Zamba (meaning "forest" in Lingala) is an open-source Python package that uses machine learning and computer vision to help automate time-intensive video processing tasks for wildlife monitoring, enabling researchers to focus on interpreting the content and using the results.

Zamba builds on the winning solution from the Pri-matrix Factorization challenge and includes multiple state-of-the-art, pretrained machine learning models for species and blank detection in different geographies. It can also be used to train custom models on new species and geographies based on user-provided labeled data.