.1": 25,
+    "hairbrush": 26,
+    "hammer.2": 27,
+    "handy_pot": 28,
+    "hat.1": 29,
+    "headphone": 30,
+    "helmet": 31,
+    "instant_noodle_packet": 32,
+    "jar": 33,
+    "jello_box.1": 34,
+    "juice_pouch.2": 35,
+    "kettle": 36,
+    "knife.1": 37,
+    "ladle": 38,
+    "lion.2": 39,
+    "marker.5": 40,
+    "meat_can": 41,
+    "milk_box.1": 42,
+    "milk_jug": 43,
+    "mouse.3": 44,
+    "mug.2": 45,
+    "mustard_bottle.3": 46,
+    "pear": 47,
+    "peeler.2": 48,
+    "power_drill": 49,
+    "pringles_can.2": 50,
+    "pump_bottle.2": 51,
+    "remote_controller": 52,
+    "root_beer_bottle": 53,
+    "scissors.1": 54,
+    "shampoo_bottle": 55,
+    "shoe.1": 56,
+    "soda_can.3": 57,
+    "soft_scrub_cleanser_bottle": 58,
+    "soup_can.1": 59,
+    "spatula.2": 60,
+    "sponge": 61,
+    "spray_bottle.2": 62,
+    "t-handle.2": 63,
+    "tape_measure": 64,
+    "teapot": 65,
+    "tong": 66,
+    "toothpaste": 67,
+    "towel.2": 68,
+    "umbrella": 69,
+    "water_bottle.2": 70
+  },
+  "global_object_id_to_object_id": {
+    "1": "air_duster_can",
+    "2": "alarm_clock",
+    "3": "apple",
+    "4": "baking_tray.1",
+    "5": "banana",
+    "6": "baseball_ball",
+    "7": "basting_brush.1",
+    "8": "beanie.2",
+    "9": "bear.1",
+    "10": "book.3",
+    "11": "boot.2",
+    "12": "bowl.1",
+    "13": "cable",
+    "14": "candy_bar.1",
+    "15": "cleaning_brush",
+    "16": "coffee_bottle",
+    "17": "coffee_can.1",
+    "18": "cracker_box",
+    "19": "cup.1",
+    "20": "doll.1",
+    "21": "fry_pan.1",
+    "22": "food_bag",
+    "23": "game_controller",
+    "24": "glove.2",
+    "25": "glue_bottle.1",
+    "26": "hairbrush",
+    "27": "hammer.2",
+    "28": "handy_pot",
+    "29": "hat.1",
+    "30": "headphone",
+    "31": "helmet",
+    "32": "instant_noodle_packet",
+    "33": "jar",
+    "34": "jello_box.1",
+    "35": "juice_pouch.2",
+    "36": "kettle",
+    "37": "knife.1",
+    "38": "ladle",
+    "39": "lion.2",
+    "40": "marker.5",
+    "41": "meat_can",
+    "42": "milk_box.1",
+    "43": "milk_jug",
+    "44": "mouse.3",
+    "45": "mug.2",
+    "46": "mustard_bottle.3",
+    "47": "pear",
+    "48": "peeler.2",
+    "49": "power_drill",
+    "50": "pringles_can.2",
+    "51": "pump_bottle.2",
+    "52": "remote_controller",
+    "53": "root_beer_bottle",
+    "54": "scissors.1",
+    "55": "shampoo_bottle",
+    "56": "shoe.1",
+    "57": "soda_can.3",
+    "58": "soft_scrub_cleanser_bottle",
+    "59": "soup_can.1",
+    "60": "spatula.2",
+    "61": "sponge",
+    "62": "spray_bottle.2",
+    "63": "t-handle.2",
+    "64": "tape_measure",
+    "65": "teapot",
+    "66": "tong",
+    "67": "toothpaste",
+    "68": "towel.2",
+    "69": "umbrella",
+    "70": "water_bottle.2"
+  }
+}

manifest/scene_name_mapping_v1.csv

@@ -0,0 +1,101 @@
+scene_number,old_scene_name,new_scene_name
+1,scene1.library.fountain,scene001
+2,scene2.library.fountain,scene002
+3,scene3.library.fountain,scene003
+4,scene4.library.fountain,scene004
+5,scene5.library.fountain,scene005
+6,scene6.ecsn.4f.sofa,scene006
+7,scene7.ecsn.4f.sofa,scene007
+8,scene8.ecsn.4f.sofa,scene008
+9,scene9.ecsn.4f.sofa,scene009
+10,scene10.ecsn.4f.sofa,scene010
+11,scene11.ecss.4f.sofa,scene011
+12,scene12.ecss.4f.sofa,scene012
+13,scene13.ecss.4f.sofa,scene013
+14,scene14.ecss.4f.sofa,scene014
+15,scene15.ecss.4f.sofa,scene015
+16,scene16.SU.CHECKERBOARD,scene016
+17,scene17.SU.CHECKERBOARD,scene017
+18,scene18.su.CHECKERBOARD,scene018
+19,scene19.su.CHECKERBOARD,scene019
+20,scene20.su.CHECKERBOARD,scene020
+21,scene21.jo.4f,scene021
+22,scene22.jo.4f,scene022
+23,scene23.jo.4f,scene023
+24,scene24.jo.4f,scene024
+25,scene25.jo.4f,scene025
+26,scene26.gaming2.JUMBOTRONSTAGE,scene026
+27,scene27.gaming2.JUMBOTRONSTAGE,scene027
+28,scene28.gaming2.JUMBOTRONSTAGE,scene028
+29,scene29.gaming2.JUMBOTRONSTAGE,scene029
+30,scene30.gaming2.JUMBOTRONSTAGE,scene030
+31,scene31.ecss.3f.sofaNchairs,scene031
