BedantaGautom/Wildfire-Detection-App

Forest Fire Detection Application Using Ultralytics YOLOv8.

FOR TRAINING THE MODEL –

1. Open the desired IDE or notebook and create a new Python virtual environment.

python -m venv .venv

2. Download and install PYTORCH and CUDA versions compatible with the system in the environment.

!pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

3. Import torch and check whether CUDA detects the device's GPU.

import torch

torch.cuda.is_available()

print(torch.cuda.get_device_name(0))

4. Install ULTRALYTICS and run the code to train the model and test the model.

!pip install ultralytics

FOR DEPLOYING AND RUNNING THE WEB APP –

1. Install the necessary packages from requirements.txt.

%pip install requirements.txt.

2. Create a file named [NAME].py and write the code to deploy the web app.
3. Run the Streamlit web app.

streamlit run [NAME].py

4. The web app can be deployed in Streamlit cloud service by uploading the code in the GitHub repository.