sci-figure

name	sci-figure
description	Extracts figures and sub-figures from academic PDF papers. Supports Fig/Figure, Scheme, Chart, Supplementary Figure, Extended Data Figure (Nature), and Chinese equivalents (图/方案/示意图/附图/补充图). Sub-figure label recognition supports (a)/(A)/a)/(i)/(1)/a. formats. High-quality PNG output at configurable DPI. Use when user asks to "extract figure", "截取文献图片", "提取子图", "get figure from paper", "Scheme", "方案图", "补充图", "Supplementary Figure", or "Extended Data".
author	Shuo Zhao
license	AGPL-3.0-or-later
copyright	© 2026 Shuo Zhao. All rights reserved.
triggers	["提取图片","截取文献图片","提取子图","提取附图","补充图","方案图","示意图","图片提取","extract figure","extract subfigure","get figure from paper","Supplementary Figure","Extended Data","Scheme","figure extraction"]

Sci-Figure — Scientific Figure Extractor

Precisely extract figures and sub-figures from academic PDF papers.

License note: sci-figure is licensed under AGPL-3.0-or-later because it links PyMuPDF (fitz), which is AGPL-licensed.

Installation

Install the package from the skill directory before first use:

cd ${SKILL_DIR}
pip install -e .

This registers the sh-sci-fig CLI command. Requires Tesseract OCR:

• Windows: winget install UB-Mannheim.TesseractOCR
• Linux: apt install tesseract-ocr
• macOS: brew install tesseract

Preferences (EXTEND.md)

Use Bash to check EXTEND.md existence (priority order):

# Check project-level first
test -f .baoyu-skills/sci-figure/EXTEND.md && echo "project"

# Then user-level (cross-platform: $HOME works on macOS/Linux/WSL)
test -f "$HOME/.baoyu-skills/sci-figure/EXTEND.md" && echo "user"

EXTEND.md Supports: Default DPI | Default output format | Tesseract path

Usage

sh-sci-fig <input.pdf> [options]

Options

Option	Short	Description	Default
<input>		PDF file path	Required
--figure	-f	Figure number (1, 2, 3...)	Required (except --list/--all)
--subfigure	-s	Sub-figure label (a, b, c...)	None (returns whole figure)
--output	-o	Output directory	Current directory
--dpi	-d	Output resolution	600
--list	-l	List all available figure numbers	false
--all		Extract all figures	false
--format		Output format (png/jpg)	png
--strategy		Extraction strategy: hybrid/native/cv	hybrid
--ocr		OCR engine: tesseract/easyocr/none	tesseract
--render-page		Render full page with annotations	false
--annotate		Draw bounding boxes on rendered page	false
--bbox		Manual bbox override (x0,y0,x1,y1 in px)	None
--no-trim		Disable whitespace trimming	false
--debug		Enable debug logging	false
--quiet	-q	Suppress info messages	false

Examples

# Extract Figure 2, sub-figure c
sh-sci-fig paper.pdf -f 2 -s c

# Extract entire Figure 3
sh-sci-fig paper.pdf -f 3

# List all available figures in a PDF
sh-sci-fig paper.pdf --list

# Extract all figures
sh-sci-fig paper.pdf --all

# Custom output directory and DPI
sh-sci-fig paper.pdf -f 2 -s c -o ./output/ -d 300

# Use EasyOCR for sub-figure label detection
sh-sci-fig paper.pdf --all --ocr easyocr

# CV-only strategy (skip native extraction)
sh-sci-fig paper.pdf --all --strategy cv

# Render page with annotated bounding boxes (debugging)
sh-sci-fig paper.pdf -f 1 --render-page --annotate

# Manual bbox extraction (multimodal correction)
sh-sci-fig paper.pdf -f 1 --bbox 100,200,800,1200

Output:

Extracted: figure_2c.png (1920x1080, 600 DPI)

Error Handling

Scenario	Behavior
Figure number not found	Error + list all available figure numbers
OCR recognition failed	Return entire figure region
Sub-figure split failed	Return entire figure region
No sub-figure labels found	Return entire figure region

Tech Stack

Library	Role
pdfplumber	Text + coordinate extraction (caption detection)
PyMuPDF (fitz)	Native image extraction + high-quality page rendering
opencv-python	CV region detection, connected-component analysis, content validation
Pillow	Final cropping, format conversion
pytesseract	OCR for sub-figure label recognition (default)
easyocr	Alternative OCR engine (optional, pip install sci-figure[ocr])
numpy	Image array operations

Extraction Engines (v2)

Engine	Priority	Best For
Native (PyMuPDF)	1st	Raster images embedded in PDF
CV (connected-component)	2nd	Vector graphics, colored plots
Caption-anchored	3rd	Fallback when above engines fail

The hybrid strategy (default) tries all three in order and validates results.

Detected Figure Fields

Each figure returned by FigureExtractor.detect_all() is a dict with these keys:

Field	Type	Description
number	int	Figure number
page	int	Page index (0-based)
bbox_pdf	tuple	Crop region in PDF points (x0, y0, x1, y1)
bbox_px	tuple	Crop region in pixels (x0, y0, x1, y1)
caption_text	str	Full caption text
figure_type	str	One of: figure, scheme, chart, supplementary, extended_data
sublabels	list[str]	Sub-figure labels, e.g. ["a","b","c"]
image	ndarray	Cropped figure image (numpy array)
engine_used	str	Engine that produced the crop: native, cv, or fallback

list_figures() returns the same dicts without the image field.

Extension Support

Custom configurations via EXTEND.md. See Preferences section for paths and supported options.

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© License & Copyright

Aut_Sci_Write — Autonomous Scientific Writer

• Author: Shuo Zhao
• License: MIT License
• Copyright: © 2026 Shuo Zhao. All rights reserved.
• Original Work: This is an original work created by the author. No reproduction, redistribution, or commercial use without explicit permission. Permission is hereby granted, free of charge, to any person obtaining a copy of this software... (See the LICENSE file in the root directory for the full MIT terms.)

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This skill is part of the Aut_Sci_Write suite. For full license terms, see the LICENSE file in the project root.