A Python package for simulating the evolution of organisms.

A process to better define speciation

[ICCV 2025] Official PyTorch implementation for paper "TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation"

A predictive model to identify four species of bird from their vocalisations. It is my contribution to a Hackster competition.

Implementation of "Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution" [ECCV 2024]

A Noah's Ark for future generations.

Megalodon is an extensive library of all-that-is-to-sharks. It contains various shark datasets, a model zoo and pre-trained networks for various tasks.

python tools to get species data from various API, like IUCN Red List or Encyclopedia of Life.

Using a pre-trained model to identify plant and animal species

🐠 Set of functions to mine FishBase database by mainly using web scraping methods

Implementing a simple REST API to use a Beetle detector trained using Tensorflow Slim Library

🌐 Wrapper for OBIS API

An app developed in Python and Javascript to help ameture ornithologists to locate recently sighted birds based on a user inputed location

🐛 Wrapper for WoRMS Rest API

Python module used to download taxa for all bats from the IUCN Redlist and store in Excel.

This repository contains code to both model the lotka volterra equations and to find the parameters necessary to fit these equations to existing data sets. The lotka volterra equations can be used to model the interactions between two species, one predator, one prey, with respect to time and several variables.

Scripts used to produce ConSpeciFix analysis for arboviruses

In this program I took information from .csv files related to 'Biodiversity in National Parks' in the United States, and converted the given information into data that could be used to develop a graph of ratios of species. In this case, I had created a ratio comparing 'Non-Native Species per At Risk Species.'

Research Project Luca Nederhorst