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    "info": {
        "author": "Vladimir Iglovikov",
        "author_email": "",
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        "classifiers": [
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# Lyft Dataset SDK\n\nWelcome 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.\n\n\n## Release Notes\nThis devkit is based on a version of the [nuScenes devkit](https://www.nuscenes.org).\n\n## Getting Started\n\n### Installation\n\nYou can use pip to install [lyft-dataset-sdk](https://pypi.org/project/lyft-dataset-sdk/):\n```bash\npip install -U lyft_dataset_sdk\n```\n\nIf you want to get the latest version of the code before it is released on PyPI you can install the library from GitHub:\n\n```bash\npip install -U git+https://github.com/lyft/nuscenes-devkit\n```\n\n### Dataset Download\nGo to <https://level5.lyft.com/dataset/> to download the Lyft Level 5 AV Dataset.\n\n\nThe dataset is also availible as a part of the [Lyft 3D Object Detection for Autonomous Vehicles Challenge](https://www.kaggle.com/c/3d-object-detection-for-autonomous-vehicles).\n\n### Tutorial and Reference Model\nCheck out the [tutorial and reference model README](notebooks/README.md).\n\n![](notebooks/media/001.gif)\n\n\n# Dataset structure\n\nThe dataset contains of json files:\n\n1. `scene.json` - 25-45 seconds snippet of a car's journey.\n2. `sample.json` - An annotated snapshot of a scene at a particular timestamp.\n3. `sample_data.json` - Data collected from a particular sensor.\n4. `sample_annotation.json` - An annotated instance of an object within our interest.\n5. `instance.json` - Enumeration of all object instance we observed.\n6. `category.json` - Taxonomy of object categories (e.g. vehicle, human).\n7. `attribute.json` - Property of an instance that can change while the category remains the same.\n8. `visibility.json` - (currently not used)\n9. `sensor.json` - A specific sensor type.\n10. `calibrated_sensor.json` - Definition of a particular sensor as calibrated on a particular vehicle.\n11. `ego_pose.json` - Ego vehicle poses at a particular timestamp.\n12. `log.json` - Log information from which the data was extracted.\n13. `map.json` - Map data that is stored as binary semantic masks from a top-down view.\n\n\nWith [the schema](schema.md).\n\n# Data Exploration Tutorial\n\nTo get started with the Lyft Dataset SDK, run the tutorial using [Jupyter Notebook](notebooks/tutorial_lyft.ipynb).\n\n# Contributing\nWe would be happy to accept issue reports and pull requests from the community.\n\nFor creating pull requests follow our [contributing guide](docs/CONTRIBUTING.md). \n\n",
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        "license": "Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)",
        "maintainer": "",
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        "package_url": "https://pypi.org/project/lyft-dataset-sdk/",
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