Extract text, tables, and document structure from images into 50 conversion formats . Conversion Complete! Your file is ready. Review the generated content before using it in an important workflow. Select or drag an image. 2. AI Processes Our engine extracts text and structure. Get your native format file. LoveOCR combines modern vision-language AI with our own conversion and file-rendering pipeline to interpret text, tables, layout, and document structure. Text & Table Extraction Attempts to preserve useful structure such as tables, lists, headings, and reading order. Multi‑Language Recognition Designed for multilingual printed text and mixed document layouts; accuracy varies with language, image quality, and typography. Online Processing Processing time depends on image size, document complexity, network conditions, and the selected output format. Choose the Output for What You Need to Do Next OCR is only the first step. The useful result is the file you can work with afterward. If you need to edit paragraphs, headings, or a scanned letter, start with Image to Word . If the image contains rows, columns, prices, quantities, or other tabular data, Image to Excel is usually the better choice because numbers can be checked, sorted, and calculated after conversion. For archival scans where the original visual appearance matters, a searchable PDF keeps the page image while adding a selectable text layer. Developer-oriented outputs solve a different problem. JSON, XML, YAML, CSV, TSV, SQL, and related tools are designed to turn information visible in an image into structured data. A file can be syntactically valid and still contain an OCR mistake, so important identifiers, dates, decimal values, coordinates, account codes, and field mappings should be checked against the source image before import. For visual or publishing workflows, LoveOCR also provides Markdown, LaTeX, SVG, EPUB, subtitle, vCard, calendar, diagram, accessibility, and geographic outputs. The all-tools page explains every available converter. What AI-Assisted Conversion Can and Cannot Preserve LoveOCR combines image analysis with format-specific generation. That means the system can often identify text blocks, tables, labels, headings, lists, and other visual relationships instead of returning one plain text stream. The selected converter then attempts to represent those elements in the destination format. A table image can become spreadsheet cells, a flowchart can become diagram code, and a photographed form can become a fillable-document structure. No automatic converter can guarantee that every visual detail will survive perfectly. Low-resolution text, glare, shadows, unusual fonts, overlapping annotations, merged table cells, handwritten corrections, decorative layouts, or ambiguous diagrams can all change the result. Structured formats also impose their own rules: Markdown tables do not support every layout that HTML can express, a CSV file has no native cell formatting, and generated code or database statements should never be treated as safe to execute merely because they parse correctly. LoveOCR therefore treats generated files as a starting point that you can inspect and refine. Prepare the Source Image Before You Convert Use the clearest source you have. A direct scan or original screenshot usually gives the OCR engine more usable detail than a heavily compressed image forwarded through messaging apps. Keep the page straight and readable. Mild rotation can often be handled, but strong perspective distortion makes table boundaries, columns, and text baselines harder to interpret. Avoid glare and deep shadows. Reflections can hide digits or punctuation even when the page looks readable at a glance. Crop unrelated material when practical. Removing surrounding desk space, browser chrome, or multiple unrelated documents helps the converter focus on the content that belongs in the output. Select the output for the real task. If you need formulas, use a spreadsheet-oriented tool; if you need searchable archival pages, choose searchable PDF; if you need machine-readable records, choose a structured-data format. Review High-Impact Fields, Not Just the Overall Appearance A quick visual review can miss the errors that matter most. For spreadsheets and financial records, compare totals, decimal separators, dates, currency symbols, negative values, and column alignment. For contacts and calendar events, verify names, phone labels, email addresses, dates, times, and time zones. For code, SQL, Mermaid, Graphviz, JSON-LD, UBL, QIF, and GeoJSON, validate the generated syntax and then verify the meaning of the data. In GeoJSON, for example, a coordinate pair can be structurally valid while still pointing to the wrong place if longitude and latitude are reversed. When the output will be published, imported into another system, used for accessibility, or relied on for business decisions, keep the source image until you finish validation. That gives you an authoritative reference when a field looks uncertain. Privacy and Temporary File Handling Uploaded and generated conversion files are temporary. LoveOCR schedules them for automatic deletion from its storage within 3 hours so users have time to download a result without turning the converter into long-term document storage. Transfers use HTTPS/TLS. Some conversion tasks may use external AI infrastructure to analyze content when necessary to produce the requested output. For a fuller explanation of file handling, support records, analytics, and service providers, read the Privacy & Data Safety page . Learn the Workflow Before Converting Important Documents

The LoveOCR Guides & Learning Center contains practical articles for the same tools available on this page. The guides focus on decisions that the converter itself cannot make for you: how to choose between Word and searchable PDF, how to validate spreadsheet OCR, what to check before executing generated Python or SQL, how to test accessibility outputs, and how to verify structured data before publishing or importing it. If you are working with an unfamiliar format, reading its guide first can save time during cleanup. Who Is Behind LoveOCR? LoveOCR is built and maintained as a focused OCR and document-structure conversion service. You can read about the project and its founder on the About LoveOCR page. If a conversion fails or you find an output problem that is repeatable, the contact page explains what information to include so the issue can be investigated without requiring you to publish the source document publicly. Learn Before You Convert Use these guides to choose the right output and verify important results. Browse the full LoveOCR learning center for guides covering all 50 tools. How AI OCR Works Understand what happens between upload, recognition, structure detection, and output generation. OCR Handwriting: Tools and Best Practices See why handwriting is harder than printed text and how to prepare clearer source images. Create Searchable PDFs from Scans Learn when a text-over-image PDF is better than extracting content into an editable document. Convert a Table Photo to Excel Cells Preserve rows and columns, then check numbers before you calculate or import the sheet. Review AI-Generated Python Before Running It Treat converted code as untrusted until you understand, test, and validate what it does. Validate JSON After OCR Check both syntax and data meaning before importing OCR-generated structured data. Everything You Need Need another output? Browse all 50 conversion tools . Secure, Private, and Transparent Uploaded and generated conversion files are temporary and are automatically removed from LoveOCR storage within 3 hours. Automatic File Deletion Uploaded and generated conversion files are scheduled for automatic deletion from LoveOCR storage within 3 hours. Temporary Processing Files are kept temporarily to perform the requested conversion and provide a short download window. Encrypted Transfer Uploads and downloads are protected in transit using HTTPS/TLS. Purpose-Limited Processing Some conversions may use external AI infrastructure when needed to produce the requested output; see our Privacy Policy for details. Read our full Privacy Policy LoveOCR is an independent web-based OCR and document-conversion project built and maintained by Danish Abbas, who also founded FileConvertFree. Free access is available, and optional account or paid features may apply to higher usage levels. Contact us about conversion errors, account or billing questions, privacy concerns, accessibility issues, or product feedback. Include enough detail for us to reproduce the problem.