+32,scene32.ecss.3f.sofaNchairs,scene032
+33,scene33.ecss.3f.sofaNchairs,scene033
+34,scene34.ecss.3f.sofaNchairs,scene034
+35,scene35.ecss.3f.sofaNchairs,scene035
+36,scene36.jo.4f,scene036
+37,scene37.jo.4f,scene037
+38,scene38.jo.4f,scene038
+39,scene39.jo.4f,scene039
+40,scene40.jo.4f,scene040
+41,scene41.gh.out,scene041
+42,scene42.gh.out,scene042
+43,scene43.gh.out,scene043
+44,scene44.gh.out,scene044
+45,scene45.gh.out,scene045
+46,scene46.ecss.out.stairs,scene046
+47,scene47.ecss.out.stairs,scene047
+48,scene48.ecss.out.stairs,scene048
+49,scene49.ecss.out.stairs,scene049
+50,scene50.ecss.out.stairs,scene050
+51,scene51.TENNISCOURTS.Ground,scene051
+52,scene52.TENNISCOURTS.Ground,scene052
+53,scene53.TENNISCOURTS.Ground,scene053
+54,scene54.TENNISCOURTS.Ground,scene054
+55,scene55.TENNISCOURTS.Ground,scene055
+56,scene56.rec.in,scene056
+57,scene57.rec.in,scene057
+58,scene58.rec.in,scene058
+59,scene59.rec.in,scene059
+60,scene60.rec.in,scene060
+61,scene61.ecsw.axxess-atrium,scene061
+62,scene62.ecsw.axxess-atrium,scene062
+63,scene63.ecsw.axxess-atrium,scene063
+64,scene64.ecsw.axxess-atrium,scene064
+65,scene65.ecsw.axxess-atrium,scene065
+66,scene66.ecsw.3f.dept,scene066
+67,scene67.ecsw.3f.dept,scene067
+68,scene68.ecsw.3f.dept,scene068
+69,scene69.ecsw.3f.dept,scene069
+70,scene70.ecsw.3f.dept,scene070
+71,scene71.ecsw.atriumStairs,scene071
+72,scene72.ecsw.atriumStairs,scene072
+73,scene73.ecsw.atriumStairs,scene073
+74,scene74.ecsw.atriumStairs,scene074
+75,scene75.ecsw.atriumStairs,scene075
+76,scene76.gaming2,scene076
+77,scene77.gaming2,scene077
+78,scene78.gaming2,scene078
+79,scene79.gaming2,scene079
+80,scene80.gaming2,scene080
+81,scene81.jsom.garden.pot,scene081
+82,scene82.jsom.garden.pot,scene082
+83,scene83.jsom.garden.pot,scene083
+84,scene84.jsom.garden.pot,scene084
+85,scene85.jsom.garden.pot,scene085
+86,scene86.jsom.atrium,scene086
+87,scene87.jsom.atrium,scene087
+88,scene88.jsom.atrium,scene088
+89,scene89.jsom.atrium,scene089
+90,scene90.jsom.atrium,scene090
+91,scene91.ad.out,scene091
+92,scene92.ad.out,scene092
+93,scene93.ad.out,scene093
+94,scene94.ad.out,scene094
+95,scene95.ad.out,scene095
+96,scene96.jsom.rocks,scene096
+97,scene97.jsom.rocks,scene097
+98,scene98.jsom.rocks,scene098
+99,scene99.jsom.rocks,scene099
+100,scene100.jsom.rocks,scene100

manifest/selected_sos_objects_v1.csv

@@ -0,0 +1,71 @@
+source_catalog_id,object_name,object_id,global_object_id,sos_data_path,questionnaire_path
+1,air_duster_can,air_duster_can,1,objects/air_duster_can/,objects_meta/air_duster_can/questionnaire.json
+3,alarm_clock,alarm_clock,2,objects/alarm_clock/,objects_meta/alarm_clock/questionnaire.json
+5,apple,apple,3,objects/apple/,objects_meta/apple/questionnaire.json
+7.1,baking_tray,baking_tray.1,4,objects/baking_tray.1/,objects_meta/baking_tray.1/questionnaire.json
+9,banana,banana,5,objects/banana/,objects_meta/banana/questionnaire.json
+10,baseball_ball,baseball_ball,6,objects/baseball_ball/,objects_meta/baseball_ball/questionnaire.json
+11.1,basting_brush,basting_brush.1,7,objects/basting_brush.1/,objects_meta/basting_brush.1/questionnaire.json
+13.2,beanie,beanie.2,8,objects/beanie.2/,objects_meta/beanie.2/questionnaire.json
+14.1,bear,bear.1,9,objects/bear.1/,objects_meta/bear.1/questionnaire.json
+17.3,book,book.3,10,objects/book.3/,objects_meta/book.3/questionnaire.json
+18.2,boot,boot.2,11,objects/boot.2/,objects_meta/boot.2/questionnaire.json
+20.1,bowl,bowl.1,12,objects/bowl.1/,objects_meta/bowl.1/questionnaire.json
+23,cable,cable,13,objects/cable/,objects_meta/cable/questionnaire.json
+25.1,candy_bar,candy_bar.1,14,objects/candy_bar.1/,objects_meta/candy_bar.1/questionnaire.json
+34,cleaning_brush,cleaning_brush,15,objects/cleaning_brush/,objects_meta/cleaning_brush/questionnaire.json
+36,coffee_bottle,coffee_bottle,16,objects/coffee_bottle/,objects_meta/coffee_bottle/questionnaire.json
+37.1,coffee_can,coffee_can.1,17,objects/coffee_can.1/,objects_meta/coffee_can.1/questionnaire.json
