Showing 4 open source projects for "java image processing library"

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    OpenAI Go

    OpenAI Go

    The official Go library for the OpenAI API

    OpenAI Go is the official Go client library for accessing the OpenAI API. It enables developers to integrate OpenAI’s models and features into Go applications with a clean and idiomatic interface. The library provides support for a wide range of API endpoints including chat completions, assistants, embeddings, image generation, audio processing, and batch jobs. It includes built-in tools for handling authentication, managing API requests, and parsing structured responses. ...
    Downloads: 5 This Week
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  • 2
    QOR

    QOR

    Libraries written in Go abstracting features needed for business apps

    QOR is architected from the ground up to accelerate development and deployment of Content Management Systems, E-commerce Systems, and Business Applications. QOR is comprised of modules that abstract common features for such systems, such as a configurable and flexible back office, a content publishing system, a media library, and much more. We built QOR at The Plant to accelerate development for our clients, it is at the core of our engineering strategy, and we maintain it on an ongoing...
    Downloads: 3 This Week
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  • 3
    bimg

    bimg

    Go package for fast high-level image processing

    bimg is a Go image-processing library that exposes high-level operations through the fast libvips C library. It is designed to minimize memory use while processing images efficiently in production applications. Developers can resize, crop, rotate, zoom, watermark, convert, and manipulate image metadata through a compact API. JPEG, PNG, and WebP are supported natively, while properly configured libvips builds add formats such as TIFF, PDF, GIF, SVG, and AVIF. ...
    Downloads: 0 This Week
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  • 4
    smartcrop

    smartcrop

    smartcrop finds good image crops for arbitrary crop sizes

    smartcrop is an image processing library that automatically crops images to focus on the most visually important regions using content-aware algorithms. It analyzes images to detect areas of interest such as faces, edges, and high-contrast regions, ensuring that the cropped output retains meaningful content. The library is particularly useful for generating thumbnails or resizing images while preserving key visual elements.
    Downloads: 0 This Week
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