sanity changes before purging dev-20200414

Former-commit-id: 91e453c

imgtools/io/common.py

@@ -1,17 +1,7 @@
 import os
-import glob
-import re
-from typing import Optional
-from collections import namedtuple
-from itertools import chain
-
-import numpy as np
-import pandas as pd
-import SimpleITK as sitk
-from pydicom import dcmread
+
 from pydicom.misc import is_dicom
 
-from ..utils import image_to_array
 
 
 
@@ -35,7 +25,7 @@ def find_dicom_paths(root_path: str, yield_directories: bool = False) -> str:
 
     """
     # TODO add some filtering options
-    for root, dirs, files in os.walk(root_path):
+    for root, _, files in os.walk(root_path):
         if yield_directories:
             if any((is_dicom(os.path.join(root, f)) for f in files)):
                 yield root

imgtools/io/loaders.py

@@ -3,10 +3,8 @@
 import re
 from typing import Optional, List
 from collections import namedtuple
-from itertools import chain
 import json
 
-import numpy as np
 import pandas as pd
 import SimpleITK as sitk
 import nrrd

imgtools/modules/dose.py

@@ -1,10 +1,13 @@
-import pydicom
-from matplotlib import pyplot as plt
 import os
-import glob
+import warnings
+
 import numpy as np
+from matplotlib import pyplot as plt
+
 import SimpleITK as sitk
-import warnings
+from pydicom import dcmread
+
+
 
 def read_image(path):
     reader = sitk.ImageSeriesReader()
@@ -32,7 +35,7 @@ def from_dicom_rtdose(cls, path):
 
         #Get the metadata
         dcm_path = os.path.join(path, os.listdir(path)[0])
-        df = pydicom.dcmread(dcm_path)
+        df = dcmread(dcm_path)
 
         #Convert to SUV
         factor = float(df.DoseGridScaling)

imgtools/modules/pet.py

@@ -1,11 +1,13 @@
-import pydicom
-from matplotlib import pyplot as plt
 import os
-import numpy as np
-import SimpleITK as sitk
 import warnings
 import datetime
 
+import numpy as np
+from matplotlib import pyplot as plt
+
+import SimpleITK as sitk
+from pydicom import dcmread
+
 def read_image(path):
     reader = sitk.ImageSeriesReader()
     dicom_names = reader.GetGDCMSeriesFileNames(path)
@@ -37,7 +39,7 @@ def from_dicom_pet(cls, path, type="SUV"):
         '''
         pet      = read_image(path)
         path_one = os.path.join(path,os.listdir(path)[0])
-        df       = pydicom.dcmread(path_one)
+        df       = dcmread(path_one)
         try:
             if type=="SUV":
                 factor = df.to_json_dict()['70531000']["Value"][0]

imgtools/modules/structureset.py

@@ -5,12 +5,11 @@
 import numpy as np
 import SimpleITK as sitk
 from pydicom import dcmread
-from itertools import chain, groupby
+from itertools import groupby
 from skimage.draw import polygon2mask
 
 from .segmentation import Segmentation
 from ..utils import physical_points_to_idxs
-from ..utils import array_to_image
 
 
 def _get_roi_points(rtstruct, roi_index):

imgtools/ops/functional.py

@@ -4,6 +4,8 @@
 from typing import Sequence, Union, Tuple, Optional
 from collections import namedtuple
 
+from imgtools.modules import segmentation
+
 from ..modules import Segmentation
 
 
@@ -381,7 +383,8 @@ def bounding_box(mask: sitk.Image, label: int = 1) -> Tuple[Tuple, Tuple]:
     """
 
     if isinstance(mask, Segmentation):
-        mask = mask.get_label(label=label, relabel=True)
+        seg = Segmentation(mask)
+        mask = seg.get_label(label=label, relabel=True)
 
     filter_ = sitk.LabelShapeStatisticsImageFilter()
     filter_.Execute(mask)
@@ -418,7 +421,8 @@ def centroid(mask: sitk.Image,
     """
 
     if isinstance(mask, Segmentation):
-        mask = mask.get_label(label=label, relabel=True)
+        seg = Segmentation(mask)
+        mask = seg.get_label(label=label, relabel=True)
 
     filter_ = sitk.LabelShapeStatisticsImageFilter()
     filter_.Execute(mask)
@@ -460,7 +464,8 @@ def crop_to_mask_bounding_box(image: sitk.Image,
     """
 
     if isinstance(mask, Segmentation):
-        mask = mask.get_label(label=label, relabel=True)
+        seg = Segmentation(mask)
+        mask = seg.get_label(label=label, relabel=True)
 
     if isinstance(margin, Sequence):
         margin = np.asarray(margin)
@@ -576,7 +581,8 @@ def image_statistics(image: sitk.Image,
 
     if mask is not None:
         if isinstance(mask, Segmentation):
-            mask = mask.get_label(label=label, relabel=True)
+            seg = Segmentation(mask)
+            mask = seg.get_label(label=label, relabel=True)
 
         filter_ = sitk.LabelStatisticsImageFilter()
         filter_.Execute(image, mask)

imgtools/ops/ops.py

@@ -1,6 +1,4 @@
-from posixpath import expanduser
 from typing import List, TypeVar, Sequence, Union, Tuple, Optional, Any
-from itertools import chain
 
 import numpy as np
 import SimpleITK as sitk

imgtools/utils/imageutils.py

@@ -33,7 +33,7 @@ def image_to_array(image):
 def show_image(image, mask=None, ax=None):
     import matplotlib.pyplot as plt
     if ax is None:
-        fig, ax = plt.subplots()
+        ax = plt.subplots()
 
     image_array, *_ = image_to_array(image)