+38,cracker_box,cracker_box,18,objects/cracker_box/,objects_meta/cracker_box/questionnaire.json
+40.1,cup,cup.1,19,objects/cup.1/,objects_meta/cup.1/questionnaire.json
+43.1,doll,doll.1,20,objects/doll.1/,objects_meta/doll.1/questionnaire.json
+49.1,fry_pan,fry_pan.1,21,objects/fry_pan.1/,objects_meta/fry_pan.1/questionnaire.json
+50,food_bag,food_bag,22,objects/food_bag/,objects_meta/food_bag/questionnaire.json
+55,game_controller,game_controller,23,objects/game_controller/,objects_meta/game_controller/questionnaire.json
+57.2,glove,glove.2,24,objects/glove.2/,objects_meta/glove.2/questionnaire.json
+58.1,glue_bottle,glue_bottle.1,25,objects/glue_bottle.1/,objects_meta/glue_bottle.1/questionnaire.json
+62,hair_brush,hairbrush,26,objects/hairbrush/,objects_meta/hairbrush/questionnaire.json
+63.2,hammer,hammer.2,27,objects/hammer.2/,objects_meta/hammer.2/questionnaire.json
+65,handy_pot,handy_pot,28,objects/handy_pot/,objects_meta/handy_pot/questionnaire.json
+66.1,hat,hat.1,29,objects/hat.1/,objects_meta/hat.1/questionnaire.json
+67,headphone,headphone,30,objects/headphone/,objects_meta/headphone/questionnaire.json
+68,helmet,helmet,31,objects/helmet/,objects_meta/helmet/questionnaire.json
+70,instant_noodle_packet,instant_noodle_packet,32,objects/instant_noodle_packet/,objects_meta/instant_noodle_packet/questionnaire.json
+71,jar,jar,33,objects/jar/,objects_meta/jar/questionnaire.json
+72.1,jello_box,jello_box.1,34,objects/jello_box.1/,objects_meta/jello_box.1/questionnaire.json
+73.2,juice_pouch,juice_pouch.2,35,objects/juice_pouch.2/,objects_meta/juice_pouch.2/questionnaire.json
+74,kettle,kettle,36,objects/kettle/,objects_meta/kettle/questionnaire.json
+77.1,knife,knife.1,37,objects/knife.1/,objects_meta/knife.1/questionnaire.json
+78,ladle,ladle,38,objects/ladle/,objects_meta/ladle/questionnaire.json
+82.2,lion,lion.2,39,objects/lion.2/,objects_meta/lion.2/questionnaire.json
+83.5,marker,marker.5,40,objects/marker.5/,objects_meta/marker.5/questionnaire.json
+84,meat_can,meat_can,41,objects/meat_can/,objects_meta/meat_can/questionnaire.json
+85.1,milk_box,milk_box.1,42,objects/milk_box.1/,objects_meta/milk_box.1/questionnaire.json
+86,milk_jug,milk_jug,43,objects/milk_jug/,objects_meta/milk_jug/questionnaire.json
+87.3,mouse,mouse.3,44,objects/mouse.3/,objects_meta/mouse.3/questionnaire.json
+88.2,mug,mug.2,45,objects/mug.2/,objects_meta/mug.2/questionnaire.json
+89.3,mustard_bottle,mustard_bottle.3,46,objects/mustard_bottle.3/,objects_meta/mustard_bottle.3/questionnaire.json
+95,pear,pear,47,objects/pear/,objects_meta/pear/questionnaire.json
+96.2,peeler,peeler.2,48,objects/peeler.2/,objects_meta/peeler.2/questionnaire.json
+102,power_drill,power_drill,49,objects/power_drill/,objects_meta/power_drill/questionnaire.json
+103.2,pringles_can,pringles_can.2,50,objects/pringles_can.2/,objects_meta/pringles_can.2/questionnaire.json
+105.2,pump_bottle,pump_bottle.2,51,objects/pump_bottle.2/,objects_meta/pump_bottle.2/questionnaire.json
+107,remote_controller,remote_controller,52,objects/remote_controller/,objects_meta/remote_controller/questionnaire.json
+109,root_beer_bottle,root_beer_bottle,53,objects/root_beer_bottle/,objects_meta/root_beer_bottle/questionnaire.json
+113.1,scissors,scissors.1,54,objects/scissors.1/,objects_meta/scissors.1/questionnaire.json
+114,shampoo_bottle,shampoo_bottle,55,objects/shampoo_bottle/,objects_meta/shampoo_bottle/questionnaire.json
+117.1,shoe,shoe.1,56,objects/shoe.1/,objects_meta/shoe.1/questionnaire.json
+120.3,soda_can,soda_can.3,57,objects/soda_can.3/,objects_meta/soda_can.3/questionnaire.json
+121,soft_scrub_cleanser_bottle,soft_scrub_cleanser_bottle,58,objects/soft_scrub_cleanser_bottle/,objects_meta/soft_scrub_cleanser_bottle/questionnaire.json
+122.1,soup_can,soup_can.1,59,objects/soup_can.1/,objects_meta/soup_can.1/questionnaire.json
+124.2,spatula,spatula.2,60,objects/spatula.2/,objects_meta/spatula.2/questionnaire.json
+125,sponge,sponge,61,objects/sponge/,objects_meta/sponge/questionnaire.json
