scansplitter 0.4.0

Automatically detect, split, and rotate multiple photos from scanned images

ScanSplitter

Automatically detect, split, and rotate multiple photos from scanned images.

Drop a scan containing multiple photos and get individual, correctly-oriented images back.

Quick Start

One-time setup - Install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

Run ScanSplitter (no clone needed):

uvx scansplitter api

Opens at http://localhost:8000 - drag & drop your scans and export cropped photos. If port 8000 is already in use, pick another:

uvx scansplitter api --port 8001

Features

• Multiple detection modes - Choose between ScanSplitterv1, ScanSplitterv2 (default), and AI (U2-Net)
• Interactive editing - Adjust, rotate, and resize bounding boxes before cropping
• Auto-rotation - Detects and corrects 90°/180°/270° rotations
• PDF support - Extract and process pages from PDF files
• Web UI - Modern React interface with Fabric.js canvas editor
• CLI - Batch process files from the command line

Detection Modes & Models

Photo detection (splitter)

• ScanSplitterv2 (default): An improved contour-based detector. It applies contrast enhancement (CLAHE), adaptive thresholding, adaptive morphology (kernel scales with resolution), and contour quality filtering (solidity/aspect/extent). It can also use convex-hull borders for irregular edges.
• ScanSplitterv1: The first contour-based detector used with adaptive threshold + fixed morphology + minAreaRect filtering. It’s simpler and can be useful as a fallback if v2 behaves unexpectedly on a specific scan.
• AI (U2-Net): A deep-learning salient-object model (ONNX) that produces a mask; ScanSplitter then extracts regions from that mask. It’s best for difficult scans (busy backgrounds, low contrast), but requires downloading a model on first use. Might be less accurate for multiple photos at once.

Auto-rotation model

• Orientation model: An EfficientNetV2-based ONNX classifier that predicts the correct 0°/90°/180°/270° rotation for each cropped photo. ScanSplitter may fall back to classic heuristics if the model can’t be loaded.

Model downloads

Some modes require downloading models on first use (U2-Net (5Mb / 176MB) and the orientation model (80MB)). The web UI shows download progress while this is happening.

Installation Options

Option 1: Run directly with uvx (recommended)

No installation needed - just run:

uvx scansplitter api

Option 2: Install with pipx

pipx install scansplitter
scansplitter api

Option 3: Install from source

git clone https://github.com/janklan/scansplitter
cd scansplitter
uv sync
uv run scansplitter api

Usage

Web Interface

scansplitter api
# or: uvx scansplitter api

Opens at http://localhost:8000 with:

• Drag & drop file upload (images and PDFs)
• Interactive bounding box editor (drag, resize, rotate)
• Multi-file support with tabs
• PDF page navigation
• ZIP export

Command Line

# Process a scanned image
uv run scansplitter process scan.jpg -o ./output/

# Process a PDF
uv run scansplitter process document.pdf -o ./output/

# Multiple files
uv run scansplitter process scan1.jpg scan2.png -o ./output/

# Options
uv run scansplitter process scan.jpg \
  --no-rotate \
  --min-area 5 \
  --max-area 70 \
  --detection-mode scansplitterv2 \
  --format jpg \
  -o ./output/

CLI Options:

Option	Description
-o, --output	Output directory (default: ./output)
--no-rotate	Disable auto-rotation
--min-area	Minimum photo size as % of scan (default: 2)
--max-area	Maximum photo size as % of scan (default: 80)
--detection-mode	scansplitterv2 (default), scansplitterv1 (legacy), or u2net (deep learning); classic is an alias for scansplitterv2
--u2net-full	Use full U2-Net model instead of lite (slower, more accurate)
--format	Output format: png or jpg (default: png)

How It Works

1. Photo detection - Runs the selected detection mode (ScanSplitterv1 / ScanSplitterv2 / AI (U2-Net)) to produce rotatable bounding boxes.
2. Interactive adjustment - You can refine boxes in the web UI before cropping.
3. Cropping - Extracts rotated regions using the adjusted boxes.
4. Auto-rotation (optional) - Uses the orientation model (with fallbacks) to fix 90°/180°/270° rotations.

Credits

ScanSplitter depends on excellent open models and upstream work:

• U²-Net (salient object detection) by Xuebin Qin et al. — paper: https://arxiv.org/abs/2005.09007, code: https://github.com/xuebinqin/U-2-Net
• U2-Net ONNX weights are downloaded from rembg releases by Daniel Gatis (with a ScanSplitter backup mirror) — https://github.com/danielgatis/rembg
• Orientation model (EfficientNetV2) is downloaded from Duarte Barbosa’s deep image orientation detection project (with a ScanSplitter backup mirror) — https://github.com/duartebarbosadev/deep-image-orientation-detection

Development

Frontend Development

# Start API server
uv run scansplitter api --reload

# In another terminal, start frontend dev server
cd frontend
npm install
npm run dev

Frontend runs on http://localhost:5173 with hot reload, proxying API requests to :8000.

Build Frontend

cd frontend
npm run build

Builds to src/scansplitter/static/, which FastAPI serves automatically.