Fixed pre-commit and some arguments bugs

CBICA · Oct 31, 2024 · a778abd · a778abd
1 parent 359f682
commit a778abd
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Showing 2 changed files with 36 additions and 46 deletions.
diff --git a/DLICV/__main__.py b/DLICV/__main__.py
@@ -1,9 +1,10 @@
 import argparse
 import json
 import os
-from pathlib import Path
 import shutil
+import sys
 import warnings
+from pathlib import Path
 
 import torch
 
@@ -15,12 +16,13 @@
 # VERSION = pkg_resources.require("NiChart_DLMUSE")[0].version
 VERSION = 1.0
 
+
 def main() -> None:
-    prog="DLICV"
+    prog = "DLICV"
     parser = argparse.ArgumentParser(
         prog=prog,
         description="DLICV - Deep Learning Intra Cranial Volume.",
-        usage = """
+        usage="""
         DLICV v{VERSION}
         ICV calculation for structural MRI data.
 
@@ -36,18 +38,22 @@ def main() -> None:
                    -o           /path/to/output    \
                    -device      cpu|cuda|mps
 
-        """.format(VERSION=VERSION),
+        """.format(
+            VERSION=VERSION
+        ),
     )
 
     # Required Arguments
     parser.add_argument(
         "-i",
+        "--in_dir",
         type=str,
         required=True,
         help="[REQUIRED] Input folder with T1 sMRI images (nii.gz).",
     )
     parser.add_argument(
         "-o",
+        "out_dir",
         type=str,
         required=True,
         help="[REQUIRED] Output folder. If it does not exist it will be created. Predicted segmentations will have the same name as their source images.",
@@ -200,14 +206,8 @@ def main() -> None:
     args.f = [0]
 
     if args.clear_cache:
-        shutil.rmtree(os.path.join(
-            Path(__file__).parent,
-            "nnunet_results"
-        ))
-        shutil.rmtree(os.path.join(
-            Path(__file__).parent,
-            ".cache"
-        ))
+        shutil.rmtree(os.path.join(Path(__file__).parent, "nnunet_results"))
+        shutil.rmtree(os.path.join(Path(__file__).parent, ".cache"))
         if not args.i or not args.o:
             print("Cache cleared and missing either -i / -o. Exiting.")
             sys.exit(0)
@@ -240,21 +240,16 @@ def main() -> None:
     )
 
     if args.clear_cache:
-        shutil.rmtree(os.path.join(
-            Path(__file__).parent,
-            "nnunet_results"
-        ))
-        shutil.rmtree(os.path.join(
-            Path(__file__).parent,
-            ".cache"
-        ))
+        shutil.rmtree(os.path.join(Path(__file__).parent, "nnunet_results"))
+        shutil.rmtree(os.path.join(Path(__file__).parent, ".cache"))
 
     # Check if model exists. If not exist, download using HuggingFace
     if not os.path.exists(model_folder):
         # HF download model
         print("DLICV model not found, downloading...")
 
         from huggingface_hub import snapshot_download
+
         local_src = Path(__file__).parent
         snapshot_download(repo_id="nichart/DLICV", local_dir=local_src)
         print("DLICV model has been successfully downloaded!")

diff --git a/setup.py b/setup.py
@@ -1,14 +1,13 @@
 """Setup tool for DLICV."""
 
-import io
-import os
 from pathlib import Path
+
 from setuptools import find_packages, setup
 
 this_directory = Path(__file__).parent
 long_description = (this_directory / "README.md").read_text()
 
-with open('requirements.txt') as f:
+with open("requirements.txt") as f:
     required = f.read().splitlines()
 
 setup(
@@ -26,29 +25,25 @@
     packages=find_packages(exclude=["tests", ".github"]),
     python_requires=">=3.8",
     install_requires=required,
-    entry_points={
-        "console_scripts": ["DLICV = DLICV.__main__:main"]
-        },
+    entry_points={"console_scripts": ["DLICV = DLICV.__main__:main"]},
     classifiers=[
-                    "Intended Audience :: Developers",
-                    "Intended Audience :: Science/Research",
-                    "Intended Audience :: Healthcare Industry",
-                    "Programming Language :: Python :: 3",
-                    "Topic :: Scientific/Engineering :: Artificial Intelligence",
-                    "Topic :: Scientific/Engineering :: Image Processing",
-                    "Topic :: Scientific/Engineering :: Medical Science Apps.",
-                ],
+        "Intended Audience :: Developers",
+        "Intended Audience :: Science/Research",
+        "Intended Audience :: Healthcare Industry",
+        "Programming Language :: Python :: 3",
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
+        "Topic :: Scientific/Engineering :: Image Processing",
+        "Topic :: Scientific/Engineering :: Medical Science Apps.",
+    ],
     license="By installing/using DLICV, the user agrees to the following license: See https://www.med.upenn.edu/cbica/software-agreement-non-commercial.html",
-    keywords = [
-                    'deep learning',
-                    'image segmentation',
-                    'semantic segmentation',
-                    'medical image analysis',
-                    'medical image segmentation',
-                    'nnU-Net',
-                    'nnunet'
-                ],
-    package_data={
-        "DLICV": ["VERSION"]
-        },
+    keywords=[
+        "deep learning",
+        "image segmentation",
+        "semantic segmentation",
+        "medical image analysis",
+        "medical image segmentation",
+        "nnU-Net",
+        "nnunet",
+    ],
+    package_data={"DLICV": ["VERSION"]},
 )