Showing 7 open source projects for "database"

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  • 1
    DeepCamera

    DeepCamera

    Open-Source AI Camera. Empower any camera/CCTV

    ...SharpAI yolov7_reid is an open-source Python application that leverages AI technologies to detect intruders with traditional surveillance cameras. The source code is here It leverages Yolov7 as a person detector, FastReID for person feature extraction, Milvus the local vector database for self-supervised learning to identify unseen persons, Labelstudio to host images locally and for further usage such as label data and train your own classifier. It also integrates with Home-Assistant to empower smart homes with AI technology.
    Downloads: 16 This Week
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  • 2
    SuperDuperDB

    SuperDuperDB

    Integrate, train and manage any AI models and APIs with your database

    Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. ...
    Downloads: 0 This Week
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  • 3
    OpenMLDB

    OpenMLDB

    OpenMLDB is an open-source machine learning database

    OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference. OpenMLDB is an open-source machine learning database that is committed to solving the data and feature challenges. OpenMLDB has been deployed in hundreds of real-world enterprise applications. It prioritizes the capability of feature engineering using SQL for open-source, which offers a feature platform enabling consistent features for training and inference. ...
    Downloads: 0 This Week
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  • 4
    Superduper

    Superduper

    Superduper: Integrate AI models and machine learning workflows

    ...This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data.
    Downloads: 0 This Week
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  • 5
    Embedding Studio

    Embedding Studio

    Framework which allows you transform your Vector Database

    Embedding Studio is a framework that transforms vector databases into feature-rich search engines. It leverages embeddings to enhance search capabilities, enabling more accurate and context-aware retrieval of information. Embedding Studio supports various data types and integrates seamlessly with existing databases, providing tools for fine-tuning and optimizing embeddings to suit specific application needs.
    Downloads: 0 This Week
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  • 6
    BrowserAI

    BrowserAI

    Run local LLMs like llama, deepseek, kokoro etc. inside your browser

    BrowserAI is a cutting-edge platform that allows users to run large language models (LLMs) directly in their web browser without the need for a server. It leverages WebGPU for accelerated performance and supports offline functionality, making it a highly efficient and privacy-conscious solution. The platform provides a developer-friendly SDK with pre-configured popular models, and it allows for seamless switching between MLC and Transformer engines. Additionally, it supports features such as...
    Downloads: 0 This Week
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  • 7
    EvaDB

    EvaDB

    Database system for building simpler and faster AI-powered application

    Over the last decade, AI models have radically changed the world of natural language processing and computer vision. They are accurate on various tasks ranging from question answering to object tracking in videos. To use an AI model, the user needs to program against multiple low-level libraries, like PyTorch, Hugging Face, Open AI, etc. This tedious process often leads to a complex AI app that glues together these libraries to accomplish the given task. This programming complexity prevents...
    Downloads: 0 This Week
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