Phyto Plankton Classification

This documentation belongs to the full phyto-plankton-classification repository.

It is the general project-level home for:

local CLI workflows
local DEEPaaS API workflows
notebook workflows
Docker usage
AI4OS and OSCAR deployment
project-level models, assets, and integration material

If you want package-focused installation, command explanations, and reusable package documentation, use the companion repository instead:

planktonclas package repo: https://github.com/woutdecrop/planktonclas

Home

This repository supports five main approaches:

package / local CLI usage through planktonclas
local API usage through DEEPaaS
notebook usage
Docker usage
AI4OS / OSCAR deployment

The important thing for new users is:

you do not have to use every workflow
these are alternative ways to use the same project and package
package-only details live in planktonclas

How To Read These Docs

Read the docs in this order:

Installation to decide how you want to set up or launch the project
Quickstart to choose your path
one of the numbered workflow pages below
Reference for project structure, outputs, and conventions

Use planktonclas for:

package installation
package command explanations
command-line workflow details
package-level API and notebook documentation

Workflow Pages

Python Usage is Option 1 and explains the package / local CLI path at a high level, then points to the fuller planktonclas docs
API Usage is Option 2 and explains the local API path in this repository
Notebooks is Option 3 and explains the notebook path in this repository
Docker and AI4OS / OSCAR are described in Installation and Quickstart as Options 4 and 5

Citation

If you use this project, please consider citing:

Decrop, W., Lagaisse, R., Mortelmans, J., Muñiz, C., Heredia, I., Calatrava, A., & Deneudt, K. (2025). Automated image classification workflow for phytoplankton monitoring. Frontiers in Marine Science, 12. https://doi.org/10.3389/fmars.2025.1699781

Contents

User Guide