Authors
Eshwaran Venkat & Tigran Poladian under Uri Schonfeld
python@3.10
conda
environment
Assuming conda
and python
are available and are in PATH
(accessible from anywhere on the system), run the following commands:
conda env create --name leafydex python=3.10 -y
conda activate leafydex
conda install -c anaconda ipykernel -y
python -m ipykernel install --user --name=leafydex
git clone https://github.com/cricksmaidiene/leafydex
cd leafydex
python -m pip install -r requirements.txt
python -m pip install -e .
- Go to the top-right corner of the repository and click
Code
- Start a github codespaces on the
main
branch - append
?editor=jupyter
of the codespaces URL to start exploring on Jupyterlab
Add Kaggle API key to
/credentials
(all files within this directory are ignored by git)
Instructions for UNIX-based systems (or Codespaces). Windows may require different commands
mkdir ~/.kaggle #ignore if directory already present
chmod 600 credentials/kaggle.json
cp credentials/kaggle.json ~/.kaggle/kaggle.json
python -m pip install kaggle
kaggle datasets download -d csafrit2/plant-leaves-for-image-classification -p ./data/raw
unzip data/raw/plant-leaves-for-image-classification.zip -d data/raw
rm data/raw/plant-leaves-for-image-classification.zip
- Get API key from
https://www.kaggle.com/account
- Review Kaggle API Docs
-
Practices: Please read practices.md for details on how to set up this project beyond the base installation.
-
Structure: Please read structure.md to see the file structure of this project
-
Execution Trail: Please read trail.md to see the trail of execution across multiple files
Project structure based on the cookiecutter conda data science project template.