turing-motors/Japan-Open-Driving-Dataset-Sample

Japan Open Driving Dataset Sample

Overview

This repository contains a sample subset of the Japan Open Driving Dataset, a large-scale autonomous driving dataset comprising over 100 hours of driving data collected in Tokyo, Japan. The data is stored in nuScenes format and can be loaded with the nuscenes-devkit.

In addition to sensor data and 3D annotations, this dataset includes virtual captioned data for training Vision-Language-Model (VLM) and Vision-Language-Action (VLA) models. See captions/README.md for details.

Dataset Statistics

Item	Count
Scenes	20
Samples (keyframes)	4,000
Sample annotations (3D bounding boxes)	218,675
Object instances	17,707
Object categories	45
Maps	4

Sensors

Sensor	Modality
CAM_FRONT	Camera
CAM_FRONT_WIDE	Camera
CAM_FRONT_LEFT	Camera
CAM_FRONT_RIGHT	Camera
CAM_BACK	Camera
CAM_BACK_LEFT	Camera
CAM_BACK_RIGHT	Camera
LIDAR_TOP	LiDAR

Collection Locations

Location	Area
2041_shibuya_shibuya	Shibuya, Tokyo
2042_minato_azabu	Azabu, Minato-ku, Tokyo
2054_koto_odaiba	Odaiba, Koto-ku, Tokyo
2062_shinagawa_osaki	Osaki, Shinagawa-ku, Tokyo

Dataset Structure

.
├── README.md
├── pyproject.toml
├── nuscenes-devkit.zip
├── nuscenes_tutorial.ipynb
├── scripts/
│   └── download_dataset.sh
├── v2.X-train/
│   ├── attribute.json
│   ├── calibrated_sensor.json
│   ├── category.json
│   ├── ego_pose.json
│   ├── instance.json
│   ├── log.json
│   ├── map.json
│   ├── sample.json
│   ├── sample_annotation.json
│   ├── sample_data.json
│   ├── scene.json
│   ├── sensor.json
│   └── visibility.json
├── samples/
│   ├── CAM_FRONT/
│   ├── CAM_FRONT_WIDE/
│   ├── CAM_FRONT_LEFT/
│   ├── CAM_FRONT_RIGHT/
│   ├── CAM_BACK/
│   ├── CAM_BACK_LEFT/
│   ├── CAM_BACK_RIGHT/
│   └── LIDAR_TOP/
├── maps/
│   └── expansion/
├── can_bus/
├── archived_pallet_pickles/
└── captions/
    ├── README.md
    ├── STRIDE-QA/
    └── RACER/

Getting Started

1. Download the Sample Dataset

Ensure you have at least 30 GB of free disk space.

huggingface-cli download turing-motors/Japan-Open-Driving-Dataset-Sample \
  --repo-type dataset \
  --local-dir ./Japan-Open-Driving-Dataset-Sample

2. Environment Setup

Install uv and set up the Python environment:

curl -LsSf https://astral.sh/uv/install.sh | sh
uv python pin 3.10
uv venv
source .venv/bin/activate

Install the nuscenes-devkit from the included pyproject.toml and additional dependencies:

cd Japan-Open-Driving-Dataset-Sample
unzip nuscenes-devkit.zip

uv pip install .                  # installs nuscenes-devkit + dependencies
uv pip install pypcd4 jupyterlab  # LiDAR PCD support + notebook

3. Load the Dataset

from nuscenes.nuscenes import NuScenes

nusc = NuScenes(version='v2.X-train', dataroot='./Japan-Open-Driving-Dataset-Sample', verbose=True)

Expected output:

======
Loading NuScenes tables for version v2.X-train...
45 category,
68 attribute,
2 visibility,
17707 instance,
27 sensor,
27 calibrated_sensor,
33613 ego_pose,
20 log,
20 scene,
4000 sample,
35400 sample_data,
218675 sample_annotation,
4 map,
Done loading in 1.671 seconds.
======
Reverse indexing ...
Done reverse indexing in 0.4 seconds.
======

4. Tutorial Notebook

We provide a modified version of the nuscenes-devkit tutorial (nuscenes_tutorial.ipynb).

You can launch the notebook using:

jupyter lab nuscenes_tutorial.ipynb

License

Japan-Open-Driving-Dataset-Sample is released under the CC BY-NC-SA 4.0.

Privacy Protection

To ensure privacy protection, human faces and license plates in the images were anonymized using the Dashcam Anonymizer.

Access to the Japan Open Driving Dataset

To access the full Japan Open Driving Dataset, you are required to review and agree to the terms of use and submit an application form. Please refer to the link below for details:

Application Form for the Japan Open Driving Dataset

The full dataset requires approximately 24 TB of storage. Once your application has been reviewed and approved, a download token will be issued.

You can then download the dataset by running:

./scripts/download_dataset.sh \
  -u "https://open-dataset.turing-motors.net/api/list?token=<YOUR_TOKEN>" \
  -o ./dataset \
  -p 16