Earth observation tools for Meta AI Segment Anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Fractional Cover

PyTorch implementation of U-TAE and PaPs for satellite image time series panoptic segmentation.

Detect field boundaries using satellite imagery.

Python code for the DECODE method and mxnet code for Fractal ResUNet

style transfer web app [FastAPI + streamlit + Docker]

A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification

Open geospatial work to support health systems' capacity (providers, supplies, ventilators, beds, meds) to effectively care for rapidly growing COVID19 patient needs

Most popular metrics used to evaluate object detection algorithms.

Earth observation processing framework for machine learning in Python

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

Landlab codebase, wiki, and tests

Using computer vision to detect if bike lanes are blocked

List of satellite imagery datasets with annotations for computer vision and deep learning

Docker container for running JUPYTER Notebook within an ANACONDA environment, exploiting NVIDIA-DOCKER for GPUs

Buscombe & Ritchie (2018) Landscape Classification with Deep Neural Networks. Geosciences 2018, 8(7), 244