Metadata-Version: 2.1
Name: dlc2nwb
Version: 0.0
Summary: DeepLabCut <-> NWB conversion utilities
Home-page: https://github.com/DeepLabCut/DLC2NWB
Author: A. & M. Mathis Labs
Author-email: alexander@deeplabcut.org
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/DeepLabCut/DLC2NWB/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: deeplabcut (>=2.2.0.5)
Requires-Dist: ndx-pose (>=0.1.1)
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'

# Welcome to the DeepLabCut 2 Neurodata Without Borders Repo

Here we provide utilities to convert DeepLabCut (DLC) output to/from Neurodata Without Borders (NWB) format. This repository also elaborates a way for how pose estimation data should be represented in NWB.

Specifically, this package allows you to convert DLC's predictions on videos (*.h5 files) into NWB format. This is best explained with an [example](# Example use:).

# Installation:

Simply:

`pip install dlc2nwb`

# NWB pose ontology

The standard is presented [here](https://github.com/rly/ndx-pose). Our code is based on this NWB extension (PoseEstimationSeries, PoseEstimation) that was developed with [Ben Dichter, Ryan Ly and Oliver Ruebel](https://www.nwb.org/team/).

# Example

see [here](https://github.com/DeepLabCut/DLC2NWB/blob/main/examples/README.md).

```
from dlc2nwb.utils import convert_h5_to_nwb, convert_nwb_to_h5

# Convert DLC -> NWB:
nwbfile = convert_h5_to_nwb(
    'examples/config.yaml',
    'examples/m3v1mp4DLC_resnet50_openfieldAug20shuffle1_30000.h5',
)

# Convert NWB -> DLC
df = convert_nwb_to_h5(nwbfile[0])
```

Example data to run the code is provided in the folder [examples](/examples). This data is based on a DLC project you can find on [Zenodo](https://zenodo.org/record/4008504#.YWhD7NOA4-R) and that was originally presented in [Mathis et al., Nat. Neuro](https://www.nature.com/articles/s41593-018-0209-y) as well as [Mathis et al., Neuron](https://www.sciencedirect.com/science/article/pii/S0896627320307170?via%3Dihub).

To limit space, the folder only contains the project file `config.yaml` and DLC predictions for an example video called `m3v1mp4.mp4`, which are stored in `*.h5` format. The video is available, [here](https://github.com/DeepLabCut/DeepLabCut/tree/master/examples/openfield-Pranav-2018-10-30/videos).


# Funding and contributions:

We gratefully acknowledge the generous support from the [Kavli Foundation](https://kavlifoundation.org/) via a [Kavli Neurodata Without Borders Seed Grants
](https://www.nwb.org/nwb-seed-grants/).

We furthermore acknowledge feedback and discussions with [Ben Dichter, Ryan Ly and Oliver Ruebel](https://www.nwb.org/team/).


