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Starred repositories
MegaDetector is an AI model that helps conservation folks spend less time doing boring things with camera trap images.
Code for training and evaluating a detector for the USGS Izembek goose survey dataset
Simplify camera trap image analysis with ML species recognition models based around the MegaDetector model
An implementation of a deep learning recommendation model (DLRM)
Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activelo…
A collection of boilerplate code for starting data science, analysis, or engineering projects.
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
GeoImageNet Examples: Sample Models and Packaging Procedures
Abstracts Megadetector's model with a standalone, generalised API that can be built on top of. Can be used as a script, or wrapped as CLI tool or a GUI.
OSMnx is a Python package to easily download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap.
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Land cover mapping of the Orinoquía region in Colombia, in collaboration with Wildlife Conservation Society Colombia. An #AIforEarth project
Trust & Safety tools for working together to fight digital harms.
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
Crop type mapping of small holder farms in Ghana, and South Sudan
Integrates Google Earth Engine and QGIS using Python API
A basic framework for your PyTorch projects
Open-source JavaScript charting library behind Plotly and Dash
Python language bindings for smartnoise-core.
Implementation of "Overcoming catastrophic forgetting in neural networks" in Tensorflow
comparative evaluation of incremental machine learning methods