Skip to main content

Datasets and models for wildfire detection in PyTorch

Project description

PyroNear Logo

Pyrovision: wildfire early detection

The 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.

Pyrovision aims at providing the means to create a wildfire early detection system with state-of-the-art performances at minimal deployment costs.

Table of Contents

Getting started


  • Python 3.6 (or more recent)
  • pip


You can install the latest release of the package using pypi as follows:

pip install pyrovision

or conda as follows:

conda install -c pyronear pyrovision


Python package

You can use the library like any other python package to detect wildfires as follows:

from pyrovision.datasets import OpenFire
dataset = OpenFire('./data', download=True)

Docker container

If you wish to deploy containerized environments, a Dockerfile is provided for you build a docker image:

docker build . -t <YOUR_IMAGE_TAG>


You 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:

pip install -r references/requirements.txt
python references/classification/ --help

You can then use the script to train tour model on one of our datasets:


Download Dataset from

This dataset is protected by a password, please contact us at

python WildFireLght/ --model rexnet1_0x --lr 1e-3 -b 16 --epochs 20 --opt radam --sched onecycle --device 0


You can also use out opensource dataset without password

python OpenFire/ --use-openfire --model rexnet1_0x --lr 1e-3 -b 16 --epochs 20 --opt radam --sched onecycle --device 0


The full package documentation is available here for detailed specifications. The documentation was built with Sphinx using a theme provided by Read the Docs.


Please refer to CONTRIBUTING if you wish to contribute to this project.


This project is developed and maintained by the repo owner and volunteers from Data for Good.


Distributed under the AGPLv3 License. See LICENSE for more information.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pyrovision, version 0.1.2
Filename, size File type Python version Upload date Hashes
Filename, size pyrovision-0.1.2-py3-none-any.whl (43.0 kB) File type Wheel Python version py3 Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page