{ "info": { "author": "PyroNear Contributors", "author_email": "pyronear.d4g@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Artificial Intelligence", "Topic :: Scientific/Engineering :: Mathematics", "Topic :: Software Development", "Topic :: Software Development :: Libraries", "Topic :: Software Development :: Libraries :: Python Modules" ], "description": "![PyroNear Logo](docs/source/_static/img/pyronear-logo-dark.png)\n\n

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\n\n\n\n# PyroNear: early wildfire detection\n\nThe increasing adoption of mobile phones have significantly shortened the time required for firefighting agents to be alerted of a starting wildfire. In less dense areas, limiting and minimizing this duration remains critical to preserve forest areas.\n\nPyroNear aims at offering an wildfire early detection system with state-of-the-art performances at minimal deployment costs.\n\n\n\n## Table of Contents\n\n* [Getting Started](#getting-started)\n * [Prerequisites](#prerequisites)\n * [Installation](#installation)\n* [Usage](#usage)\n* [References](#references)\n* [Documentation](#documentation)\n* [Contributing](#contributing)\n* [Credits](#credits)\n* [License](#license)\n\n\n\n## Getting started\n\n### Prerequisites\n\n- Python 3.6 (or more recent)\n- [pip](https://pip.pypa.io/en/stable/)\n\n### Installation\n\nUse pip to install the package from git\n\n```shell\npip install git+https://github.com/frgfm/PyroNear@master\n```\n\n\n\n## Usage\n\n### datasets\n\nAccess all PyroNear datasets just like any `torchvision.datasets.VisionDataset`:\n\n```python\nfrom pyronear.datasets import OpenFire\ndataset = OpenFire('./data', download=True)\n```\n\n\n\n## References\n\nYou are free to use any training script, but some are already provided for reference. In order to use them, install the specific requirements and check script options as follows:\n\n```shell\npip install -r references/classification/fastai/requirements.txt\npython references/classification/fastai/train.py --help\n```\n\nYou can then run the script with your own arguments:\n\n```shell\npython references/classification/fastai/train.py --data-path ./data --lr 3e-3 --epochs 4 --pretrained --deterministic\n```\n\n*Please note that most tasks are provided with two training scripts (and their `requirements.txt`): one using [fastai](https://github.com/fastai/fastai) and the other without it.*\n\n\n\n## Documentation\n\nThe full package documentation is available [here]() for detailed specifications. The documentation was built with [Sphinx](sphinx-doc.org) using a [theme](github.com/readthedocs/sphinx_rtd_theme) provided by [Read the Docs](readthedocs.org).\n\n\n\n## Contributing\n\nPlease refer to `CONTRIBUTING` if you wish to contribute to this project.\n\n\n\n## Credits\n\nThis project is developed and maintained by the repo owner and volunteers from [Data for Good](https://dataforgood.fr/).\n\n\n\n## License\n\nDistributed under the MIT License. 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