🛰️ Official repository of paper "RemoteCLIP: A Vision Language Foundation Model for Remote Sensing" (IEEE TGRS)

SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Model

Changes to Captions: An Attentive Network for Remote Sensing Change Captioning

[CVPR 2024 🔥] GeoChat, the first grounded Large Vision Language Model for Remote Sensing

Master programming by recreating your favorite technologies from scratch.

a state-of-the-art-level open visual language model | 多模态预训练模型

Must-have resource for anyone who wants to experiment with and build on the OpenAI vision API 🔥

Images to inference with no labeling (use foundation models to train supervised models).

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

Fine-tuning OpenAI CLIP Model for Image Search on medical images

A WebGL viewer for UMAP-clustered images

Set-of-Mark Prompting for GPT-4V and LMMs

Datasets for remote sensing images (Paper:Exploring Models and Data for Remote Sensing Image Caption Generation)

[ACM MM23] CLIP-Count: Towards Text-Guided Zero-Shot Object Counting

❄️🔥 Visual Prompt Tuning [ECCV 2022] https://arxiv.org/abs/2203.12119

[ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"

A Python package for using Artificial Intelligence (AI) with geospatial data

Simplex Random Feature attention, in PyTorch

A PyTorch-based tool to generate clouds for satellite images.

Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: …

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

Port of OpenAI's Whisper model in C/C++

LLM inference in C/C++

Label Studio is a multi-type data labeling and annotation tool with standardized output format

Repository for machine learning and remote sensing pipeline described in Kruitwagen, L., Story, K., Friedrich, J, et. al. (2019) , used to produce a global inventory of utility-scale solar photvolt…

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

ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels

The database for modern applications. Common use cases: knowledge graphs for AI, fraud detection, personalization, and search. Built and maintained by @HypermodeInc.