Pullrequest from Josef to allow recreation of fullimage by deletion and...

Pullrequest from Josef to allow recreation of fullimage by deletion and robustness changes in segmentation.py

dataset.py

@@ -104,8 +104,8 @@ class DataSet(object):
             from opticalscan import loadAndPasteImage
             
             # try to load png and check for detection contours
-            buggyimage = recreatefullimage
-            if not buggyimage and os.path.exists(self.getLegacyImageName()):
+            recreatefullimage = recreatefullimage or not os.path.exists(self.getLegacyImageName())
+            if not recreatefullimage:
                 img = cv2imread_fix(self.getLegacyImageName())
                 Nc = len(self.particlecontours)
                 if Nc>0:
@@ -113,12 +113,12 @@ class DataSet(object):
                     contpixels = img[contour[:,0,1],contour[:,0,0]]
                     if np.all(contpixels[:,1]==255) and np.all(contpixels[:,2]==0) \
                         and np.all(contpixels[:,0]==0):
-                        buggyimage = True
-                if not buggyimage:
+                        recreatefullimage = True
+                if not recreatefullimage:
                     cv2imwrite_fix(self.getImageName(), img)
                 del img
             
-            if buggyimage:
+            if recreatefullimage:
                 print("recreating fullimage from grid data")
                 imgdata = None
                 zvalimg = None

segmentation.py

@@ -279,6 +279,10 @@ class Segmentation(object):
         if return_step=="contrastcurve": return gray, 0
         
         # image blur for noise-reduction
+        if self.blurRadius%2 != 1:
+            self.blurRadius += 1
+            print('blur Radius was an even number, incremented blur Radius by 1')
+            
         blur = cv2.medianBlur(gray, self.blurRadius)
         blur = np.uint8(blur*(255/blur.max()))
         if return_step=="blurRadius": return blur, 0
@@ -331,7 +335,10 @@ class Segmentation(object):
             h, w = sure_fg.shape[:2]
             mask = np.zeros((h+2, w+2), np.uint8)
         for p in np.int32(deletepoints):
+            if p[0] >= 0 and p[1] >= 0:
                 cv2.floodFill(sure_fg, mask, tuple(p), 0)
+            else:
+                print('skipped del point at {}'.format(p))
         for p in np.int32(deletepoints):
             cv2.circle(sure_fg, tuple(p), int(seedradius), 0, -1)