Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Extract text from images using the Tesseract OCR engine directly via command line. Supports multiple languages including Chinese, English, and more. Use this...
Extract text from images using the Tesseract OCR engine directly via command line. Supports multiple languages including Chinese, English, and more. Use this...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Extract text content from images using the Tesseract engine directly via command line.
Extract text from image files using native tesseract CLI Support multi-language recognition (Chinese, English, etc.) No Python dependencies required Simple and fast
Install Tesseract OCR system package: # Ubuntu/Debian: sudo apt-get install tesseract-ocr tesseract-ocr-chi-sim # macOS: brew install tesseract tesseract-lang
# Use default language (English) tesseract /path/to/image.png stdout # Specify language (Chinese + English) tesseract /path/to/image.png stdout -l chi_sim+eng # Save to file tesseract /path/to/image.png output.txt -l chi_sim+eng # Multiple languages tesseract /path/to/image.png stdout -l chi_sim+eng+jpn
LanguageCodeSimplified Chinesechi_simTraditional Chinesechi_traEnglishengJapanesejpnKoreankorChinese + Englishchi_sim+eng
# OCR with Chinese support tesseract image.jpg stdout -l chi_sim # OCR with mixed Chinese and English tesseract image.png stdout -l chi_sim+eng # Save to file instead of stdout tesseract document.png result -l chi_sim+eng # Creates result.txt
OCR accuracy depends on image quality; use clear images for best results Complex layouts (tables, multi-column) may require post-processing Chinese recognition requires the tesseract-ocr-chi-sim language pack Language packs must be installed separately on your system
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.