Showing 4 open source projects for "phase retrieval"

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  • 1
    turbovec

    turbovec

    A vector index built on TurboQuant, written in Rust with Python

    ...The project targets workloads where embedding search needs to be compact, efficient, and practical to integrate into Python applications. It avoids a separate training phase for the quantizer, which can simplify setup compared with systems that require codebook learning. TurboVec is useful for developers building retrieval, ranking, semantic search, recommendation, or AI memory systems. Its main value is combining Rust performance with a Python-facing workflow for modern vector search experiments and applications.
    Downloads: 2 This Week
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  • 2
    FinalRecon

    FinalRecon

    All-in-one Python web reconnaissance tool for fast target analysis

    FinalRecon is an all-in-one web reconnaissance tool written in Python that helps security professionals gather information about a target website quickly and efficiently. It combines multiple reconnaissance techniques into a single command-line utility so users do not need to run several separate tools to collect similar data. FinalRecon focuses on providing a fast overview of a web target while maintaining accuracy in the collected results. It includes modules for gathering server...
    Downloads: 1 This Week
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  • 3
    This package includes a collection of MATLAB files which are designed to: 1. Given a calibration scan of the image of a point emitter with an engineered point spread function (PSF), 2. Perform a phase retrieval algorithm based on maximum likelihood estimation (MLE) of a phase aberration term which is added to the theoretical pupil function of the imaging system. 3. Use the phase-retrieved pupil function to perform single-emitter localization. Accompanying publication available here: https://doi.org/10.1364/OE.25.007945
    Downloads: 0 This Week
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  • 4
    NuMarkdown-8B-Thinking

    NuMarkdown-8B-Thinking

    Reasoning-powered OCR VLM for converting complex documents to Markdown

    NuMarkdown-8B-Thinking is the first reasoning OCR vision-language model (VLM) designed to convert documents into clean Markdown optimized for retrieval-augmented generation (RAG). Built on Qwen 2.5-VL-7B and fine-tuned with synthetic Doc → Reasoning → Markdown examples, it generates thinking tokens before producing the final Markdown to better handle complex layouts and tables. It uses a two-phase training process: supervised fine-tuning (SFT) followed by reinforcement learning (GRPO) with a layout-centric reward for accuracy on challenging documents. ...
    Downloads: 0 This Week
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