This project was created for wildfire smoke detection analysis, and aims to improve upon a smoke detection model, SmokeyNet, originally built by the San Diego Supercomputer Center at UCSD.
Note: Processed data may change over time depending on latest camera/weather station updates and if the configured timeframe is changed.
- Ensure dependencies installed:
- python3
-
With git installed, clone project:
git clone git@github.com:shaneluna/smokeynet-api.gitNote: You may need to setup an ssh key if first time using git
-
Change directory into cloned repo:
cd smokeynet-api -
Create a virtual environment:
python -m venv venv -
Start virutal environment:
Linux & Mac:source venv/bin/activateWindows:
./venv/Scripts/activate -
Install requirements:
pip install -r requirements.txt -
Run the following to fix jupyter lab code formatter:
jupyter server extension enable --py jupyterlab_code_formatter
-
All folder names + filenames should be lowercase
- 1 exception is for README files
-
All folder names + filesnames should be snakecase
-
Required notebooks for data getting/processing should have #_ prefix
I.e. 1_process_camera_metadata.ipynb -
Save prefix 0_ for notebooks that retrieve initial raw data
I.e. 0_get_camera_metadata.ipynb
- black python formatting
VS Code:
Code > Preferences > Settings > Search python formatting provider > Select black > Search format on save > Check box for Editor: Format on Save
JupyterLab:
JupyterLab Code Formatter has beeng added by default with black and isort formatting.
Make sure to update on save options within JupyterLab: Settings > Advanced Settings Editor > JSON Settings Editor > Jupyterlab Code Formatter > Add the following to User Preferences:
{ "formatOnSave": true }