Skill

image-ocr

Extract text from a directory of JPG/JPEG images into a single Markdown file using Apple Vision, tesseract, or MLX OCR

Install

npx claudepluginhub varunr89/claude-marketplace --plugin ocr-toolkit

Tool Access

This skill uses the workspace's default tool permissions.

Preview

Batch-processes a directory of JPG/JPEG images and produces a combined Markdown file containing the OCR text from each image.

SKILL.md

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Last CommitMar 1, 2026

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Image OCR

Batch-processes a directory of JPG/JPEG images and produces a combined Markdown file containing the OCR text from each image.

When to use

Use this skill when the user wants to extract text from one or more JPG/JPEG images -- for example scanned documents, photos of whiteboards, or screenshots.

Backends

vision (default on macOS/Apple Silicon) -- Uses Apple's Vision framework via PyObjC. Fast, on-device, GPU-accelerated. Requires pyobjc-core and pyobjc-framework-Vision.
tesseract -- Uses the tesseract CLI binary. Cross-platform. Optional preprocessing (grayscale, autocontrast, upscale) via Pillow.
mlx_ocr -- Uses MLX-based OCR on Apple Silicon. Runs in a subprocess to isolate potential Metal crashes. Requires Python 3.10+ and mlx-ocr.
auto -- Tries vision first, falls back to tesseract.

Usage

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/ocr_jpgs_to_markdown.py \
  --input <directory-of-jpgs> \
  --output <output.md> \
  [--backend auto|vision|tesseract|mlx_ocr] \
  [--start N] [--limit N] \
  [--languages en-US] \
  [--fast] \
  [--workers N] \
  [--tesseract-lang eng] [--tesseract-psm 6] [--tesseract-oem 1] \
  [--preprocess] [--preprocess-scale 2.0] \
  [--det-lang eng] [--rec-lang lat] \
  [--mlx-worker-python /path/to/python3.11]

Key arguments

Argument	Default	Description
`--input`	`ezgif-...`	Directory containing .jpg/.jpeg files
`--output`	`training_plan_ocr.md`	Output Markdown file path
`--backend`	`auto`	OCR backend: auto, vision, tesseract, mlx_ocr
`--start`	0	Start index (0-based) within sorted file list
`--limit`	None	Max files to process
`--languages`	`en-US`	Comma-separated recognition languages (Vision)
`--fast`	false	Use faster, less accurate recognition level (Vision)
`--workers`	CPU count	Number of parallel workers
`--preprocess`	false	Grayscale/autocontrast/upscale before tesseract
`--preprocess-scale`	2.0	Upscale factor for preprocessing

Dependencies

macOS + PyObjC for Vision backend (pip install pyobjc-core pyobjc-framework-Vision)
tesseract binary for tesseract backend (brew install tesseract)
mlx-ocr + Python 3.10+ for MLX backend
Pillow for preprocessing and MLX