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This project aims to build a new vision model that reconstructs objects from their in-line holograms. The objective is to minimize the twin-image effects and image artifacts (aberrations, speckles, sensor effects, etc.).

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electricalgorithm/holopaswin

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HoloPASWIN: In-Line Holographical Physics-Aware SWIN Transformer

A deep learning project for eliminating the twin-image problem in in-line holography using a physics-aware Swin-UNet architecture trained with synthetic holograms generated via the Angular Spectrum Method.

Development Setup

Installing Git Hooks

This repository includes pre-commit hooks that automatically run code quality checks (ruff and mypy) before each commit. To install them:

./scripts/install-hooks.sh

This will set up the hooks from .githooks/ to .git/hooks/. The hooks will:

  • Run ruff check on src/
  • Run ruff format --check on src/
  • Run mypy --strict on src/

If any check fails, the commit will be blocked. You can bypass the hook with git commit --no-verify (not recommended).

About

This project aims to build a new vision model that reconstructs objects from their in-line holograms. The objective is to minimize the twin-image effects and image artifacts (aberrations, speckles, sensor effects, etc.).

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