PyTorch Wildlife: a Collaborative Deep Learning Framework for Conservation.
Simplify camera trap image analysis with ML species recognition models based around the MegaDetector model
MegaDetector is an AI model that helps conservation folks spend less time doing boring things with camera trap images.
A desktop application that makes using MegaDetector's model easier
Detect Animals, Humans and Vehicles in Camera Trap Imagery. Powered by MegaDetector v5.
MegaDetector models served over FastAPI & visualized with Streamlit
The Image Level Label to Bounding Box (IL2BB) pipeline automates the generation of labeled bounding boxes by leveraging an organization’s previous labeling efforts.
Docker image for running the MegaDetector v4 camera-trap object detection model.
Instructions to export megadetector v5 from PyTorch to ONNX and tools to use the exported model.
Guidance for image-based identification of traded animals in highly occluded contexts.
Classifiying tigers (and other species) in camera trap images using ML, open data, open source tools and free compute resources
Aplicación de estrategias de deep-learning para la detección de animales en imágenes de fototrampeo
Filter cameras traps images with megadetector on a cluster
Add a description, image, and links to the megadetector topic page so that developers can more easily learn about it.
To associate your repository with the megadetector topic, visit your repo's landing page and select "manage topics."