PackageX OCR API turns any smartphone into an incredibly powerful universal label scanner. It can read every bit of text, including barcodes, QR codes and other information on the label.
Our OCR technology is the best in the industry. It uses proprietary algorithms and deep learning models to extract information from labels.
Our OCR API has been trained using information from more than 10 million labels. This allows for the highest scanning accuracy in the market, at over 95%.
Our technology can scan in low-light conditions and read labels from any angle.
Create your own OCR scanner app to eliminate pen-and-paper inefficiencies.
Our OCR scanner allows you to extract information from printed text or handwritten labels.
Our OCR software is trained using multilingual label data extracted in over 40 countries.
Detect and extract information from barcodes or QR codes.
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Foxit delivers a robust set of cloud-native APIs that enable organizations to automate and modernize document-driven workflows at scale. Built on flexible REST architecture, these APIs allow developers to seamlessly create, convert, extract, sign, and display documents within their own applications—improving efficiency while reducing manual processes.
The Foxit PDF Services API handles large-scale PDF processing, including conversion, extraction, optimization, and redaction. The Document Generation API streamlines the production of personalized PDFs and DOCX files using dynamic templates and live business data. The Foxit eSign API integrates secure, legally binding eSignature workflows with audit tracking and compliance capabilities. The PDF Embed API provides customizable in-app document viewing with support for annotations, forms, and secure user access.
Combined, Foxit APIs give enterprises a secure and scalable platform for digital document automation and workflow transformation.
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DeepSeek-OCR
DeepSeek-OCR is an open-source framework that focuses on Contexts Optical Compression, aimed at pushing the limits of visual-text compression and examining the role of vision encoders through an LLM-focused lens. This innovative model effectively compresses extensive contexts via optical 2D mapping, utilizing DeepEncoder as its primary engine and DeepSeek3B-MoE-A570M as the decoding mechanism. With a capacity to maintain low activations under high-resolution inputs, DeepEncoder achieves impressive compression ratios, allowing for a manageable number of vision tokens essential for understanding documents. The system is optimized for OCR and document parsing tasks related to images and PDFs, featuring inference options through vLLM or Transformers. Users have the flexibility to execute image OCR with streaming outputs, handle PDFs with high concurrency, or conduct batch evaluations for benchmarking purposes. Additionally, DeepSeek-OCR is capable of transforming documents into Markdown format, enabling free OCR without the constraints of layouts, parsing figures, providing detailed image descriptions, and pinpointing referenced text within images, thereby enhancing its utility across various applications. This versatility positions DeepSeek-OCR as a valuable tool for anyone needing advanced document processing capabilities.
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Docling
Docling is a user-friendly, self-sufficient, open-source toolkit licensed under MIT that facilitates the transformation of disorganized documents into structured data, thereby enhancing subsequent document and AI workflows. This versatile tool can interpret a wide array of document types, including PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, images, audio files, and even scanned documents using any preferred OCR engine. Docling proficiently identifies and processes various elements such as tables, formulas, reading sequences, bounding boxes, headers, footers, images, captions, code snippets, list items, paragraphs, and overall document architecture, which significantly aids in the searchability and integration of the extracted content into AI systems, retrieval-augmented generation, and agent-based applications. Furthermore, it allows for exporting the parsed output in formats like JSON, plain text, Markdown, HTML, and Doctags, thus providing developers with versatile options for their development pipelines and applications. By efficiently organizing and managing components based on reading sequence, Docling breaks down documents into manageable, continuous text segments, optimizing the processing experience.
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