Details: https://aihabitat.org/datasets/hm3d/.
Getting access: https://matterport.com/habitat-matterport-3d-research-dataset
Github page with download links: https://github.com/matterport/habitat-matterport-3dresearch
After getting access to the dataset, you can download manually or programmatically via Habitat's data download utility.
First, you will need to generate a matterport API Token:
- Navigate to https://my.matterport.com/settings/account/devtools
- Generate an API token
- Your API token ID then functions as your username, passed to the download script with
--username
, and your API token secret functions as your password, passed to the download script with--password
. Note: Make sure to write your API token secret down, you can't reveal it again!
Now, you are ready to download. For example, to download the minival split, use:
python -m habitat_sim.utils.datasets_download --username <api-token-id> --password <api-token-secret> --uids hm3d_minival
By default, downloading the data for train/val/example scenes also pulls in the semantic annotations and configs for HM3D-Semantics v0.1. To download only the semantic files for these splits, use the uid hm3d_semantics
.
By default the download script will only download what is needed for Habitat-Sim. You can add _full
to the uid to download the raw glbs and the obj+mtl's in addition to what is needed for use with Habitat-Sim.
First, ensure that the corresponding file structure exists (see minival example below):
> ls <PATH TO HM3D>
hm3d_annotated_basis.scene_dataset_config.json train/
hm3d_basis.scene_dataset_config.json val/
minival/
> ls <PATH TO HM3D>/minival
00800-TEEsavR23oF/ 00806-tQ5s4ShP627/
00801-HaxA7YrQdEC/ 00807-rsggHU7g7dh/
00802-wcojb4TFT35/ 00808-y9hTuugGdiq/
00803-k1cupFYWXJ6/ 00809-Qpor2mEya8F/
00804-BHXhpBwSMLh/ hm3d_annotated_minival_basis.scene_dataset_config.json
00805-SUHsP6z2gcJ/ hm3d_minival_basis.scene_dataset_config.json
> ls <PATH TO HM3D>/minival/00800-TEEsavR23oF/
TEEsavR23oF.basis.glb TEEsavR23oF.basis.navmesh
TEEsavR23oF.semantic.glb TEEsavR23oF.semantic.txt
Note that there may be more files in <PATH TO HM3D>/minival/00800-TEEsavR23oF/
if the full HM3D dataset is downloaded. Most importantly, ensure that the hm3d_annotated_*
, *.semantic.glb
, and *.semantic.txt
files are present.
To load semantic annotations in Habitat-Sim:
- Enable the semantic sensor
- Set the
scene_dataset_config_file
configuration variable
A simple example below:
import habitat_sim
backend_cfg = habitat_sim.SimulatorConfiguration()
backend_cfg.scene_id = "<PATH TO HM3D>/minival/00800-TEEsavR23oF/TEEsavR23oF.basis.glb"
backend_cfg.scene_dataset_config_file = "<PATH TO HM3D>/hm3d_annotated_basis.scene_dataset_config.json"
sem_cfg = habitat_sim.CameraSensorSpec()
sem_cfg.uuid = "semantic"
sem_cfg.sensor_type = habitat_sim.SensorType.SEMANTIC
agent_cfg = habitat_sim.agent.AgentConfiguration()
agent_cfg.sensor_specifications = [sem_cfg]
sim_cfg = habitat_sim.Configuration(backend_cfg, [agent_cfg])
sim = habitat_sim.Simulator(sim_cfg)
To view the semantic annotations in the C++ viewer, install the latest main
branch of Habitat-Sim and run the following command:
# ./build/viewer if compiled locally
habitat-viewer --dataset '<PATH TO HM3D>/hm3d_annotated_basis.scene_dataset_config.json' TEEsavR23oF
To load semantic annotations in habitat-lab:
-
Add the semantic sensor to the list of agent sensors:
SIMULATOR.AGENT_0.SENSORS = ["RGB_SENSOR", "SEMANTIC_SENSOR"]
-
Set the
SIMULATOR.SCENE_DATASET
configuration variable:SIMULATOR.SCENE_DATASET = "<PATH TO HM3D>/hm3d_annotated_basis.scene_dataset_config.json"
Note that if you are using the RL environment from habitat-lab, SIMULATOR.SCENE_DATASET
is overridden by the episode dataset (see here). Each episode in the episode dataset must point to the annotation config file (as done in the HM3D ObjectNav dataset here).
Details: https://niessner.github.io/Matterport/.
Github: https://github.com/niessner/Matterport
MP3D dataset for use with Habitat can be downloaded using the official Matterport3D download script as follows: python download_mp.py --task habitat -o path/to/download/
.
Note that this download script requires python 2.7 to run.
