camera-traps 话题在 GitHub 上没有填写简介，这里按 Star 数汇总最相关的热门仓库。
Microsoft AI for Good Lab — Biodiversity research hub. Open-source AI models, edge devices, and tools for biodiversity monitoring and conservation. Your source for MegaDetector, SPARROW, PytorchWildlife, Bioacoustics, and more.
MegaDetector是一款AI模型，帮助保护人员减少花在无聊相机陷阱图像上的时间。
Everything I know about machine learning and camera traps.
A Python package for identifying hundreds of kinds of animals, training custom models, and estimating distance from camera trap videos and images
This repo contains code+pre-trained models for extracting information from camera-trap images. The pre-trained models have been trained on the Snapshot Serengeti dataset.
SPARROW — Solar-Powered Acoustic and Remote Recording Observation Watch. An AI-enabled edge device for biodiversity monitoring with camera-trap imaging and bioacoustic recording. By Microsoft AI for Good Lab.
Deep learning computer vision for classifying wildlife in camera trap images
MegaDetector V6 — Microsoft AI for Good Lab's open-source model that detects animals, people, and vehicles in camera-trap images, filtering blanks to speed wildlife research.
Detect Animals, Humans and Vehicles in Camera Trap Imagery. Powered by MegaDetector v5.
An online toolset to manage and analyze data collected from insect camera traps for research and conservation efforts.
AI-Powered Camera-Trap Image Processing
Save 99% of Your Time Classifying Camera-Trap Footage. Completely Free.
ecoSecrets is a web application which enables users to manage their camera traps data
Distance Estimation for Estimating Animal Abundance
Bounding Box Editor and Exporter
R package containing functions to help manage and analyze environmental sensor data to and from WildTrax (wildtrax.ca)
Automated Camera Trapping Identification and Organization Network (ACTION)
📷🦔 CamTrapML Python Library for Detecting, Classifying, and Analysing Camera Trap Imagery.
R package to explore and visualize Camera Trap Data Packages (Camtrap DP)
PyTorch-Wildlife — The Microsoft collaborative deep learning framework for conservation. Multi-task computer vision and bioacoustic models for camera-trap detection, species classification, and biodiversity monitoring. Maintained by Microsoft AI for Good Lab.