A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper.

Scenic: A Jax Library for Computer Vision Research and Beyond

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

AVES: Animal Vocalization Encoder based on Self-Supervision

Code for paper "From Crowd to Herd Counting: How to Precisely Detect and Count African Mammals using Aerial Imagery and Deep Learning?"

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

Distance Estimation for Estimating Animal Abundance

Are They the Same Picture? Adapting Concept Bottleneck Models for Human-AI Collaboration in Image Retrieval accepted at IJCAI'24 and CV4Animals@CVPR'24

The Clay Foundation Model (in development)

Effortless data labeling with AI support from Segment Anything and other awesome models.

An Artificial Intelligence Wildlife Alert System Using 4G Camera Traps

The interactive graphing library for Python ✨ This project now includes Plotly Express!

Insect Identification in the Wild: The AMI Dataset

Estimate cyanobacteria density based on Sentinel-2 satellite imagery

WildlifeDatasets: An open-source toolkit for animal re-identification

YOLOv10: Real-Time End-to-End Object Detection

Python tools for geographic data

Web application for ecoacoustics that archives and organises soundscape collections, hosts reference recording collections, generates navigable sound spectrograms, and allows annotation of animal v…

Wildbook's Image Analysis (WBIA) backend service supporting machine learning for wildlife conservation

Computer Vision for the Greater Good

Data release for the ImageInWords (IIW) paper.

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.

Video / Image Annotation (Polygon, Semantic mask, Classification) with Python and Re3

Visual localization made easy with hloc

Showcasing various experiments.