How to Extract & Copy Unselectable Text from Any Webpage
Encountered text baked into an infographic, a code snippet inside a YouTube tutorial, an HTML5 canvas chart, or a site with right-click disabled? Here is how to copy it instantly.
Why Can't I Copy This Text?
On the modern web, content is increasingly rendered in non-standard formats that your browser cursor cannot highlight:
1. Raster Image Embeds
Infographics, diagrams, scanned PDFs, screenshots, and receipts are composed of pixel arrays, not DOM characters.
2. Video Player Frames
Code walkthroughs, lecture slides, and presentations on YouTube, Loom, or Coursera cannot be selected with a mouse.
3. CSS Protection Rules
Many documentation and paywalled portals use user-select: none or JavaScript event blockers like contextmenu to prevent copying.
4. HTML5 Canvas & WebGL
Figma mockups, interactive charts (Chart.js, D3), and games render directly to a graphics buffer with zero selectable HTML text nodes.
Why Cloud OCR Websites Are a Security Risk
Most people take a screenshot and upload it to a free online OCR site. Those third-party cloud servers store your uploaded images on their disks — exposing company passwords, customer data, and internal code. GoFully runs a compiled WebAssembly model (Tesseract Wasm) completely inside your browser memory. No server ever receives your pixels.
How to Extract Text in 3 Clicks
Trigger Region Capture
Click the GoFully icon or press the shortcut (Ctrl+Shift+A on Windows / Cmd+Shift+A on Mac).
Select the Area
Drag a box over the image, video frame, chart, or protected text.
Click "Extract Text" (OCR)
In the result bar, click the OCR button. The on-device engine extracts all readable characters, preserves spacing, and copies the clean text to your clipboard.
Pro Tips for Maximum OCR Accuracy
- Zoom in on small fonts: If a video frame has tiny code characters, zoom the browser (Cmd/Ctrl +) before capturing. More pixels per character dramatically improves recognition accuracy.
- Capture tight bounding boxes: Crop closely around the relevant text to avoid noisy background graphics or decorative borders.
- High Contrast: Light text on dark backgrounds and dark text on light backgrounds are recognized with >99% precision.
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