+127.2,spray_bottle,spray_bottle.2,62,objects/spray_bottle.2/,objects_meta/spray_bottle.2/questionnaire.json
+133.2,t-handle,t-handle.2,63,objects/t-handle.2/,objects_meta/t-handle.2/questionnaire.json
+135,tape_measure,tape_measure,64,objects/tape_measure/,objects_meta/tape_measure/questionnaire.json
+137,teapot,teapot,65,objects/teapot/,objects_meta/teapot/questionnaire.json
+141,tong,tong,66,objects/tong/,objects_meta/tong/questionnaire.json
+142,toothpaste,toothpaste,67,objects/toothpaste/,objects_meta/toothpaste/questionnaire.json
+144.2,towel,towel.2,68,objects/towel.2/,objects_meta/towel.2/questionnaire.json
+147,umbrella,umbrella,69,objects/umbrella/,objects_meta/umbrella/questionnaire.json
+148.2,water_bottle,water_bottle.2,70,objects/water_bottle.2/,objects_meta/water_bottle.2/questionnaire.json

objects_meta/_index.json

@@ -0,0 +1,924 @@
+{
+  "schema_version": "v1",
+  "selected_object_count": 70,
+  "object_catalog": "manifest/object_catalog_v1.json",
+  "selected_objects": "manifest/selected_sos_objects_v1.csv",
+  "object_ids": [
+    "air_duster_can",
+    "alarm_clock",
+    "apple",
+    "baking_tray.1",
+    "banana",
+    "baseball_ball",
+    "basting_brush.1",
+    "beanie.2",
+    "bear.1",
+    "book.3",
+    "boot.2",
+    "bowl.1",
+    "cable",
+    "candy_bar.1",
+    "cleaning_brush",
+    "coffee_bottle",
+    "coffee_can.1",
+    "cracker_box",
+    "cup.1",
+    "doll.1",
+    "fry_pan.1",
+    "food_bag",
+    "game_controller",
+    "glove.2",
+    "glue_bottle.1",
+    "hairbrush",
+    "hammer.2",
+    "handy_pot",
+    "hat.1",
+    "headphone",
+    "helmet",
+    "instant_noodle_packet",
+    "jar",
+    "jello_box.1",
+    "juice_pouch.2",
+    "kettle",
+    "knife.1",
+    "ladle",
+    "lion.2",
+    "marker.5",
+    "meat_can",
+    "milk_box.1",
+    "milk_jug",
+    "mouse.3",
+    "mug.2",
+    "mustard_bottle.3",
+    "pear",
+    "peeler.2",
+    "power_drill",
+    "pringles_can.2",
+    "pump_bottle.2",
+    "remote_controller",
+    "root_beer_bottle",
+    "scissors.1",
+    "shampoo_bottle",
+    "shoe.1",
+    "soda_can.3",
+    "soft_scrub_cleanser_bottle",
+    "soup_can.1",
+    "spatula.2",
+    "sponge",
+    "spray_bottle.2",
+    "t-handle.2",
+    "tape_measure",
+    "teapot",
+    "tong",
+    "toothpaste",
+    "towel.2",
+    "umbrella",
+    "water_bottle.2"
+  ],
+  "object_id_to_global_object_id": {
+    "air_duster_can": 1,
+    "alarm_clock": 2,
+    "apple": 3,
+    "baking_tray.1": 4,
+    "banana": 5,
+    "baseball_ball": 6,
+    "basting_brush.1": 7,
+    "beanie.2": 8,
+    "bear.1": 9,
+    "book.3": 10,
+    "boot.2": 11,
+    "bowl.1": 12,
+    "cable": 13,
+    "candy_bar.1": 14,
+    "cleaning_brush": 15,
+    "coffee_bottle": 16,
+    "coffee_can.1": 17,
+    "cracker_box": 18,
+    "cup.1": 19,
+    "doll.1": 20,
+    "fry_pan.1": 21,
+    "food_bag": 22,
+    "game_controller": 23,
+    "glove.2": 24,
+    "glue_bottle.1": 25,
+    "hairbrush": 26,
+    "hammer.2": 27,
+    "handy_pot": 28,
+    "hat.1": 29,
+    "headphone": 30,
+    "helmet": 31,
+    "instant_noodle_packet": 32,
+    "jar": 33,
+    "jello_box.1": 34,
+    "juice_pouch.2": 35,
+    "kettle": 36,
+    "knife.1": 37,
+    "ladle": 38,
+    "lion.2": 39,
+    "marker.5": 40,
+    "meat_can": 41,
+    "milk_box.1": 42,
+    "milk_jug": 43,
+    "mouse.3": 44,
+    "mug.2": 45,
+    "mustard_bottle.3": 46,
+    "pear": 47,
+    "peeler.2": 48,
+    "power_drill": 49,
+    "pringles_can.2": 50,
+    "pump_bottle.2": 51,
+    "remote_controller": 52,
+    "root_beer_bottle": 53,
+    "scissors.1": 54,
+    "shampoo_bottle": 55,
+    "shoe.1": 56,
+    "soda_can.3": 57,
+    "soft_scrub_cleanser_bottle": 58,
+    "soup_can.1": 59,
+    "spatula.2": 60,
+    "sponge": 61,
+    "spray_bottle.2": 62,
+    "t-handle.2": 63,
+    "tape_measure": 64,
+    "teapot": 65,
+    "tong": 66,
+    "toothpaste": 67,
+    "towel.2": 68,
+    "umbrella": 69,
