SVG is a vector graphics format that defines images using mathematical descriptions of shapes, paths, and text rather than pixel grids. Created by the W3C in 1999, SVG files are XML documents that can be opened in any text editor. The format scales to any resolution without quality loss because shapes are recalculated at each size. SVG is the standard for web icons, logos, diagrams, charts, infographics, and technical illustrations. Text in SVG files can exist in two forms: embedded text elements that are part of the XML structure, and text rendered as visual paths that look like text but are not selectable. Flowcharts, organizational charts, architectural diagrams, and data visualizations commonly use SVG. The format supports CSS styling, JavaScript interactivity, and animation.

SVG to text conversion is valuable for extracting text from diagrams, flowcharts, infographics, and technical illustrations. Architectural blueprints and engineering diagrams saved as SVG contain labels, measurements, and annotations. Organizational charts and process flow diagrams have text in every node and connection label. If your diagrams are exported as PNG images instead, those work equally well. Data visualizations and charts include axis labels, legends, and data annotations. Presentation graphics exported as SVG contain slide text. When designers share SVG mockups, the embedded text may not copy directly if it has been converted to outlines. For quick captures of any diagram, the screenshot to text extractor works instantly from your clipboard.

ImagText uses a dual extraction approach for SVG files. First, the SVG is rendered to a raster image and analyzed by the AI vision model, which reads all visible text regardless of how it was created in the vector file. Second, the SVG source is parsed for embedded text elements — specifically the XML tags that contain actual text data. If the XML parsing finds text that the visual OCR missed, it is appended to the results. This dual approach ensures maximum coverage: text converted to outlines or paths is captured by the AI vision model, while embedded text elements are captured directly from the source code. The result is more complete text extraction than either method alone would achieve for complex SVG files.

SVG text extraction quality depends on how the SVG was created. Files with native text elements produce the most complete results because the text is extracted directly from the XML source. SVGs where text has been "outlined" or "converted to curves" in design tools lose the embedded text data, so extraction relies entirely on the AI vision model rendering. For complex diagrams with many small labels, the AI reads text at the rendered resolution — larger SVGs produce better results. SVG files with CSS-styled text extract cleanly. Files using web fonts that are not embedded may render with fallback fonts during the raster conversion, but this rarely affects text extraction accuracy. Malformed SVG files are handled gracefully — if XML parsing fails, the tool falls back to vision-only extraction without errors.