Holography dataset generation toolkit
Project description
HoloGen: Synthetic Hologram Dataset Toolkit
The HoloGen toolkit generates paired object-domain images and their inline or off-axis holograms for machine learning workflows.
Features
- Binary object-domain sample generation with diverse analytic shapes
- Strategy-based hologram creation supporting inline and off-axis methods
- Reconstruction pipeline for object-domain recovery from holograms
- Dataset writer for NumPy bundles and preview imagery
Quickstart
- Create a virtual environment and install the package:
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
pip install -e .
- Generate a sample dataset:
python scripts/generate_dataset.py
The default dataset is written to the dataset/ directory with both .npz tensors and PNG previews.
Configuration
Key parameters reside in scripts/generate_dataset.py. Adjust them to change:
- Grid resolution and pixel pitch
- Optical wavelength and propagation distance
- Holography method (inline or off-axis)
- Carrier parameters for off-axis holography
Licensing
Released under the MIT License. See LICENSE for details.
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