# PyMAIA
<p align="center">
<img src="https://raw.githubusercontent.com/SimoneBendazzoli93/PyMAIA/main/images/MAI_A_logo.png" width="50%" alt='PyMAIA'>
</p>
[](https://pymaia.readthedocs.io/en/latest/?badge=latest)
[](https://opensource.org/licenses/GPL-3.0)
## What is PyMAIA?
Hive is a Python package to support Deep Learning data preparation, pre-processing. training, result visualization and
model deployment across different frameworks ([nnUNet](https://github.com/MIC-DKFZ/nnUNet)
, [nnDetection](https://github.com/MIC-DKFZ/nnDetection), [MONAI](https://monai.io/) ).
## Local Environment Setup
To install the package, run the following commands:
```bash
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
or conda install cudatoolkit cuda-version=11
pip install nnunetv2/nndetection
pip install pymaia-learn
```
More information can be found in the [documentation](https://pymaia.readthedocs.io/en/latest/).
## Tutorials
- [nnUNet Tutorial](https://pymaia.readthedocs.io/en/latest/tutorials/nnUNet_tutorial.html)
- [nnDetection Tutorial](https://pymaia.readthedocs.io/en/latest/tutorials/nnDetection_tutorial.html)
## Docker and Singularity
PyMAIA can be run in a containerized environment using Docker or Singularity. To
create the PyMAIA image, you can use [HPPCM](https://github.com/NVIDIA/hpc-container-maker), a tool to create container
images for HPC applications from given recipes.
```bash
pip install hpccm
hpccm --recipe recipe.py --format singularity > PyMAIA.def
singularity build PyMAIA.sif PyMAIA.def
hpccm --recipe recipe.py --format docker > Dockerfile
docker build -t pymaia .
```
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"description": "# PyMAIA\n\n<p align=\"center\">\n<img src=\"https://raw.githubusercontent.com/SimoneBendazzoli93/PyMAIA/main/images/MAI_A_logo.png\" width=\"50%\" alt='PyMAIA'>\n</p>\n\n[](https://pymaia.readthedocs.io/en/latest/?badge=latest)\n\n[](https://opensource.org/licenses/GPL-3.0)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n## What is PyMAIA?\n\nHive is a Python package to support Deep Learning data preparation, pre-processing. training, result visualization and\nmodel deployment across different frameworks ([nnUNet](https://github.com/MIC-DKFZ/nnUNet)\n, [nnDetection](https://github.com/MIC-DKFZ/nnDetection), [MONAI](https://monai.io/) ).\n\n## Local Environment Setup\n\nTo install the package, run the following commands:\n\n```bash\nconda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia\nor conda install cudatoolkit cuda-version=11\npip install nnunetv2/nndetection\npip install pymaia-learn\n```\n\nMore information can be found in the [documentation](https://pymaia.readthedocs.io/en/latest/).\n\n## Tutorials\n\n- [nnUNet Tutorial](https://pymaia.readthedocs.io/en/latest/tutorials/nnUNet_tutorial.html)\n- [nnDetection Tutorial](https://pymaia.readthedocs.io/en/latest/tutorials/nnDetection_tutorial.html)\n\n## Docker and Singularity\nPyMAIA can be run in a containerized environment using Docker or Singularity. To\ncreate the PyMAIA image, you can use [HPPCM](https://github.com/NVIDIA/hpc-container-maker), a tool to create container\nimages for HPC applications from given recipes.\n\n```bash\npip install hpccm\n\nhpccm --recipe recipe.py --format singularity > PyMAIA.def\nsingularity build PyMAIA.sif PyMAIA.def\n\nhpccm --recipe recipe.py --format docker > Dockerfile\ndocker build -t pymaia .\n```\n",
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