+    "water_bottle.2": 70
+  },
+  "global_object_id_to_object_id": {
+    "1": "air_duster_can",
+    "2": "alarm_clock",
+    "3": "apple",
+    "4": "baking_tray.1",
+    "5": "banana",
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+      "questionnaire_path": "objects_meta/remote_controller/questionnaire.json"
+    },
+    {
+      "global_object_id": 53,
+      "source_catalog_id": "109",
+      "source_category_id": "109",
+      "source_instance_id": null,
+      "object_name": "root_beer_bottle",
+      "object_id": "root_beer_bottle",
+      "sos_data_path": "objects/root_beer_bottle/",
+      "questionnaire_path": "objects_meta/root_beer_bottle/questionnaire.json"
+    },
+    {
+      "global_object_id": 54,
+      "source_catalog_id": "113.1",
+      "source_category_id": "113",
+      "source_instance_id": "1",
+      "object_name": "scissors",
+      "object_id": "scissors.1",
+      "sos_data_path": "objects/scissors.1/",
+      "questionnaire_path": "objects_meta/scissors.1/questionnaire.json"
+    },
+    {
+      "global_object_id": 55,
+      "source_catalog_id": "114",
+      "source_category_id": "114",
+      "source_instance_id": null,
+      "object_name": "shampoo_bottle",
+      "object_id": "shampoo_bottle",
+      "sos_data_path": "objects/shampoo_bottle/",
+      "questionnaire_path": "objects_meta/shampoo_bottle/questionnaire.json"
+    },
+    {
+      "global_object_id": 56,
+      "source_catalog_id": "117.1",
+      "source_category_id": "117",
+      "source_instance_id": "1",
+      "object_name": "shoe",
+      "object_id": "shoe.1",
+      "sos_data_path": "objects/shoe.1/",
+      "questionnaire_path": "objects_meta/shoe.1/questionnaire.json"
+    },
+    {
+      "global_object_id": 57,
+      "source_catalog_id": "120.3",
+      "source_category_id": "120",
+      "source_instance_id": "3",
+      "object_name": "soda_can",
+      "object_id": "soda_can.3",
+      "sos_data_path": "objects/soda_can.3/",
+      "questionnaire_path": "objects_meta/soda_can.3/questionnaire.json"
+    },
+    {
+      "global_object_id": 58,
+      "source_catalog_id": "121",
+      "source_category_id": "121",
+      "source_instance_id": null,
+      "object_name": "soft_scrub_cleanser_bottle",
+      "object_id": "soft_scrub_cleanser_bottle",
+      "sos_data_path": "objects/soft_scrub_cleanser_bottle/",
+      "questionnaire_path": "objects_meta/soft_scrub_cleanser_bottle/questionnaire.json"
+    },
+    {
+      "global_object_id": 59,
+      "source_catalog_id": "122.1",
+      "source_category_id": "122",
+      "source_instance_id": "1",
+      "object_name": "soup_can",
+      "object_id": "soup_can.1",
+      "sos_data_path": "objects/soup_can.1/",
+      "questionnaire_path": "objects_meta/soup_can.1/questionnaire.json"
+    },
+    {
+      "global_object_id": 60,
+      "source_catalog_id": "124.2",
+      "source_category_id": "124",
+      "source_instance_id": "2",
+      "object_name": "spatula",
+      "object_id": "spatula.2",
+      "sos_data_path": "objects/spatula.2/",
+      "questionnaire_path": "objects_meta/spatula.2/questionnaire.json"
+    },
+    {
+      "global_object_id": 61,
+      "source_catalog_id": "125",
+      "source_category_id": "125",
+      "source_instance_id": null,
+      "object_name": "sponge",
+      "object_id": "sponge",
+      "sos_data_path": "objects/sponge/",
+      "questionnaire_path": "objects_meta/sponge/questionnaire.json"
+    },
+    {
+      "global_object_id": 62,
+      "source_catalog_id": "127.2",
+      "source_category_id": "127",
+      "source_instance_id": "2",
+      "object_name": "spray_bottle",
+      "object_id": "spray_bottle.2",
+      "sos_data_path": "objects/spray_bottle.2/",
+      "questionnaire_path": "objects_meta/spray_bottle.2/questionnaire.json"
+    },
+    {
+      "global_object_id": 63,
+      "source_catalog_id": "133.2",
+      "source_category_id": "133",
+      "source_instance_id": "2",
+      "object_name": "t-handle",
