Popular GitHub Repositories for Mapbox Satellite Oss

:satellite: Simple and ready-to-use tutorials for TensorFlow

Techniques for deep learning with satellite & aerial imagery

Mycroft Core, the Mycroft Artificial Intelligence platform.

:satellite: All You Need to Know About Deep Learning - A kick-starter

?? List of satellite image training datasets with annotations for computer vision and deep learning

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

An open source library and framework for deep learning on satellite and aerial imagery.

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

Analysis, Comparison, Trends, Rankings of Open Source Software, you can also get insight from more than 7 billion with natural language (powered by OpenAI). Follow us on Twitter: https://twitter.com/ossinsight

[ICML'24] Magicoder: Empowering Code Generation with OSS-Instruct

LLM powered fuzzing via OSS-Fuzz.

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image and UAV image segmentation.

基于chatgpt-next-web，增加了midjourney绘画功能，支持mj-plus的ai换脸和局部重绘，接入了stable-diffusion，支持oss，支持接入fastgpt知识库，支持suno，支持luma。支持dall-e-3、gpt-4-vision-preview、whisper、tts等多模态模型，支持gpt-4-all，支持GPTs商店。新增加了支持后台管理的版本，包括登录注册，平台模型apikey管理，套餐管理，消息保存等。

A curated list of resources focused on Machine Learning in Geospatial Data Science.

kani (カニ) is a highly hackable microframework for chat-based language models with tool use/function calling. (NLP-OSS @ EMNLP 2023)

TernausNetV2: Fully Convolutional Network for Instance Segmentation

Pytorch implementation of ResUnet and ResUnet ++

[IGARSS'22]: A Transformer-Based Siamese Network for Change Detection

This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic segmentation, and instance segmentation tasks. These datasets are ideal for applications in computer vision, machine learning, remote sensing, and maritime analysis.

Data Preparation for Satellite Machine Learning