Popular GitHub Repositories for Structure Similarity

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 80+ languages.

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database?.

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Retrieval and Retrieval-augmented LLMs

Best Practices, code samples, and documentation for Computer Vision.

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!

Semantic cache for LLMs. Fully integrated with LangChain and llama_index.

open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ???

text2vec, text to vector. 文本向量表征工具，把文本转化为向量矩阵，实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型，开箱即用。

搜索所有中文NLP数据集，附常用英文NLP数据集

Photogrammetric Computer Vision Framework

.NET, Angular, Clean Architecture, Clean Code, SOLID Principles, KISS Principle, DRY Principle, Fail Fast Principle, Common Closure Principle, Common Reuse Principle, Acyclic Dependencies Principle, Mediator Pattern, Result Pattern, Folder-by-Feature Structure, Separation of Concerns

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

Top2Vec learns jointly embedded topic, document and word vectors.