--- pretty_name: "NATIX Multi-Camera Driving Dataset" language: - en license: "other" license_name: "natix-data-rail-nc-license" license_link: "LICENSE.md" viewer: true extra_gated_description: "This repository is publicly accessible, but you have to accept the conditions to access its files and content. Once your access request is approved, you will be provided with the credentials required to download the full dataset." extra_gated_fields: Company/Organisation: text Company/Organisation email (access to R2 will be shared to this email): text I want to use this dataset for: type: select options: - Research - Education - Open Source - Other Please describe your project and provide details: text I will not attempt to de-anonymize, re-identify, or track any individual or vehicle appearing in the Dataset - including by cross-referencing license plates - and will not infer or label personal characteristics (such as race, ethnicity, gender, age, or health), perform biometric processing, emotion recognition, or social scoring, or use the Dataset for any surveillance or law enforcement purpose: checkbox I will not use the Dataset, Derivatives of the Dataset, or any Trained Model for any Commercial Purpose as defined in the License, and will not redistribute, sublicense, sell, or otherwise make the Dataset or Derivatives of the Dataset available to any third party, except for Internal Use within my own organization or with NATIX's express written permission: checkbox I understand this License is granted for a term of 12 months from my initial download of the Dataset, and that I must permanently delete all copies of the Dataset, Derivatives of the Dataset, and any Trained Model upon expiration: checkbox I agree to notify NATIX and cooperate in good faith if I identify insufficiently anonymized content or receive a request from a data subject seeking to exercise their rights: checkbox tags: - autonomous-driving - computer-vision - video - dashcam - multi-camera - geospatial - gps - gnss - road-scene-understanding size_categories: - 1K **Note: you need 1,283.58 GB of free storage** Install dependencies: ```bash pip install boto3 ``` Download the full dataset: ```python import boto3 from pathlib import Path ENDPOINT_URL = "https://e613d208b194c3a6749f5cc0a1ca5510.eu.r2.cloudflarestorage.com" BUCKET_NAME = "natix-prod-100h-open-source" ACCESS_KEY = "PROVIDED_ACCESS_KEY" # provided after access request is approved SECRET_KEY = "PROVIDED_SECRET_KEY" # provided after access request is approved DEST_DIR = Path("./dataset") s3 = boto3.client( "s3", endpoint_url=ENDPOINT_URL, aws_access_key_id=ACCESS_KEY, aws_secret_access_key=SECRET_KEY, ) paginator = s3.get_paginator("list_objects_v2") for page in paginator.paginate(Bucket=BUCKET_NAME): for obj in page.get("Contents", []): key = obj["Key"] dest_path = DEST_DIR / key # Creating parent directories as needed dest_path.parent.mkdir(parents=True, exist_ok=True) print(f"Downloading: {key}") s3.download_file(BUCKET_NAME, key, str(dest_path)) ``` ## Dataset Overview * **Footage**: recorded via vehicle surround-view camera system and segmented into approximately 1-minute `.mp4` files. * **4-camera trips**: `FRONT`, `REAR`, `LEFT`, `RIGHT`. * **6-camera trips**: `FRONT`, `REAR`, `LEFT_REPEATER`, `RIGHT_REPEATER`, plus two pillar cameras: `LEFT_PILLAR`, `RIGHT_PILLAR`. * **Camera FOV (Field of View)**: Front ~50°; Rear ~140°; Side ~90°; Side Pillar ~90°. * **Resolution** depends on the vehicle type and camera. Observed examples include * 1280 x 960 across all cameras in some 4-camera trips * 1448 x 938 for the standard cameras in some 6-camera trips, and, * in some 6-camera trips, a natively larger front camera, for example, 2896 x 1876. * All faces and license plates are blurred. In addition, 14% of the bottom of all rear-camera footage is blurred/anonymized. * **Time-series metadata** * **GPS metadata, 1-10 Hz**: Per-camera, frame-matched location and motion metadata. * **Trip-level metadata** * **Trip Insight**: high-level aggregated metadata about the trip, including duration, estimated