HoloGen: Synthetic Hologram Dataset Toolkit

The HoloGen toolkit generates paired object-domain images and their inline or off-axis holograms for machine learning workflows.

See the first dataset (100k, 157.4GB!) generated with the HoloGen in HuggingFace 🤗

Features

• Binary object-domain sample generation with diverse analytic shapes
• Complex field support for amplitude, phase, and mixed object types
• 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 with multiple field representations
• Realistic noise and aberration modeling for physically accurate simulations

Quickstart

1. Create a virtual environment and install the package:

   python3 -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt
   pip install -e .

2. 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
• Noise levels and aberration coefficients (see docs)

Complex Field Support

HoloGen supports complex-valued optical fields with amplitude, phase, and mixed representations. Generate phase-only objects (transparent samples), amplitude-only objects (absorbing samples), or full complex fields. Export data as intensity, amplitude, phase, or complex representations. See docs/COMPLEX_FIELDS.md for detailed documentation.

Quick Example: Phase-Only Objects

python scripts/generate_dataset.py \
    --samples 100 \
    --object-type phase \
    --output-domain complex \
    --phase-shift 1.5708

Noise Simulation & Realistic Modeling

HoloGen includes comprehensive noise and aberration modeling to bridge the gap between synthetic and experimental holography. See docs/NOISE_SIMULATION.md for detailed parameter explanations.

Basic Noise Configuration

python scripts/generate_dataset.py \
    --samples 100 \
    --output ./dataset_noisy \
    --method inline \
    --height 512 \
    --width 512 \
    --pixel-pitch 6.4e-6 \
    --wavelength 532e-9 \
    --distance 0.05 \
    --speckle-contrast 0.8 \
    --sensor-read-noise 3.0 \
    --sensor-shot-noise \
    --sensor-dark-current 0.5 \
    --sensor-bit-depth 12

Licensing

Released under the MIT License. See LICENSE for details.