+      "object_id": "t-handle.2",
+      "sos_data_path": "objects/t-handle.2/",
+      "questionnaire_path": "objects_meta/t-handle.2/questionnaire.json"
+    },
+    {
+      "global_object_id": 64,
+      "source_catalog_id": "135",
+      "source_category_id": "135",
+      "source_instance_id": null,
+      "object_name": "tape_measure",
+      "object_id": "tape_measure",
+      "sos_data_path": "objects/tape_measure/",
+      "questionnaire_path": "objects_meta/tape_measure/questionnaire.json"
+    },
+    {
+      "global_object_id": 65,
+      "source_catalog_id": "137",
+      "source_category_id": "137",
+      "source_instance_id": null,
+      "object_name": "teapot",
+      "object_id": "teapot",
+      "sos_data_path": "objects/teapot/",
+      "questionnaire_path": "objects_meta/teapot/questionnaire.json"
+    },
+    {
+      "global_object_id": 66,
+      "source_catalog_id": "141",
+      "source_category_id": "141",
+      "source_instance_id": null,
+      "object_name": "tong",
+      "object_id": "tong",
+      "sos_data_path": "objects/tong/",
+      "questionnaire_path": "objects_meta/tong/questionnaire.json"
+    },
+    {
+      "global_object_id": 67,
+      "source_catalog_id": "142",
+      "source_category_id": "142",
+      "source_instance_id": null,
+      "object_name": "toothpaste",
+      "object_id": "toothpaste",
+      "sos_data_path": "objects/toothpaste/",
+      "questionnaire_path": "objects_meta/toothpaste/questionnaire.json"
+    },
+    {
+      "global_object_id": 68,
+      "source_catalog_id": "144.2",
+      "source_category_id": "144",
+      "source_instance_id": "2",
+      "object_name": "towel",
+      "object_id": "towel.2",
+      "sos_data_path": "objects/towel.2/",
+      "questionnaire_path": "objects_meta/towel.2/questionnaire.json"
+    },
+    {
+      "global_object_id": 69,
+      "source_catalog_id": "147",
+      "source_category_id": "147",
+      "source_instance_id": null,
+      "object_name": "umbrella",
+      "object_id": "umbrella",
+      "sos_data_path": "objects/umbrella/",
+      "questionnaire_path": "objects_meta/umbrella/questionnaire.json"
+    },
+    {
+      "global_object_id": 70,
+      "source_catalog_id": "148.2",
+      "source_category_id": "148",
+      "source_instance_id": "2",
+      "object_name": "water_bottle",
+      "object_id": "water_bottle.2",
+      "sos_data_path": "objects/water_bottle.2/",
+      "questionnaire_path": "objects_meta/water_bottle.2/questionnaire.json"
+    }
+  ]
+}

rpx_croissant.json

@@ -0,0 +1,274 @@
+{
+  "@context": {
+    "@language": "en",
+    "@vocab": "https://schema.org/",
+    "citeAs": "cr:citeAs",
+    "column": "cr:column",
+    "conformsTo": "dct:conformsTo",
+    "cr": "http://mlcommons.org/croissant/",
+    "data": {
+      "@id": "cr:data",
+      "@type": "@json"
+    },
+    "dataBiases": "cr:dataBiases",
+    "dataCollection": "cr:dataCollection",
+    "dataType": {
+      "@id": "cr:dataType",
+      "@type": "@vocab"
+    },
+    "dct": "http://purl.org/dc/terms/",
+    "extract": "cr:extract",
+    "field": "cr:field",
+    "fileProperty": "cr:fileProperty",
+    "fileObject": "cr:fileObject",
+    "fileSet": "cr:fileSet",
+    "format": "cr:format",
+    "includes": "cr:includes",
+    "isLiveDataset": "cr:isLiveDataset",
+    "jsonPath": "cr:jsonPath",
+    "key": "cr:key",
+    "md5": "cr:md5",
+    "parentField": "cr:parentField",
+    "path": "cr:path",
+    "personalSensitiveInformation": "cr:personalSensitiveInformation",
+    "recordSet": "cr:recordSet",
+    "references": "cr:references",
+    "regex": "cr:regex",
+    "repeated": "cr:repeated",
+    "replace": "cr:replace",
+    "sc": "https://schema.org/",
+    "separator": "cr:separator",
+    "source": "cr:source",
+    "subField": "cr:subField",
+    "transform": "cr:transform"
+  },
+  "@type": "sc:Dataset",
+  "name": "RPX",
