Nothing special needs to be done for the nuScenes dataset, simply download it as per the instructions in the devkit README.
It should look like this after downloading:
/path/to/nuScenes/
├── maps/
├── samples/
├── sweeps/
├── v1.0-mini/
├── v1.0-test/
└── v1.0-trainval/
Note: At a minimum, only the annotations need to be downloaded (not the raw radar/camera/lidar/etc data).
Nothing special needs to be done for the nuPlan dataset, simply download v1.1 as per the instructions in the devkit documentation.
It should look like this after downloading:
/path/to/nuPlan/
└── dataset
├── maps
│ ├── nuplan-maps-v1.0.json
│ ├── sg-one-north
│ │ └── 9.17.1964
│ │ └── map.gpkg
│ ├── us-ma-boston
│ │ └── 9.12.1817
│ │ └── map.gpkg
│ ├── us-nv-las-vegas-strip
│ │ └── 9.15.1915
│ │ ├── drivable_area.npy.npz
│ │ ├── Intensity.npy.npz
│ │ └── map.gpkg
│ └── us-pa-pittsburgh-hazelwood
│ └── 9.17.1937
│ └── map.gpkg
└── nuplan-v1.1
├── mini
│ ├── 2021.05.12.22.00.38_veh-35_01008_01518.db
│ ├── 2021.06.09.17.23.18_veh-38_00773_01140.db
│ ├── ...
│ └── 2021.10.11.08.31.07_veh-50_01750_01948.db
└── trainval
├── 2021.05.12.22.00.38_veh-35_01008_01518.db
├── 2021.06.09.17.23.18_veh-38_00773_01140.db
├── ...
└── 2021.10.11.08.31.07_veh-50_01750_01948.db
Note: Not all dataset splits need to be downloaded. For example, you can download only the nuPlan Mini Split in case you only need a small sample dataset.
Nothing special needs to be done for the Waymo Open Motion Dataset, simply download v1.1 as per the instructions on the dataset website.
It should look like this after downloading:
/path/to/waymo/
├── training/
| ├── training.tfrecord-00000-of-01000
| ├── training.tfrecord-00001-of-01000
| └── ...
├── validation/
│ ├── validation.tfrecord-00000-of-00150
| ├── validation.tfrecord-00001-of-00150
| └── ...
└── testing/
├── testing.tfrecord-00000-of-00150
├── testing.tfrecord-00001-of-00150
└── ...
Note: Not all the dataset parts need to be downloaded, only the necessary directories in the Google Cloud Bucket need to be downloaded (e.g., validation for the validation dataset).
Nothing special needs to be done for the Lyft Level 5 dataset, simply download it as per the instructions on the dataset website.
It should look like this after downloading:
/path/to/lyft/
├── LICENSE
├── aerial_map
├── feedback.txt
├── meta.json
├── scenes/
│ ├── sample.zarr
| ├── train.zarr
| └── ...
└── semantic_map/
└── semantic_map.pb
Note: Not all the dataset parts need to be downloaded, only the necessary .zarr files need to be downloaded (e.g., sample.zarr for the small sample dataset).
Nothing special needs to be done for the INTERACTION Dataset, simply download it as per the instructions on the dataset website.
It should look like this after downloading:
/path/to/interaction_single/
├── maps/
│ ├── DR_CHN_Merging_ZS0.osm
| ├── DR_CHN_Merging_ZS0.osm_xy
| └── ...
├── test_conditional-single-agent/
│ ├── DR_CHN_Merging_ZS0_obs.csv
| ├── DR_CHN_Merging_ZS2_obs.csv
| └── ...
└── test_single-agent/
│ ├── DR_CHN_Merging_ZS0_obs.csv
| ├── DR_CHN_Merging_ZS2_obs.csv
| └── ...
└── train/
│ ├── DR_CHN_Merging_ZS0_train.csv
| ├── DR_CHN_Merging_ZS2_train.csv
| └── ...
└── val/
├── DR_CHN_Merging_ZS0_val.csv
├── DR_CHN_Merging_ZS2_val.csv
└── ...
/path/to/interaction_multi/
├── maps/
│ ├── DR_CHN_Merging_ZS0.osm
| ├── DR_CHN_Merging_ZS0.osm_xy
| └── ...
├── test_conditional-multi-agent/
│ ├── DR_CHN_Merging_ZS0_obs.csv
| ├── DR_CHN_Merging_ZS2_obs.csv
| └── ...
└── test_multi-agent/
│ ├── DR_CHN_Merging_ZS0_obs.csv
| ├── DR_CHN_Merging_ZS2_obs.csv
| └── ...
└── train/
│ ├── DR_CHN_Merging_ZS0_train.csv
| ├── DR_CHN_Merging_ZS2_train.csv
| └── ...
└── val/
├── DR_CHN_Merging_ZS0_val.csv
├── DR_CHN_Merging_ZS2_val.csv
└── ...
The raw data can be found in many places online, ranging from research projects' data download scripts to copies of the original data itself on GitHub. In this data loader, we assume the data was sourced from the latter.
It should look like this after downloading:
/path/to/eth_ucy/
├── biwi_eth.txt
├── biwi_hotel.txt
├── crowds_zara01.txt
├── crowds_zara02.txt
├── crowds_zara03.txt
├── students001.txt
├── students003.txt
└── uni_examples.txt
The raw data can be found in many places online, the easiest is probably this space-optimized version on Kaggle.
It should look like this after downloading:
/path/to/sdd/
├── bookstore/
| ├── video0
| ├── annotations.txt
| └── reference.jpg
| ├── video1
| ├── annotations.txt
| └── reference.jpg
| └── ...
├── coupa/
| ├── video0
| ├── annotations.txt
| └── reference.jpg
| ├── video1
| ├── annotations.txt
| └── reference.jpg
| └── ...
└── ...
Note: Only the annotations need to be downloaded (not the videos).
The dataset can be downloaded from here.
It should look like this after downloading:
/path/to/av2mf/
├── train/
| ├── 0000b0f9-99f9-4a1f-a231-5be9e4c523f7/
| | ├── log_map_archive_0000b0f9-99f9-4a1f-a231-5be9e4c523f7.json
| | └── scenario_0000b0f9-99f9-4a1f-a231-5be9e4c523f7.parquet
| ├── 0000b6ab-e100-4f6b-aee8-b520b57c0530/
| | ├── log_map_archive_0000b6ab-e100-4f6b-aee8-b520b57c0530.json
| | └── scenario_0000b6ab-e100-4f6b-aee8-b520b57c0530.parquet
| └── ...
├── val/
| ├── 00010486-9a07-48ae-b493-cf4545855937/
| | ├── log_map_archive_00010486-9a07-48ae-b493-cf4545855937.json
| | └── scenario_00010486-9a07-48ae-b493-cf4545855937.parquet
| └── ...
└── test/
├── 0000b329-f890-4c2b-93f2-7e2413d4ca5b/
| ├── log_map_archive_0000b329-f890-4c2b-93f2-7e2413d4ca5b.json
| └── scenario_0000b329-f890-4c2b-93f2-7e2413d4ca5b.parquet
└── ...