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1.2.1 pymaia_learn-1.2.1-py3-none-any.whl

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Project: pymaia-learn
Version: 1.2.1
Filename: pymaia_learn-1.2.1-py3-none-any.whl
Download: [link]
Size: 60622
MD5: 0bc938b55d60a2978205366ffa7d05fa
SHA256: 492145a3fc24c44bbafadaa5b0b11b539e9354e0174fb2c4dcb06956ea6d3abd
Uploaded: 2024-10-18 08:47:25 +0000

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METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: pymaia-learn
Version: 1.2.1
Summary: Python Package to support Deep Learning data preparation, pre-processing. training, result visualization and model deployment across different frameworks (nnUNet, nnDetection, MONAI).
Author: Bendazzoli Simone
Author-Email: simben[at]kth.se
Home-Page: https://github.com/SimoneBendazzoli93/PyMAIA.git
Project-Url: Documentation, https://pymaia.readthedocs.io
Project-Url: Bug Tracker, https://github.com/SimoneBendazzoli93/PyMAIA/issues
Project-Url: Source Code, https://github.com/SimoneBendazzoli93/PyMAIA
License: GPLv3
Keywords: deep learning,image segmentation,medical image analysis,medical image segmentation,object detection
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Typing :: Typed
Platform: OS Independent
Requires-Python: >=3.8
Requires-Dist: coloredlogs
Requires-Dist: dicom2nifti
Requires-Dist: nibabel
Requires-Dist: nilearn
Requires-Dist: numpy
Requires-Dist: pydicom
Requires-Dist: pydicom-seg
Requires-Dist: scipy
Requires-Dist: SimpleITK
Requires-Dist: tqdm
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: openpyxl
Requires-Dist: mlflow
Description-Content-Type: text/markdown; charset=UTF-8
License-File: LICENSE
[Description omitted; length: 3359 characters]

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Wheel-Version: 1.0
Generator: setuptools (75.2.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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pymaia_learn-1.2.1.dist-info/RECORD — —

top_level.txt

PyMAIA
PyMAIA_scripts

entry_points.txt

[console_scripts]
PyMAIA_convert_DICOM_dataset_to_NIFTI_dataset = PyMAIA_scripts.PyMAIA_convert_DICOM_dataset_to_NIFTI_dataset:main
PyMAIA_convert_NIFTI_predictions_to_DICOM_SEG = PyMAIA_scripts.PyMAIA_convert_NIFTI_predictions_to_DICOM_SEG:main
PyMAIA_convert_semantic_to_instance_segmentation = PyMAIA_scripts.PyMAIA_convert_semantic_to_instance_segmentation:main
PyMAIA_create_subset = PyMAIA_scripts.PyMAIA_create_subset:main
PyMAIA_downsample_modality = PyMAIA_scripts.PyMAIA_downsample_modality:main
PyMAIA_order_data_folder = PyMAIA_scripts.PyMAIA_order_data_folder:main
PyMAIA_run_pipeline_from_file = PyMAIA_scripts.PyMAIA_run_pipeline_from_file:main
nndet_compute_metric_results = PyMAIA_scripts.nndet_compute_metric_results:main
nndet_create_pipeline = PyMAIA_scripts.nndet_create_pipeline:main
nndet_extract_experiment_predictions = PyMAIA_scripts.nndet_extract_experiment_predictions:main
nndet_prepare_data_folder = PyMAIA_scripts.nndet_prepare_data_folder:main
nndet_run_preprocessing = PyMAIA_scripts.nndet_run_preprocessing:main
nndet_run_training = PyMAIA_scripts.nndet_run_training:main
nnunet_create_pipeline = PyMAIA_scripts.nnunet_create_pipeline:main
nnunet_prepare_data_folder = PyMAIA_scripts.nnunet_prepare_data_folder:main
nnunet_run_plan_and_preprocessing = PyMAIA_scripts.nnunet_run_plan_and_preprocessing:main
nnunet_run_preprocessing = PyMAIA_scripts.nnunet_run_preprocessing:main
nnunet_run_training = PyMAIA_scripts.nnunet_run_training:main