wrap repo as installable package

.github/workflows/ci-install-pkg.yml

@@ -0,0 +1,56 @@
+name: Install package
+
+# see: https://help.github.com/en/actions/reference/events-that-trigger-workflows
+on:  # Trigger the workflow on push or pull request, but only for the main branch
+  push:
+    branches: [master]
+  pull_request: {}
+
+jobs:
+  pkg-check:
+    runs-on: ubuntu-20.04
+
+    steps:
+      - uses: actions/checkout@master
+      - uses: actions/setup-python@v2
+        with:
+          python-version: 3.7
+
+      - name: Check package
+        run: |
+          pip install check-manifest
+          check-manifest
+          python setup.py check --metadata --strict
+
+      - name: Create package
+        run: |
+          pip install --upgrade setuptools wheel
+          python setup.py sdist bdist_wheel
+
+      - name: Verify package
+        run: |
+          pip install twine==3.2
+          twine check dist/*
+
+  pkg-install:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-20.04]
+        python-version: [3.7]
+
+    steps:
+      - uses: actions/checkout@master
+      - uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Create package
+        run: |
+          python setup.py sdist
+
+      - name: Install package
+        run: |
+          pip install dist/*
+          cd .. & python -c "import med3d ; print(med3d.__version__)"

MANIFEST.in

@@ -0,0 +1,24 @@
+# Manifest syntax https://docs.python.org/2/distutils/sourcedist.html
+graft wheelhouse
+
+recursive-exclude __pycache__  *.py[cod] *.orig
+
+# Include the README and CHANGELOG
+include *.md
+
+# Include the license file
+include LICENSE
+
+# Include the Requirements
+include requirements.txt
+
+exclude *.yml
+recursive-include images *.gif *.png
+recursive-include toy_data *.gz *.txt
+
+prune .git
+prune .github
+prune notebook*
+prune temp*
+prune test*
+prune docs*

README.md

@@ -97,12 +97,17 @@ We transferred the above pre-trained models to the multi-class segmentation task
 ```
 MedicalNet is used to transfer the pre-trained model to other datasets (here the MRBrainS18 dataset is used as an example).
 MedicalNet/
-    |--datasets/：Data preprocessing module
-    |   |--brains18.py：MRBrainS18 data preprocessing script
-    |	|--models/：Model construction module
-    |   |--resnet.py：3D-ResNet network build script
-    |--utils/：tools
-    |   |--logger.py：Logging script
+    |--med3d
+    |   |--datasets/：Data preprocessing module
+    |   |   |--brains18.py：MRBrainS18 data preprocessing script
+    |   |--models/：Model construction module
+    |   |   |--resnet.py：3D-ResNet network build script
+    |   |--utils/：tools
+    |   |   |--logger.py：Logging script
+    |   |--model.py: Network processing script
+    |   |--setting.py: Parameter setting script
+    |   |--train.py: MRBrainS18 training demo script
+    |   |--test.py: MRBrainS18 testing demo script
     |--toy_data/：For CI test
     |--data/：Data storage module
     |   |--MRBrainS18/：MRBrainS18 dataset
@@ -111,10 +116,6 @@ MedicalNet/
     |   |--train.txt: training data lists
     |   |--val.txt: validation data lists
     |--pretrain/：Pre-trained models storage module
-    |--model.py: Network processing script
-    |--setting.py: Parameter setting script
-    |--train.py: MRBrainS18 training demo script
-    |--test.py: MRBrainS18 testing demo script
     |--requirement.txt: Dependent library list
     |--README.md
 ```

med3d/__init__.py

@@ -0,0 +1,6 @@
+__version__ = "0.1.0"
+__docs__ = "MedicalNet 3D"
+__author__ = "Sihong Chen"
+__author_email__ = "TBD"
+__homepage__ = "https://github.com/Tencent/MedicalNet"
+__license__ = "MIT"

model.py → med3d/model.py

@@ -1,6 +1,6 @@
 import torch
 from torch import nn
-from models import resnet
+from med3d.models import resnet
 
 
 def generate_model(opt):

test.py → med3d/test.py

@@ -1,15 +1,13 @@
 from setting import parse_opts 
-from datasets.brains18 import BrainS18Dataset
+from med3d.datasets.brains18 import BrainS18Dataset
 from model import generate_model
 import torch
-import numpy as np
 from torch.utils.data import DataLoader
 import torch.nn.functional as F
 from scipy import ndimage
 import nibabel as nib
-import sys
 import os
-from utils.file_process import load_lines
+from med3d.utils.file_process import load_lines
 import numpy as np
 
 

train.py → med3d/train.py

@@ -4,16 +4,15 @@
 '''
 
 from setting import parse_opts 
-from datasets.brains18 import BrainS18Dataset 
+from med3d.datasets.brains18 import BrainS18Dataset
 from model import generate_model
 import torch
 import numpy as np
 from torch import nn
 from torch import optim
-from torch.optim import lr_scheduler
 from torch.utils.data import DataLoader
 import time
-from utils.logger import log
+from med3d.utils.logger import log
 from scipy import ndimage
 import os
 

setup.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python
+
+import os
+
+# Always prefer setuptools over distutils
+from setuptools import find_packages, setup
+
+# https://packaging.python.org/guides/single-sourcing-package-version/
+# http://blog.ionelmc.ro/2014/05/25/python-packaging/
+import med3d
+
+_PATH_ROOT = os.path.dirname(__file__)
+
+
+def _load_requirements(path_dir=_PATH_ROOT, comment_char='#'):
+    with open(os.path.join(path_dir, 'requirements.txt')) as file:
+        lines = [ln.strip() for ln in file.readlines()]
+    reqs = [ln[:ln.index(comment_char)] if comment_char in ln else ln for ln in lines]
+    return reqs
+
+
+# https://packaging.python.org/discussions/install-requires-vs-requirements /
+# keep the meta-data here for simplicity in reading this file... it's not obvious
+# what happens and to non-engineers they won't know to look in init ...
+# the goal of the project is simplicity for researchers, don't want to add too much
+# engineer specific practices
+setup(
+    name='MedicalNet',
+    version=med3d.__version__,
+    description=med3d.__docs__,
+    author=med3d.__author__,
+    author_email=med3d.__author_email__,
+    url=med3d.__homepage__,
+    license=med3d.__license__,
+    packages=find_packages(exclude=['tests', 'docs']),
+    long_description_content_type='text/markdown',
+    include_package_data=True,
+    zip_safe=False,
+    keywords=['deep learning', 'pytorch', 'AI'],
+    python_requires='>=3.6',
+    setup_requires=[],
+    install_requires=_load_requirements(_PATH_ROOT),
+    classifiers=[
+        'Environment :: Console',
+        'Natural Language :: English',
+        # How mature is this project? Common values are
+        #   3 - Alpha, 4 - Beta, 5 - Production/Stable
+        'Development Status :: 3 - Alpha',
+        # Indicate who your project is intended for
+        'Intended Audience :: Developers',
+        'Topic :: Scientific/Engineering :: Artificial Intelligence',
+        'Topic :: Scientific/Engineering :: Image Recognition',
+        'Topic :: Scientific/Engineering :: Information Analysis',
+        # Pick your license as you wish
+        # 'License :: OSI Approved :: BSD License',
+        'Operating System :: OS Independent',
+        # Specify the Python versions you support here. In particular, ensure
+        # that you indicate whether you support Python 2, Python 3 or both.
+        'Programming Language :: Python :: 3',
+    ],
+)