You only need the habitat zip archive and not the entire Matterport3D dataset.
Once you have the habitat zip archive, you should download this SceneDatasetConfig file and place it in the root directory for the Matterport3D dataset (e.g. Habitat-Sim/data/scene_datasets/mp3d/). This file should then be specified as the scene dataset config in the SimulatorConfiguration structure like this example for the ReplicaCAD dataset.
-
The Gibson dataset for use with Habitat can be downloaded by agreeing to the terms of use in the Gibson repository.
-
Semantic information for Gibson is available from the 3DSceneGraph dataset. The semantic data will need to be converted before it can be used within Habitat:
tools/gen_gibson_semantics.sh /path/to/3DSceneGraph_medium/automated_graph /path/to/GibsonDataset /path/to/output
To use semantics, you will need to enable the semantic sensor.
Once you have downloaded the Gibson dataset and converted the semantic data, you should download this SceneDatasetConfig file and place it in the root directory for the Gibson dataset (e.g. Habitat-Sim/data/scene_datasets/gibson/). This file should then be specified as the scene dataset config in the SimulatorConfiguration structure like this example for the ReplicaCAD dataset.
Details and download isntructions: https://github.com/facebookresearch/Replica-Dataset.
Details and download instructions: https://aihabitat.org/datasets/replica_cad/.
The official ScanNet data can be downloaded here: http://www.scan-net.org/. To use ScanNet scans with Habitat-Sim, the scene_*.ply
files need to be converted to glTF format (*.glb
). For example, using assimp:
assimp export <PLY FILE> <GLB PATH>
The exported *.glb
files can directly be used with Habitat-Sim versions >= 2.0.
Note: Depending on the configured radius and height of the agent, certain scans may have no navigable locations on the navmesh (~200). These scenes can be filtered out by checking if sim.pathfinder.is_loaded
is False.
Details: https://www.ycbbenchmarks.com/.
YCB Object and Model Set is designed for facilitating benchmarking in robotic manipulation... The set is associated with a model database which provides mesh models and high-resolution RGB-D scans of the objects for easy incorporation into manipulation and planning software platforms.
Pre-processed, Habitat-ready assets.
Quick-start with the dataset_downloader utility:
# with conda install
python -m habitat_sim.utils.datasets_download --uids ycb --data-path /path/to/data/
# with source
python /path/to/habitat_sim/src_python/habitat_sim/utils/datasets_download.py --uids ycb --data-path /path/to/data/
Load the assets in python by setting MetadataMediator.active_dataset:
#load the full YCB dataset into the MetadataMediator
sim.metadata_mediator.active_dataset = "/path/to/data/objects/ycb/ycb.scene_dataset_config.json"
#then instance objects from the ObjectAttributesManager:
chef_can_key = sim.get_object_template_manager().get_file_template_handles("002_master_chef_can")[0]
chef_can_object = sim.get_rigid_object_manager().add_object_by_template_handle(chef_can_key)
For more information on using objects in habitat-sim, see the "Habitat-Sim for Interaction" and "Habitat-Sim Advanced Topics" sections of our ECCV tutorial series.
To quickly test in the viewer application:
#from the habitat-sim directory
# C++
# ./build/viewer if compiling locally
habitat-viewer --stage-requires-lighting --enable-physics --object-dir "" --dataset data/objects/ycb/ycb.scene_dataset_config.json -- data/test_assets/scenes/simple_room.glb
Then press 'o'
key to add random objects from the dataset.
For datasets with scene dataset configuration support (such as HM3D, ReplicaCAD, MP3D, Gibson, etc) you can preview the assets using one of Habitat's command-line driven viewers, either in c++ or python. When launching the viewer, you should specify not only the desired scene to load, but also the specifying the scene dataset configuration file, to guarantee the assets load and display correctly. This has the added benefit of providing quick access to other scenes in the same dataset, without requiring a reload of the entire simulation environment from the command line.
If you are using the python viewer, the command line parameters to load a scene dataset configuration and a scene file would be (run from the Habitat-Sim source directory):
python examples/viewer.py --dataset '<path to desired dataset config>/<desired dataset>.scene_dataset_config.json' --scene '<scene to show>'
If you are using the c++ viewer, the command line parameters to load a scene dataset configuration and a scene file would be (run from the Habitat-Sim source directory):
# ./build/viewer if compiled locally
habitat-viewer --dataset '<path to desired dataset config>/<desired dataset>.scene_dataset_config.json' '<scene to show>'
To preview other scenes in the same scene dataset in either viewer, use TAB
/SHIFT-TAB
to cycle forward/backward through the list of scenes referenced by the loaded scene dataset config.