A dynamic WildFires Dataset Generator for Artificial Intelligence serving WildFires Detection.
This project requires conda to be installed. You can find conda's documentation for installation here
Create a virtual environment (venv):
conda create -p .venv python
Initialize conda (if not done already):
conda init
Activate the environment:
conda activate ./.venv
Execute the following command to install all required packages (except pyhdf):
pip install -r requirements.txt
Then execute the following command to install pyhdf:
conda install -c conda-forge pyhdf
That's it for the installation.
The project was initially developped for MySQL, so we recommand using it for this project. To configure the database for this project, add a .env file in the main folder, copy attributes from .env.example into .env. For the DATABASE_URL, it should be like this:
DATABASE_URL=mysql+mysqlconnector://<user>:<password>@<host>:<port>/<database_name>
Every <attribute> should be replaced according to your database and where it's hosted.
After successfully configuring the database, you can populate it by executing the populate_database.py script. Ex:
python populate_database.py --lat_min=36 --lat_max=36.5 --lng_min=1 --lng_max=1.5 --start_date=1/7/2015 --end_date=10/7/2015
You can see more details about this sccript by executing:
python populate_database.py -h
First make sure that the database is online and just run the run.py file, that will run the flask server:
python run.py
Access the user web portal:
http://localhost:5000