Developed by Linh Ta, Bryan Heidorn, Jessica Guo, and David LeBauer
This repo contains scripts to process Phenocam canopy and ground images in order to better predict phenological processes (green up, brown down) for the EFI phenology competition.
You should have Anaconda or Miniconda installed, which should also include Python3.
Regardless of how you run the program, the scripts contained in this repository will require a few library to get set up. In here I will instruct you how to set up an environment in the running folder, so that the setting here does not affect your other project.
Navigate to the folder containing the code, type
conda create -p ./env python=3.7
It will create a Conda environment named env in the current folder.
Then anytime you want to use that environment, you can head into the folder and run
conda activate ./env
To deactivate the environment, type
conda deactivate
Then we should attach that environment to the Jupyter Notebook.
We will do it by installing ipykernel, type
pip3 install --user ipykernel
OR
python3 -m pip install virtualenv
Then to attach the environment to Jupyter Notebook, run
python3 -m ipykernel install --user --name=env
Everytime you want to run the notebook in the environment we set up, just click Kernel->Change Kernel-> Kernel Name
We need to install many package, run
conda install numpy
conda install pandas
conda install matplotlib
conda install scipy
conda install scikit-image
pip install -U scikit-learn
pip install opencv-python
```conda install jupyter notebook`