+  "description": "RPX (Robot Perception X) is a unified real-world RGB-D benchmark for evaluating robot perception under embodied deployment conditions. It comprises 75,000 frames across 100 indoor scenes with ~70 daily object categories, captured under a three-phase reconfiguration protocol (clutter, human interaction, clean) using Intel D435 and T265 sensors. Ground-truth annotations include instance masks, tracklets, metric depth, 6-DoF camera pose, and language attributes, enabling evaluation of 8 perception tasks on identical scenes and objects.\n\nNote on on-disk shape: per-frame records are physically packed into per-(scene, phase, modality) tar shards on the HF repo (scenes/<scene>/<phase>/<modality>.tar for raw modalities; labels/<modality>/v<N>.tar for versioned labels). The rpx_benchmark.dataset_hub downloader resolves selective task+split downloads from these shards transparently.",
+  "conformsTo": "http://mlcommons.org/croissant/1.0",
+  "citeAs": "TODO: add bibtex citation after paper is published",
+  "license": "https://creativecommons.org/licenses/by/4.0/",
+  "url": "https://huggingface.co/datasets/IRVLUTD/RPX",
+  "version": "1.0.0",
+  "isLiveDataset": false,
+  "creator": {
+    "@type": "Organization",
+    "name": "Anonymous (for review)",
+    "url": "https://anonymous.4open.science/r/RPX"
+  },
+  "dataCollection": "Data was collected using a hand-held sensor rig (Intel RealSense D435 RGB-D + T265 tracking camera) by human operators in indoor environments. Each of 100 scenes was captured across three phases: clutter, human interaction, and clean. Per-frame instance masks were generated using SAM2 with iterative human refinement. Camera poses are from T265 visual-inertial odometry. Language annotations are derived from FewSOL object questionnaires.",
+  "dataBiases": "The dataset is limited to indoor tabletop and room-scale environments with D435 depth range (0.3-3m). Object categories skew toward household and laboratory manipulation objects. Capture trajectories are human-driven and may not cover all robot motion profiles. All capture was performed by lab personnel; annotator diversity is limited.",
+  "personalSensitiveInformation": "The dataset contains video footage of human hands during the interaction phase. No faces, biometric identifiers, or personally identifiable information are captured or released. Participants provided informed consent for data collection and release.",
+  "distribution": [
+    {
+      "@type": "cr:FileObject",
+      "@id": "rpx-sample",
+      "name": "rpx-sample",
+      "description": "5-scene reviewer sample (<4GB), available without registration",
+      "contentUrl": "https://anonymous.4open.science/r/RPX/sample",
+      "encodingFormat": "application/zip",
+      "sha256": "TODO"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "rpx-full",
+      "name": "rpx-full",
+      "description": "Full 75,000-frame dataset with all annotations",
+      "contentUrl": "https://anonymous.4open.science/r/RPX/full",
+      "encodingFormat": "application/zip",
+      "sha256": "TODO"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "rpx-manifests",
+      "name": "rpx-manifests",
+      "description": "JSON manifest files for train/val/test splits and ESD labels",
+      "contentUrl": "https://anonymous.4open.science/r/RPX/manifests",
+      "encodingFormat": "application/json"
+    }
+  ],
+  "recordSet": [
+    {
+      "@type": "cr:RecordSet",
+      "@id": "frames",
+      "name": "frames",
+      "description": "Per-frame records with RGB, depth, instance mask, camera pose, phase, and ESD label",
+      "field": [
+        {
+          "@type": "cr:Field",
+          "@id": "frames/id",
+          "name": "id",
+          "description": "Unique frame identifier (scene_phase_framenum)",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/scene_id",
+          "name": "scene_id",
+          "description": "Scene index (0-99)",
+          "dataType": "sc:Integer"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/phase",
