| name | image-ocr |
| description | Extract text from images using Python OCR. Use when the user wants to read text from screenshots, photos of documents, scanned pages, or any image containing text. Supports PNG, JPEG, TIFF, BMP, and WebP formats. |
| compatibility | Requires Python 3 and pytesseract + Pillow (pip install pytesseract Pillow). Also requires Tesseract OCR engine installed on the system. |
Image OCR
Extract text from images using Tesseract OCR via Python.
When to use this skill
- User asks to read or extract text from an image
- User has a screenshot with text they want to process
- User has scanned documents that need text extraction
- User wants to digitize text from photos
Scripts overview
| Script | Purpose | Dependencies |
|---|
ocr_extract.py | Extract text from images with multiple options | pytesseract, Pillow |
Steps
1. Install dependencies (first time only)
Install the Python packages:
pip install pytesseract Pillow
Install Tesseract OCR engine:
For additional language support:
- Windows: Select languages during installation
- Linux:
sudo apt install tesseract-ocr-chi-sim (Chinese Simplified), tesseract-ocr-jpn (Japanese), etc.
CRITICAL — Dependency Error Recovery: If the script fails with an ImportError or "tesseract not found" error, install the missing dependencies using the commands above, then re-run the EXACT SAME script command that failed.
2. Extract text from an image
python scripts/ocr_extract.py "IMAGE_PATH"
Options:
--lang LANG — OCR language (default: eng). Use chi_sim for Chinese, jpn for Japanese, eng+chi_sim for multiple.--save OUTPUT_PATH — Save extracted text to a file--preprocess MODE — Image preprocessing: none (default), grayscale, threshold, blur--dpi DPI — Set image DPI for better accuracy (default: auto-detect)--psm MODE — Tesseract page segmentation mode (0-13, default: 3 = auto)
Examples:
python scripts/ocr_extract.py "screenshot.png"
python scripts/ocr_extract.py "document.jpg" --lang chi_sim
python scripts/ocr_extract.py "mixed.png" --lang eng+chi_sim
python scripts/ocr_extract.py "noisy_scan.png" --preprocess threshold
python scripts/ocr_extract.py "scan.tiff" --save output.txt
python scripts/ocr_extract.py "plate.jpg" --psm 7
Page Segmentation Modes (PSM)
| Mode | Description | Use Case |
|---|
| 3 | Fully automatic (default) | General documents |
| 4 | Assume single column | Single-column text |
| 6 | Assume single block | Uniform text block |
| 7 | Single line | One line of text |
| 8 | Single word | One word |
| 11 | Sparse text | Text scattered on image |
| 13 | Raw line | Single line, no OSD |
Edge cases
- Low quality images: Use
--preprocess threshold or --preprocess blur to improve results
- Rotated text: Tesseract handles slight rotation; for heavily rotated images, rotate first
- Very small text: Increase DPI with
--dpi 300 or higher
- Mixed languages: Combine with
+, e.g., --lang eng+chi_sim+jpn
- Empty results: Try different PSM modes or preprocessing options
Scripts
