Metadata-Version: 2.4
Name: cytosummarynet
Version: 0.0.4
Summary: Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning
Author-email: Shantanu Singh <shsingh@broadinstitute.org>
Requires-Python: >=3.10
Requires-Dist: numpy>=2.2.0
Requires-Dist: pandas>=2.2.3
Requires-Dist: pytorch-metric-learning>=2.8.1
Requires-Dist: torch>=2.5.1
Requires-Dist: tqdm>=4.67.1
Description-Content-Type: text/markdown

# CytoSummaryNet

A PyTorch-based deep learning library for learning an optimal way to aggregate single-cell features into population-level profiles.


## Installation

```bash
pip install cytosummarynet
```

## Quick Start

To try out CytoSummaryNet with sample data:

1. Generate sample data:
```bash
python examples/generate_sample_data.py
```

2. Run the example pipeline:
```bash
python examples/example_pipeline.py
```

This will create a sample dataset and train a model using the default parameters.