+          "name": "phase",
+          "description": "Scene phase: clutter | interaction | clean",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/difficulty",
+          "name": "difficulty",
+          "description": "ESD difficulty level: easy | medium | hard",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/rgb_path",
+          "name": "rgb_path",
+          "description": "Relative path to RGB image (PNG, 1920x1080)",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/depth_path",
+          "name": "depth_path",
+          "description": "Relative path to depth map (NPY float32, metres)",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/mask_path",
+          "name": "mask_path",
+          "description": "Relative path to instance mask (PNG, pixel values = instance IDs)",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/camera_pose",
+          "name": "camera_pose",
+          "description": "4x4 SE(3) camera-to-world matrix from T265 (float64)",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "frames/split",
+          "name": "split",
+          "description": "Dataset split: train | val | test",
+          "dataType": "sc:Text"
+        }
+      ]
+    },
+    {
+      "@type": "cr:RecordSet",
+      "@id": "tracklets",
+      "name": "tracklets",
+      "description": "Per-object tracklets with consistent IDs across frames within a phase",
+      "field": [
+        {
+          "@type": "cr:Field",
+          "@id": "tracklets/scene_id",
+          "name": "scene_id",
+          "dataType": "sc:Integer"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tracklets/phase",
+          "name": "phase",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tracklets/track_id",
+          "name": "track_id",
+          "description": "Unique object track identifier within scene+phase",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tracklets/object_category",
+          "name": "object_category",
+          "description": "Object category name",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tracklets/language_description",
+          "name": "language_description",
+          "description": "Natural language referring expression from FewSOL attributes",
+          "dataType": "sc:Text"
+        }
+      ]
+    },
+    {
+      "@type": "cr:RecordSet",
+      "@id": "esd_scores",
+      "name": "esd_scores",
+      "description": "Per-(scene, phase) ESD feature values and RPX-DS scores",
+      "field": [
+        {
+          "@type": "cr:Field",
+          "@id": "esd/scene_id",
+          "name": "scene_id",
+          "dataType": "sc:Integer"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/phase",
+          "name": "phase",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/rpx_ds",
+          "name": "rpx_ds",
+          "description": "RPX Difficulty Score (higher = harder)",
+          "dataType": "sc:Float"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/difficulty",
+          "name": "difficulty",
+          "description": "ESD split assignment: easy | medium | hard",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/occ_mean",
+          "name": "occ_mean",
+          "dataType": "sc:Float"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/iter_mean",
+          "name": "iter_mean",
+          "dataType": "sc:Float"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/area_cv",
+          "name": "area_cv",
+          "dataType": "sc:Float"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/depth_invalid_mask",
+          "name": "depth_invalid_mask",
+          "dataType": "sc:Float"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/vis_instability",
+          "name": "vis_instability",
+          "dataType": "sc:Float"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "esd/jerk",
+          "name": "jerk",
+          "dataType": "sc:Float"
+        }
+      ]
+    }
+  ]
+}

scenes/scene040/0/depth.tar

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