ML project for wildfire smoke detection. Follow this article as a detailed guide.

This project is connected to a repository on DagsHub.

DagsHub is a GitHub for Machine Learning projects. It eases MLOps practices by enabling data scientists and machine learning engineers to version their data, models, experiments, and code, through its integration with DVC and MLflow.

1. Clone the project:

git clone https://github.com/RihabFekii/

2. Set up a virtual python environment, by running the following commands:

make env
source env/bin/activate .

3. Install requirements, by running this command:

make requirements

4. Pull the data

dvc pull

1. You can experiment with the different models of YOLOv8 and edit its hyperparameters by editing the params.yaml file.

2. Since the data pipeline is created with dvc, you can easily reproduce experiments by runing:

dvc exp run 

3. Visualize experiments by running:

dvc exp show