The dataset viewer is not available for this split.
Error code: StreamingRowsError Exception: ArrowTypeError Message: ("Expected bytes, got a 'list' object", 'Conversion failed for column window/model_b8f12521a4ebb7744bbf7d8a60c5aaf3_0 with type object') Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables pa_table = paj.read_json( File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: JSON parse error: Column(/window/model_b8f12521a4ebb7744bbf7d8a60c5aaf3_0/nearby_objects/cabinet/model_17fc64919a2c0aa03fa27c37b59b182e_0/[]) changed from string to number in row 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise return get_rows( File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator return func(*args, **kwargs) File "/src/services/worker/src/worker/utils.py", line 77, in get_rows rows_plus_one = list(itertools.islice(ds, rows_max_number + 1)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__ for key, pa_table in self.generate_tables_fn(**gen_kwags): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 167, in _generate_tables pa_table = pa.Table.from_pandas(df, preserve_index=False) File "pyarrow/table.pxi", line 3874, in pyarrow.lib.Table.from_pandas File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 611, in dataframe_to_arrays arrays = [convert_column(c, f) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 611, in <listcomp> arrays = [convert_column(c, f) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 598, in convert_column raise e File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 592, in convert_column result = pa.array(col, type=type_, from_pandas=True, safe=safe) File "pyarrow/array.pxi", line 339, in pyarrow.lib.array File "pyarrow/array.pxi", line 85, in pyarrow.lib._ndarray_to_array File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowTypeError: ("Expected bytes, got a 'list' object", 'Conversion failed for column window/model_b8f12521a4ebb7744bbf7d8a60c5aaf3_0 with type object')
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ποΈ GRScenes Data
β¨ Features
Large-Scale & Dynamic & Realistic: GRScenes is built from over 100k high-quality scene prototypes and now includes 99 environments (69 home scenes and 30 commercial scenes). Each scene has been carefully designed and accurately modeled to ensure realism.
Fine-grained Interactive Objects: All the objects have full internal modeling, enabling robots to perform actions such as opening doors or sliding drawers in a realistic way. These assets facilitate fine-grained manipulation tasks and include part-level annotations in Omniverse X-form level.
Rich Semantic Information: We set object-level semantic labels in each scene, which support tasks such as local navigation and object searching.
π Directory Structure
GRScenes-100/commercial_scenes.zip --(unzip)--> target_30_new
βββ ...
GRScenes-100/home_scenes.zip --(unzip)--> target_69_new
βββ Materials
β βββ ... (material mdl files and texture pictures)
βββ models
β βββ layout
β β βββ articulated
β β β βββ ... ( window, door, etc.)
β β βββ others
β β βββ ... (ceiling, wall, ground, etc.)
β βββ object
β βββ articulated
β β βββ ... (microwave, refrigerator, etc.)
β βββ others
β βββ ... (bed, bottle, cup, etc.)
βββ scenes
βββ MV7J6NIKTKJZ2AABAAAAADA8_usd
β βββ Materials -> ../../Materials
β βββ models -> ../../models
β βββ metadata.json (records the referenced model and material paths)
β βββ start_result_xxx.usd (scene usd files)
βββ ... (other scene folders)
Materials folder contains mdl files and texture pictures. The mdl files, which are Material Definition Language files commonly used by rendering engines such as NVIDIA Omniverse. These mdl files are used with texture pictures to define the physically based material properties such as color, reflectivity, and transparency that can be applied to 3D objects.
models folder contains 3D object models, where layouts objects under
layout/
and interactive objects underobject/
. Subdirectories are further categorized according to the model semantic labels such asdoor
andoven
.scenes folder (e.g.,
MV7J6NIKTKJZ2AABAAAAADA8_usd/
) contains the following files:Scene USD Files
We provides three usd files.
- raw scene, named as
start_result_raw.usd
, which defines the layout of the scene. - navigation scene, named as
start_result_navigation.usd
, which used for navigation tasks. - interaction scene, named as
start_result_interaction.usd
, which used for manipulation tasks.
- raw scene, named as
metadata.json
This file records the metadata information of the models and materials referenced in the raw scene.
interactive_obj_list.json
This file records the prim paths of the interactive objects in the interaction scene.
π Getting Started
Prerequisites
Configure MDL Material Search Path
If loading scenes in Isaac Sim, we recommend to configure an environment variable named MDL_SYSTEM_PATH
according to this document. Here are the steps:
# step 1. Find the Materials folder path, such as `./target_69_new/Materials`
# step 2. Configure the environment variable `MDL_SYSTEM_PATH` (saved to `~/.bashrc` is recommended).
echo 'export MDL_SYSTEM_PATH=$MDL_SYSTEM_PATH:</path/to/your_downloaded_materials_folder>' >> ~/.bashrc
source ~/.bashrc
Install Dependencies
Our tool scripts depends on OpenUSD and IsaacSim Python SDK, users need to install these dependencies as follows:
conda create -n <env_name> python=3.10
conda activate <env_name>
pip install usd-core==24.11
pip install isaacsim==4.2.0.2 isaacsim-extscache-physics==4.2.0.2 isaacsim-extscache-kit==4.2.0.2 isaacsim-extscache-kit-sdk==4.2.0.2 --extra-index-url https://pypi.nvidia.com
Usage
We provide some scripts for GRScenes.
- preprocess.py is used to bind physics properties (rigid body, collider etc.) with objects in one or several scenes.
## use `-i/--interaction` option to preprocess scenes for interaction.
python preprocess.py -i/--interaction -f/--files [</path/to/raw_scene_usd_file>...]
## use `-n/--navigation` option to preprocess scenes for navigation
python preprocess.py -n/--navigation -f/--files [</path/to/raw_scene_usd_file>...]
## besides, use `-d/--dirs` option to preprocess all scenes under the scenes folder such as `/ssd/$USER/target_69_new/scenes`
python preprocess.py -i/--interaction -n/--navigation -d/--dirs [</path/to/scene_root_folder>...]
- warmup.py is used to warmup the simulation process of the given scenes.
## warmup the specific scenes
python warmup.py -f/--files [</path/to/scene_usd_file>...]
## warmup all scenes
python warmup.py -d/--dirs [</path/to/scene_root_folder>...]
- play_scene.py is used to load and play the given scene.
python play_scene.py -f/--file </path/to/scene_usd_file>
- export_scenes.py is used to export the specified one or more scenes with its related objects and material files.
python export_scenes.py -i/--input </path/to/source_scene_root_folder> -o/--output </path/to/target_scene_root_folder> -n/--names [<scene_id1>...]
- get_metadata.py is used to get the metadata information of the models and materials referenced in given model instance or scene usd files.
python get_metadata.py -f/--files [</path/to/single_instance_or_scene_usd>...]
python get_metadata.py -d/--dirs [</path/to/instance_or_scene_root_folder>...]
- extract_objaverse.py is used to extract model objects from objaverse. It can convert the data type of 3D models from glb format to usd format, and detach the raw models and its materials.
python extract_objaverse.py --usd_path </path/to/objavers_usd_file> --material_path </path/to/output_material_files_path>
π License
GRUtopia's simulation platform is MIT licensed. The open-sourced GRScenes are under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License .
- Downloads last month
- 53