Table of contents

  1. Supported platforms and dependencies
  2. Install via a package manager
    1. Conda
    2. PyPI
  3. Installing PlantCV for contributors

Supported platforms and dependencies

  • Linux 64-bit, x86 processors
  • macOS x86 (Intel) and M (ARM) processors
  • Windows 64-bit, x86 processors

PlantCV requires Python (tested with versions 3.8, 3.9, and 3.10) and these Python packages. Additionally, we recommend installing JupyterLab.

Install via a package manager


We recommend installing PlantCV in a virtual environment, which is a self-contained Python environment that includes PlantCV and its dependencies. Virtual environments are used to avoid conflicts between packages and can increase the reproducability of your work by isolating package versions for specific projects.

Stable releases of PlantCV are available through both the Python Package Index (PyPI) and conda through the conda-forge channel.


First install conda if you do not already have it. We recommend using the Miniconda, but the full Anaconda distribution will also work.

conda create -n plantcv -c conda-forge plantcv

Or with optional (but recommended) dependencies:

conda create -n plantcv -c conda-forge plantcv jupyterlab ipympl nodejs


pip install plantcv

Or with optional (but recommended) dependencies:

pip install plantcv jupyterlab ipympl

Installing PlantCV for contributors

Before getting started, please read our contributor guidelines and code of conduct.

You can build PlantCV from the source code if you are a developer or want the absolute latest version available. As noted above, we recommend installing PlantCV in a virtual environment. We will outline how to do this using conda. You will also need a GitHub account. You will need to clone the PlantCV repository from GitHub before getting started.

To set up your environment, follow these steps in your command-line terminal:

# Enter the PlantCV directory
cd plantcv

# Create a conda environment named "plantcv" (or whatever you like) and automatically install the developer dependencies
conda env create -n plantcv -f environment.yml

# Activate the plantcv environment (you will have to do this each time you start a new session)
conda activate plantcv

# Install PlantCV in editable mode so that it updates as you work on new features/updates
pip install -e .