distance, estimated average speed, per-minute weather, road type, location context, and camera availability. * **Fixed Metadata**: values that do not change during a trip, including vehicle/platform information, camera intrinsics, camera extrinsics, and sensor positions. **Artifacts included in this Dataset** | Component | Location | Availability | |---|---|---| | Footage (`.mp4`, per camera) | Camera folder | Included | | GPS metadata (`.csv`, per camera) | Camera folder | Included | | `trip_insight.json` | Trip root | Included | | `fixed_metadata.json` / `.csv` | Trip root | Included | | Schema files (`telemetry_data.proto`, `trip_metadata.proto`) | Trip root | Included | | `mapping.txt` | Segment folder | Expected. Contact NATIX if missing or inconsistent. | | `trip_manifest.jsonl` | `/` | Included. Trip-level manifest for all trips | | `dataset-sample/` | `/` | Included. 6 complete trips from Switzerland and the United States | ## Dataset Folder Structure ```text 📁 dataset/ ├── 📁 Country/[State]/ │ └── 📁 / │ ├── 📁 HH-MM-SS/ │ │ ├── 📁 FRONT_FOLDER/ │ │ │ ├── FRONT__.mp4 │ │ │ ├── FRONT__.csv │ │ │ └── FRONT__.mcap │ │ ├── 📁 REAR_FOLDER/ │ │ │ │ │ │ # 4-camera trips additionally contain: │ │ ├── 📁 LEFT_FOLDER/ │ │ ├── 📁 RIGHT_FOLDER/ │ │ │ │ │ │ # 6-camera trips additionally contain: │ │ ├── 📁 LEFT_REPEATER_FOLDER/ │ │ ├── 📁 RIGHT_REPEATER_FOLDER/ │ │ ├── 📁 LEFT_PILLAR_FOLDER/ │ │ ├── 📁 RIGHT_PILLAR_FOLDER/ │ │ │ │ │ └── mapping.txt │ │ │ ├── 📁 HH-MM-SS/ │ │ └── ... │ │ │ ├── trip_insight.json │ ├── fixed_metadata.json │ ├── fixed_metadata.csv │ ├── fixed_metadata.mcap │ ├── telemetry_data.proto │ └── trip_metadata.proto ``` ## Data Definitions ### Trip Manifest The manifest contains one JSON object per trip folder, not one JSON object per individual file. Each row describes a self-contained trip folder and includes the trip prefix, country or region, duration, camera configuration, file count, total size, counts for per-camera data files, and segment timestamps. The complete trip-level manifest is provided as: `trip_manifest.jsonl` | Field | Description | |---|---| | `trip_id` | Trip folder identifier, including the continuous-piece suffix where applicable | | `country` | Country of the trip | | `state` | State or region when available, otherwise `null` | | `prefix` | Relative path to the trip folder under the R2 dataset root | | `duration_min` | Trip duration in minutes | | `cam_count` | Number of cameras in the trip configuration | | `cameras` | Camera folders present for the trip | | `file_count` | Total number of files inside the trip folder | | `size_bytes` | Total trip folder size in bytes | | `formats` | Count of per-camera data files by extension, such as `mp4` and `csv` | | `timestamps` | Segment start-time folders included in the trip | ### GPS Metadata Each GPS Metadata file is located in its camera folder and is named like the corresponding `.mp4` file, for example, `FRONT_2025-11-12_21-07-33.csv`. It contains frame-matched GPS position and motion metadata. | Field | Description | |---|---| | `timestamp` | ISO-8601 timestamp with millisecond precision | | `frame_number` | Frame index synced to the `.mp4`, starting at 1 | | `GPS_latitude_deg`, `GPS_longitude_deg` | Latitude and longitude | | `horizontal_accuracy_m` | Location uncertainty in meters | | `speed_mps` | Estimated speed in meters per second, from the location data | | `velocity_north_mps`, `velocity_east_mps` | Velocity components toward north and east in meters per second | | `heading_deg` | Heading in degrees, clockwise, 0 = north, calculated from position updates | | `heading_accuracy_deg` | Heading uncertainty in degrees | | `image_direction` | Direction the camera faces in this frame, in degrees, clockwise, 0 = north; calculated from heading and camera mounting direction | > **Notes** > 1- Missing values are encoded as the literal string `na`. > 2- Rows may skip frame numbers on any camera, including the front camera. When no GPS update is available for a footage frame, that frame may have no row. Do not assume one row