3d blob detection - Difference of Gaussian (DoG) method

Added a class to perform blob detection by using the difference of gaussian method from skimage. In the task blob detection in QIM notion there is an example of usage

qim3d/processing/blob_detection.py

@@ -4,12 +4,12 @@ import numpy as np
 from skimage import img_as_float
 
 class blob_detection():
-    def __init__(self, volume, background=0, min_sigma=1, max_sigma=50, sigma_ratio=1.6, threshold=0.5, overlap=0.5, threshold_rel=None, exclude_border=False):
+    def __init__(self, volume, background='dark', min_sigma=1, max_sigma=50, sigma_ratio=1.6, threshold=0.5, overlap=0.5, threshold_rel=None, exclude_border=False):
         """
         Initialize the blob detection object
         Args:
             volume: The volume to detect blobs in
-            background: 0 if background is darker than the blobs, 1 if background is lighter than the blobs
+            background: 'dark' if background is darker than the blobs, 'bright' if background is lighter than the blobs
             min_sigma: The minimum standard deviation for Gaussian kernel
             max_sigma: The maximum standard deviation for Gaussian kernel
             num_sigma: The number of standard deviations between min and max
@@ -17,7 +17,7 @@ class blob_detection():
             overlap: The fraction of area of two blobs that overlap
         """
         self.volume = volume
-        if background != 0:
+        if background == 'bright':
             self.volume = np.invert(self.volume)
         self.volume = img_as_float(self.volume)
         self.min_sigma = min_sigma
@@ -35,7 +35,7 @@ class blob_detection():
         Args:
             None
         Returns:    
-            blobs: The blobs found in the volume
+            blobs: The blobs found in the volume as (p, r, c, radius)
         """
         blobs = blob_dog(self.volume, min_sigma=self.min_sigma, max_sigma=self.max_sigma, sigma_ratio=self.sigma_ratio, threshold=self.threshold, overlap=self.overlap, threshold_rel=self.threshold_rel, exclude_border=self.exclude_border)
         blobs[:, 3] = blobs[:, 3] * np.sqrt(3) # Change sigma to radius