MyQ develops print management solutions offering secure, user-friendly experience across two product lines. MyQ X is a robust, feature-rich solution for small to enterprise organizations in three editions: Smart, Enterprise, and Ultimate. MyQ Roger is a public cloud-based solution designed for cloud-first environment supporting hybrid and remote workplaces.
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TinyPNG (by Tinify) is a free image optimization solution trusted by developers, designers, and businesses worldwide. Using smart lossy compression, it reduces JPEG, PNG, WebP, and AVIF file sizes by up to 80% without sacrificing quality. Accelerating load times, boosting SEO, and lowering bandwidth costs.
Easily compress, convert, and resize images through a user-friendly web interface or integrate with your stack via our robust API. Tinify also offers an image CDN to ensure fast, reliable global delivery of optimized images. Official SDKs are available for Python, Node.js, PHP, Java, Ruby, and .NET. We also offer a WordPress plugin and a growing ecosystem of third-party integrations.
Tinify eliminates complexity, no confusing settings, no guesswork. Whether you're optimizing a small catalog or managing millions of files, it delivers consistent, scalable results. Every plan starts with a generous free tier, and our responsive support team is ready to assist.
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ByteScout Text Recognition SDK
Text recognition refers to the process of identifying and converting images or documents, such as PDFs, that contain typed or printed text into a digital format that computers can interpret, primarily through Optical Character Recognition (OCR) techniques bolstered by Machine Learning and Artificial Intelligence. This innovative technology simplifies traditionally laborious tasks like extracting information from various documents, including driver's licenses, passports, invoices, and bank statements. Users can specify particular rectangular sections of an image for analysis, allowing for adjustments like rotating and flipping the image as necessary. By merging cutting-edge technologies with user-friendly tools available on our website, we strive to provide SDKs that cater to your unique needs. Furthermore, for those seeking a more in-depth exploration, our extensive tutorials, source codes, and documentation offer valuable insights into the mechanics of our solutions. We firmly believe that equipping users with knowledge is just as important as supplying the necessary tools, fostering a well-rounded understanding of the capabilities at their disposal. Ultimately, our goal is to enhance user experience and empower individuals to maximize the full potential of text recognition technology.
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GLM-OCR
GLM-OCR represents a cutting-edge multimodal optical character recognition solution and an open-source framework that stands out by providing accurate, efficient, and comprehensive document understanding through the seamless integration of text and visual components within a unified encoder-decoder framework inspired by the GLM-V series. It incorporates a visual encoder that has been pre-trained on a vast array of image-text datasets and features an efficient cross-modal connector that feeds data into a GLM-0.5B language decoder. The system is equipped with capabilities for detecting layouts, recognizing multiple areas simultaneously, and generating structured outputs that accommodate a variety of content types, such as text, tables, formulas, and complex real-world document formats. Moreover, it utilizes Multi-Token Prediction (MTP) loss alongside advanced full-task reinforcement learning methods to improve training efficiency, enhance recognition accuracy, and foster better generalization across different tasks, ultimately leading to outstanding results in significant document understanding challenges. By employing this novel approach, GLM-OCR not only establishes new performance standards but also paves the way for future innovations in the realm of document analysis and understanding. As a result, it has the potential to revolutionize how documents are interpreted and processed in various applications.
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