Microscopy Image Generation with Diffusion Models

This project implements a deep learning pipeline for generating microscopy images using diffusion models.

Project Structure

.
├── data/
│   ├── raw/           # Examples of original microscopy images
│   └── processed/     # Examples of preprocessed and augmented data
├── src/
│   ├── data/         # Data loading and preprocessing modules
│   ├── models/       # Model architecture definitions
│   ├── training/     # Training scripts and utilities
│   ├── utils/        # Helper functions and utilities
│   └── config/       # Configuration files
├── tests/            # Unit tests
├── notebooks/        # Jupyter notebooks for exploration
└── docs/            # Documentation

Setup

1. Install uv (if not already installed):

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

2. Create a virtual environment and install dependencies:

uv venv
source .venv/bin/activate  # On Unix/macOS
uv pip install -r requirements.txt

Usage

1. Data Preparation:

   • Fetch data using the IDR API
   • Run preprocessing scripts from src/data/

2. Training:

   • Configure training parameters in src/config/
   • Run training scripts from src/training/

3. Evaluation:

   • Use notebooks in notebooks/ for visualization and analysis
   • Run evaluation scripts from src/training/

Requirements

• Python 3.8+
• PyTorch
• NumPy
• Matplotlib
• Other dependencies listed in requirements.txt

License

[Your chosen license]