Metadata-Version: 2.1
Name: lyft-dataset-sdk
Version: 0.0.3
Summary: SDK for Lyft dataset.
Home-page: UNKNOWN
Author: Vladimir Iglovikov
Author-email: viglovikov@lyft.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
Requires-Dist: flake8
Requires-Dist: numpy (>=1.14.5)
Requires-Dist: opencv-python (>=3.4.2.17)
Requires-Dist: Pillow (>=5.2.0)
Requires-Dist: pyquaternion (>=0.9.5)
Requires-Dist: scikit-learn (>=0.19.2)
Requires-Dist: tqdm (>=4.25.0)
Requires-Dist: scipy (>=1.1.0)
Requires-Dist: cachetools (>=3.1.0)
Requires-Dist: Shapely (>=1.6.4.post2)
Requires-Dist: fire
Requires-Dist: pytest
Requires-Dist: black
Requires-Dist: matplotlib
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'

# Lyft Dataset SDK

Welcome to the devkit for the [Lyft Level 5 AV dataset](https://level5.lyft.com/dataset/)! This devkit shall help you to visualise and explore our dataset.


## Release Notes
This devkit is based on a version of the [nuScenes devkit](https://www.nuscenes.org).

## Getting Started

### Installation

If you have a Python >=3.6 environment set up and Pip installed, you can simply run
```
pip install -U git+https://github.com/lyft/nuscenes-devkit
```

### Dataset Download
Go to <https://level5.lyft.com/dataset/> to download the Lyft Level 5 AV Dataset.

### Tutorial and Reference Model
Check out the [tutorial and reference model README](notebooks/README.md).

![](notebooks/media/001.gif)


# Dataset structure

The dataset contains of json files:

1. `scene.json` - 25-45 seconds snippet of a car's journey.
2. `sample.json` - An annotated snapshot of a scene at a particular timestamp.
3. `sample_data.json` - Data collected from a particular sensor.
4. `sample_annotation.json` - An annotated instance of an object within our interest.
5. `instance.json` - Enumeration of all object instance we observed.
6. `category.json` - Taxonomy of object categories (e.g. vehicle, human).
7. `attribute.json` - Property of an instance that can change while the category remains the same.
8. `visibility.json` - (currently not used)
9. `sensor.json` - A specific sensor type.
10. `calibrated_sensor.json` - Definition of a particular sensor as calibrated on a particular vehicle.
11. `ego_pose.json` - Ego vehicle poses at a particular timestamp.
12. `log.json` - Log information from which the data was extracted.
13. `map.json` - Map data that is stored as binary semantic masks from a top-down view.


With [the schema](schema.md).

# Data Exploration Tutorial

To get started with the Lyft Dataset SDK, run the tutorial using [Jupyter Notebook](notebooks/tutorial_lyft.ipynb).

