drivendataorg/zamba

A Python package for identifying hundreds of kinds of animals, training custom models, and estimating distance from camera trap videos and images # Zamba user-images.githubuserconte… > *Zamba* means "forest" in Lingala, a Bantu language spoken throughout the Democratic Republic of the Congo and the Republic of the Congo. **`zamba` is a tool built in Python that uses machine learning and computer vision to automatically detect and classify animals in camera trap _images_ and _videos_.** You can use `zamba` to: - Identify which species appear in each image or video - Filter out blank images or videos - Create your own custom models that identify your species in your habitats - Estimate the distance between animals in the frame and the video camera - And more! 🙈 🙉 🙊 The official video models in `zamba` can identify blank videos (where no animal is present) along with 32 species common to Africa and 11 species common to Europe. The official image models can identify 178 species from throughout the world. Users can also finetune models using their own labeled images and videos to then make predictions for new species and/or new ecologies. `zamba` can be used both as a command-line tool and as a Python package. It is also available as a user-friendly website application, Zamba Cloud. We encourage people to share their custom models trained with Zamba. If you train a model and want to make it available, please add it to the Model Zoo Wiki for others to be able to use! Visit zamba.drivendata.org for full documentation and tutorials. ## Installing `zamba` We recommend uv for installing Python packages and managing environments. Install uv, then ensure you have: * Python >= 3.11 * FFmpeg > 4.3 and < 5 (only needed for video workflows) Then install the extras you need with uv. **We recommend only installing one or the other depending on your use case.** ```console # For video workflows uv pip install zamba[video] # For image workflows uv pip install zamba[image] # For both uv pip install zamba[video,image] ``` You …