Metadata-Version: 2.1
Name: med-imagetools
Version: 0.2.2
Summary: Transparent and reproducible image processing pipelines in Python.
Home-page: https://github.com/bhklab/med-imagetools
Author: Michal Kazmierski, Sejin Kim, Vishwesh Ramanathan, Benjamin Haibe-Kains
Author-email: benjamin.haibe.kains@utoronto.ca
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Development Status :: 2 - Pre-Alpha
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: h5py
Requires-Dist: joblib
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: pydicom
Requires-Dist: pynrrd
Requires-Dist: scikit-image
Requires-Dist: SimpleITK
Requires-Dist: tqdm
Requires-Dist: torch
Requires-Dist: torchio
Provides-Extra: debug
Requires-Dist: pyvis ; extra == 'debug'

# med-imagetools: transparent and reproducible medical image processing pipelines in Python
From messy TCIA folders to deep learning ready Nrrd/NiFTIs in one line. 

## Installation
```
pip install med-imagetools
```

### (recommended) Create new conda virtual environment
```
conda create -n mit
conda activate mit
pip install med-imagetools
```

### (optional) Install in development mode

```
conda create -n mit
conda activate mit
pip install -e git+https://github.com/bhklab/med-imagetools.git
```
This will install the package in editable mode, so that the installed package will update when the code is changed.

## Demo
```
Under Construction
```

### AutoPipeline CLI

### Pipeline custom processing

### From Training a model with Dataset 

## Upcoming Features
* TorchIO Support
* More demos/example scripts



