Metadata-Version: 2.1
Name: openfertility
Version: 0.1.0
Summary: Machine learning and data analysis for fertility
Home-page: https://github.com/delestro/openfertility
Author: Felipe Delestro
Author-email: delestro@gmail.com
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE

![Open Ferlility logo](docs/static/OpenFertility.svg)

Open Fertility is an open-source project dedicated to advancing fertility analysis and prediction through machine learning. The goal is to foster a __community-driven__ initiative that empowers fertility professionals, researchers, and enthusiasts. 

Inspired by the paper [_An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization_](https://www.nature.com/articles/s41597-023-02182-3) the aim is to leverage the open data they published to develop initial models.

The primary objectives are to:

- Cultivate an inclusive and collaborative community, bringing together experts and enthusiasts.
- Provide comprehensive tools for training, evaluating, and applying machine learning techniques.
- Effective data visualization, to gain valuable insights and interpret data with clarity.
- Deliver intuitive user interfaces that grant easy access to the models.


Get in touch if you feel interested in participating!

# Installation

During this early develoment stage, a pip install is still not provided.

So, follow these steps:

1. Download or clone the files
2. Navigate to the directory containing the repository
3. Run `pip install .` 


# Early features

## Download the blastocyst dataset

```python
import openfertility as of

blasto2k = of.datasets.blasto2k.Dataset()
blasto2k.download()
```