per frame. ### Fixed Trip Metadata At the root of each trip folder, static information that does not change during the trip is provided in multiple equivalent formats: `fixed_metadata.json` and `fixed_metadata.csv`. **Top-level fields** | Field | Description | |---|---| | `version` | Schema version | | `trip_identifier` | Trip UUID, without the `_` piece suffix | | `frame_width`, `frame_height`, `frame_mp` | Footage frame size in pixels and megapixels; see the note below | | `vehicle_make`, `vehicle_model` | Vehicle make and model, for example, `Tesla` / `model3` or `modely` | | `platform_type_video` | Source platform of the footage, for example, `Tesla` | | `reference_frame` | Reference frame of all extrinsics, for example, `ground_nominal` | > **Front camera resolution note** > `frame_width` and `frame_height` describe the trip standard cameras. In some 6-camera trips, the front camera is natively larger, for example, 2896 x 1876 instead of 1448 x 938. Its intrinsic parameters, such as `fx`, `fy`, `cx`, and `cy`, are already expressed at the native front-camera size. Use them as shipped together with the actual pixel size of the front footage. NATIX does not resize the footage. **`device_extrinsics`** - one entry per device. Camera entries contain: | Field | Description | |---|---| | `device_name` | e.g. `camera_front`, `camera_rear`; `camera_left`, `camera_right` in 4-camera trips; `camera_left_repeater`, `camera_right_repeater`, `camera_left_pillar`, `camera_right_pillar` in 6-camera trips | | `fx`, `fy`, `cx`, `cy` | Camera intrinsics, estimated, in pixels | | `k1`, `k2`, `k3`, `p1`, `p2` | Radial and tangential distortion, estimated | | `r11` ... `r33` | 3 x 3 row-major rotation matrix: orientation of the camera relative to `ground_nominal` | | `tx`, `ty`, `tz` | Translation of the device relative to `ground_nominal`, based on usual device locations | | `field_of_view_hor_deg`, `field_of_view_ver_deg` | Horizontal and vertical field of view in degrees | ### Trip Insight At the root of each trip folder, `trip_insight.json` gives an overview of the whole trip. For split trips, it describes the standalone trip piece. **Trip-level fields** | Field | Description | |---|---| | `startEpochMs`, `endEpochMs` | Trip start and end time in Unix epoch milliseconds | | `duration` | Trip duration in milliseconds | | `estimatedDistance` | Estimated distance traveled in kilometers | | `estimatedAverageSpeed` | Estimated average speed over the trip in km/h | | `firstLocation` | Object with `latitude` and `longitude` of the trip first GPS position | | `timezone` | IANA timezone string, for example, `America/New_York` | | `minutes` | Array of per-minute objects, each keyed by `YYYY-MM-DD_HH-MM` | **Per-minute fields** | Field | Type | Description | |---|---|---| | `weather` | list | Observed weather conditions, for example, `["Clear"]` | | `temperature` | list | Temperature in C, for example, `[7.4]` | | `timeOfDay` | list | Time-of-day category, for example, `["day"]`, `["dusk"]` | | `roadType` | list | OSM-based road type, for example, `["motorway"]`, `["residential"]` | | `country` | string | Country name | | `region` | string | Region or state | | `place` | string | City or town | | `district` | string | Administrative district | | `postcode` | string | Postal code | | `locality` | string | Locality sub-area | | `neighborhood` | string | Neighborhood name, may be empty | | `address` | string | Street address or area name | | `cameraCount` | number | Number of cameras present in this minute | | `footageCount` | number | Number of cameras with available footage in this minute | | `camera flags` | boolean | Whether footage exists per camera | The camera-existence flags match the trip camera configuration: * **4-camera trips**: `frontCameraExists`, `rearCameraExists`, `leftCameraExists`, `rightCameraExists` * **6-camera trips**: `frontCameraExists`, `rearCameraExists`, `leftRepeaterCameraExists`, `rightRepeaterCameraExists`, `leftPillarCameraExists`, `rightPillarCameraExists` ## Special Considerations ### General Footage and File Notes 1. Footage may have different frame rates and durations, even within the same segment. * Different durations, same frame rate: Front - 00:01:00.21 @ 36.02 fps; Rear - 00:01:00.00 @ 36.02 fps. * Different durations, different frame rates: Front - 00:01:00.06 @ 36.03 fps; Rear - 00:01:00.36 @ 34.62 fps. 2. Split trips use the `_` folder format. Each piece contains continuous minutes and has its own metadata. 