modif FindVoxelDimensionInMicrons() w/ re expression + try-except

brick/processing/input.py

@@ -34,6 +34,9 @@ import numpy as np_
 import sys as sy_
 from PIL import Image
 from PIL.ExifTags import TAGS
+import re
+
+size_voxel_in_micron = None
 
 
 def ImageVerification(image: array_t, channel: str) -> array_t:
@@ -70,6 +73,10 @@ def ImageVerification(image: array_t, channel: str) -> array_t:
 
 
 def IntensityNormalizedImage(image: array_t) -> array_t:
+    '''
+    Relative normalization of the image between 0 and 1.
+    No division per 0 since the image should not be constant (ImageVerification function).
+    '''
     #
     print('Relative Intensity Normalization between 0 and 1. Need to reevaluate the parameters !!!')
 
@@ -94,30 +101,35 @@ def IntensityNormalizedImage(image: array_t) -> array_t:
     # return result
 
 
-def VoxelDimensionInMicrons(data_path: str) -> array_t:
-    # TODO Verify if metadata are in the same format for all the images - if not, add a raise error ?
+def FindVoxelDimensionInMicrons(data_path: str) -> array_t:
+    #
+    if size_voxel_in_micron is not None:
+        return np_.array(size_voxel_in_micron)
+
+    else:
+        print('The size of a voxel is not specified in the parameters.')
+
+        try:
+            with Image.open(data_path) as img:  # Find the voxels dimensions in micron in the metadata.
+                meta_dict = {TAGS.get(key, 'missing'): img.tag[key] for key in
+                             img.tag}  # Use the exif tags into the image metadata
 
-    with Image.open(data_path) as img:  # Find the voxels dimensions in micron in the metadata.
-        meta_dict = {TAGS.get(key, 'missing'): img.tag[key] for key in
-                     img.tag}  # Use the exif tags into the image metadata
+            # Decode the tags text
+            metadata = meta_dict['missing'].decode('utf8')  # Decode the tags text
+            metadata = metadata.replace('\x00', '')
 
-    # Decode the tags text
-    metadata = meta_dict['missing'].decode('utf8')  # Decode the tags text
-    metadata = metadata.replace('\x00', '')
+            voxel_size = []  # Initialize the list of voxel size in str
+            for axe in 'XYZ':
+                pattern = 'Voxel' + axe + '.+\= (\d.+E.\d.)'  # Regular expression
+                voxel_size.append(re.findall(pattern, metadata)[0])
 
-    voxel_size = ['', '', '']  # Initialize the list of voxel size in str
-    for idaxe, axe in enumerate('XYZ'):
-        idvox = metadata.find('dblVoxel' + axe)  # Get the index of the voxel size for the axe X, Y, Z
-        idvox += 15
-        while metadata[idvox] != '\n':
-            voxel_size[idaxe] += metadata[idvox]
-            idvox += 1
-    voxel_size = np_.asarray(list(map(float, voxel_size)))
-    voxel_size_microns = 1.0e6 * voxel_size
-    print('Voxel dimension in the image is [X Y Z] =', voxel_size_microns, 'in microns. WARNING this method highly '
-                                                                           'depends on the format of the metadata.')
+            voxel_size = np_.array(list(map(float, voxel_size)))
+            voxel_size_microns = 1.0e6 * voxel_size
+            print('Voxel dimension in the image is [X Y Z] =', voxel_size_microns, 'in microns.')
+            return voxel_size_microns
 
-    return voxel_size_microns
+        except:
+            print('Unable to find the voxel dimensions in micron in the metadata. Please specify it in the parameters.')
 
 
 def ToPixels(micron: float, voxel_size_microns: array_t) -> int:

nutrimorph.py

@@ -89,7 +89,7 @@ start_time = tm_.time()
 
 
 # --- Images
-voxel_micron = in_.VoxelDimensionInMicrons(data_path)
+voxel_micron = in_.FindVoxelDimensionInMicrons(data_path)
 
 
 image = io_.imread(data_path)

parameters.py

@@ -32,6 +32,7 @@
 
 data_path = "./data/DIO_6H_6_1.70bis_2.2_3.tif"
 channel = 'G'
+size_voxel_in_micron = None  # -> list [X,Y,Z]
 with_plot = True
 
 soma_low_c = 0.15