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JSON: No Smile Format Specification: Yes No Yes Partial (JSON Schema Proposal, other JSON schemas/IDLs) Partial (via JSON APIs implemented with Smile backend, on Jackson, Python) — SOAP: W3C: XML: Yes W3C Recommendations: SOAP/1.1 SOAP/1.2: Partial (Efficient XML Interchange, Binary XML, Fast Infoset, MTOM, XSD base64 data) Yes Built-in id ...
hOCR is an open standard of data representation for formatted text obtained from optical character recognition (OCR). The definition encodes text, style, layout information, recognition confidence metrics and other information using Extensible Markup Language (XML) in the form of Hypertext Markup Language (HTML) or XHTML.
Download as PDF; Printable version; In other projects ... This allows developers to store JSON data directly in a relational database without having to convert it to ...
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The SPDX 2.x standard defines an SBOM document, which contains SPDX metadata about software. The document itself can be expressed in multiple formats, including JSON, YAML, RDF/XML, tag–value, and spreadsheet. Each SPDX document describes one or more elements, which can be a software package, a specific file, or a snippet from a file.
For example, if your file contains the right type of data (such as text), but in the wrong format, you may have to create a new file and enter the text manually in the proper format in order to use that program. Various file conversion programs exist because people need to convert their files to a different format in order to use them effectively.
pdffonts – lists the fonts used in a PDF; pdfimages – extract all embedded images at native resolution from a PDF; pdfinfo – list all information of a PDF; pdfseparate – extract single pages from a PDF; pdftocairo – convert single pages from a PDF to vector or bitmap formats using cairo; pdftohtml – convert PDF to HTML format ...
Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.