3. If footage, metadata, or camera-folder contents appear missing or inconsistent, please contact NATIX so the dataset can be reviewed. ### GPS Data Processing 1. GPS rows can skip frame numbers on any camera, including the front camera. Do not assume one metadata row per frame. 2. GPS data is first aligned with the front footage. Because camera durations and frame rates can differ, other cameras may have different row counts or different matched metadata per frame. 3. Time sync error between vehicle camera/video data and GPS data is expected to be 0-1 seconds, and in extreme cases up to 3 seconds. 4. When GPS updates arrive too quickly, such as in two consecutive frames, `heading_deg` and `speed_mps` may be 0 because they are calculated from position updates. ### Trip Insight Estimate Notes Some Trip Insight values, such as `estimatedDistance`, `estimatedAverageSpeed`, `weather`, and `temperature`, are best-effort estimates derived from third-party APIs or baseline calculations. Treat them as guidance, not ground truth. ## License and Usage Terms This dataset is released by NATIX under the **NATIX Data RAIL-NC License**, a responsible-AI data license adapted from the BigScience Open RAIL-M License. Under this License, the dataset may be used for non-commercial purposes only, subject to the use-based restrictions set out in the License, and may not be redistributed or made available to third parties. The License is granted for a limited term. Commercial use is NOT permitted without separate written permission from NATIX. For the full license text, see [LICENSE.md](LICENSE.md). **Disclaimer** This dataset is provided "as is" and "as available", without warranties of any kind, whether express or implied, including but not limited to warranties of merchantability, fitness for a particular purpose, accuracy, or non-infringement. While faces and license plates have been blurred and known sensitive areas removed, NATIX does not warrant that anonymization is complete or that all sensitive areas have been excluded. NATIX makes no guarantees regarding the completeness, reliability, or correctness of the data and provides no support, maintenance, or updates. Use of this dataset is entirely at the consumer's own risk, and NATIX shall not be liable for any damages or losses arising from its use. ## Attribution and Citation There is no separate paper required for citation. If you use this dataset, please credit NATIX and link to the dataset page. Recommended attribution: ```text NATIX Multi-Camera Driving Dataset. 2026. Available on Hugging Face Hub. NATIX Website: https://www.natix.network/ ``` BibTeX: ```bibtex @misc{natix2026_multi_camera_driving_dataset, title = {NATIX Multi-Camera Driving Dataset}, author = {{NATIX}}, year = {2026}, publisher = {NATIX}, howpublished = {Hugging Face Hub}, url = {https://huggingface.co/datasets/natix-network-org/natix-multi-camera-driving-dataset}, note = {Multi-camera driving dataset with telemetry metadata. Website: https://www.natix.network/} } ``` ## Contact Us We check every dataset before release, but real-world crowd-sourced data can contain surprises. If anything in the dataset looks sensitive, incomplete, inconsistent, or unexpected, please contact NATIX so it can be reviewed. NATIX has built a unique, large-scale multi-camera driving dataset crowd-sourced from vehicles' cameras globally. This data is currently being used by various physical AI players supporting world foundational models, end-to-end (E2E) driving models, and simulation-based workflows for training, testing, and validation. For more info, you can contact NATIX directly at `dataset@natix.io`.