---
license: cc-by-nc-4.0
task_categories:
- image-to-text
dataset_info:
  features:
  - name: image
    dtype: image
  - name: file_name
    dtype: string
  - name: path_index
    dtype: int64
  - name: node_index
    dtype: int64
  - name: split
    dtype: string
  - name: latitude
    dtype: float64
  - name: longitude
    dtype: float64
  - name: month
    dtype: int64
  - name: year
    dtype: int64
  - name: move
    dtype: float64
  - name: heading
    dtype: float64
  - name: month_action
    dtype: int64
  - name: year_action
    dtype: int64
  splits:
  - name: train
    num_bytes: 95465834864.625
    num_examples: 1670003
  - name: test
    num_bytes: 1691121089.0
    num_examples: 34000
  download_size: 50700120251
  dataset_size: 97156955953.625
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
tags:
- autonomous-driving
- road-images
- spatio-temporal
---

# STRIDE
We develop STRIDE (Spatio-Temporal Road Image Dataset for Exploration), that consists of approximately 82B tokens which were arranged into a total of 6M visual "sentences" or token sequences. The sequences are generated from a relatively small set of 131k panoramic images, along with their metadata and openly available highway system data. Our approach enables a 27x increase in information, allowing for generative world model training. In essence, STRIDE turns real street-view panoramic observations into a navigable, interactive environment suitable for free-play across space and time.

For ease of use and data exploration, we prepared this sample of 10k detokenized paths, which amounts to about 100k projected panoramic images along with its corresponding metadata.

## Breakdown

### Dataset (STRIDE)
The full tokenized dataset is made available through two downloadable files in a public GCS bucket:
```bash
gsutil -m cp gs://tera-tardis/STRIDE-1/training.jsonl . # ~327GB
gsutil -m cp gs://tera-tardis/STRIDE-1/testing.jsonl . # ~9GB
```

In the future, the fully detokenized dataset will be made available. Should you need it, feel free to [contact the authors](#contacts).

#### San Mateo Coverage Map

![image/png](https://cdn-uploads.huggingface.co/production/uploads/681a420c572cfadef4d7954d/q5tLpuZJKdl7wFXJ68eUM.png)

Above is the 70km^2 area we selected for putting together the Google StreetView data using openly available road data. Each directly connected component of the graph is represented with a distinct color, for ease of visualization.

#### Queens Coverage Map

![image/png](https://cdn-uploads.huggingface.co/production/uploads/681a420c572cfadef4d7954d/qJiddVVEPWgjle83OxfFZ.png)

Above is an additional Queens, NY 27km^2 area. Each directly connected component of the graph is represented with a distinct color, for ease of visualization.

### Code (TARDIS)
The code used for training of the model is available [on GitHub](https://github.com/tera-ai/tardis).

### Checkpoints (TARDIS)
The checkpoint/state used for evaluation of the model was saved in MessagePack format and is made available through this downloadable file:
```bash
gsutil -m cp gs://tera-tardis/STRIDE-1/checkpoint.msgpack . # ~10GB
```

Should you need other checkpoints, feel free to [contact the authors](#contacts).

### Project Website
The project website is available [here](https://tera-ai.github.io/tardis-stride-webpage).

## Contacts

* [Héctor Carrión](mailto:hector@tera.earth)
* [Yutong Bai](mailto:ytongbai@gmail.com)
* [Víctor A. Hernández Castro](mailto:vhernandezcastro@gmail.com)
* [Kishan Panaganti](mailto:kpb@caltech.edu)
* [Ayush Zenith](mailto:ayush@tera-ai.com)
* [Matthew Trang](mailto:matthew@tera.earth)
* [Tony Zhang](mailto:tony@tera-ai.com)
<!-- * [Pietro Perona](mailto:) -->
<!-- * [Jitendra Malik](mailto:) -->

## Paper
[TARDIS STRIDE: A Spatio-Temporal Road Image Dataset for Exploration and Autonomy](https://huggingface.co/papers/2506.11302)