PicText Search | Powerful Offline Image Text Search

PicText Search – Find text inside your images, instantly.

PicText Search is a lightweight, fully offline Windows desktop application that scans your image folders and finds any photo, screenshot, or scanned document containing specific text using built-in OCR (Optical Character Recognition). No internet connection, no cloud services, and no third-party software required. Everything runs locally on your PC.

Search through thousands of images in seconds and extract exact matching words from any picture perfect for scanned documents, screenshots, and photo archives.

Key Features

• 100% Offline no internet connection needed after installation
• One-click installer no manual setup, no dependencies, nothing extra to configure
• Subfolder search scan an entire folder tree in one pass
• Multiple search terms search several words or phrases at once
• Regex & fuzzy matching advanced pattern search plus approximate/typo-tolerant matching
• Smart caching scanned images are cached locally for instant re-searches
• Live progress bar with pause, resume, and cancel controls
• Grid or list view visual thumbnail grid or a detailed sortable table
• Powerful filters filter by file type, folder, or date modified
• Bulk copy/move move or copy all matched files to a new folder in one click
• Search history every past search logged, one click to repeat it
• Top words report see the most frequent words across all your images
• Export to CSV/TXT for reporting and record-keeping
• Full source code included clean, modular, and easy to customize

Who is this for?

Perfect for anyone who needs to search large collections of screenshots, scanned receipts, invoices, ID cards, memes, chat exports, or any images containing text photographers, admins, researchers, students, and everyday Windows users managing large photo libraries.

Requirements

• Windows 10 or later (64-bit)
• No Python, no separate OCR engine, no internet required

What’s Included

• Windows installer (.exe)
• Full readable source code
• Documentation (HTML)