Fixed bgr -> gray bug for fluosv images.

ih/imgproc.py

@@ -326,7 +326,7 @@ class Image(object):
         Assumes that image is already binary.
         """
         if self._isColor():
-            binary = cv2.inRange(self.image.copy(), np.array([1, 1, 1], np.uint8), np.array([255, 255, 255], np.uint8))
+            binary = cv2.inRange(self.image.copy(), np.array([0, 0, 1], np.uint8), np.array([255, 255, 255], np.uint8))
         else:
             binary = self.image.copy()
         contours,hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, 2)
@@ -341,7 +341,7 @@ class Image(object):
         A helper function that draws all detected contours in the image onto the image.
         """
         if self._isColor():
-            binary = cv2.inRange(self.image.copy(), np.array([1, 1, 1], np.uint8), np.array([255, 255, 255], np.uint8))
+            binary = cv2.inRange(self.image.copy(), np.array([0, 0, 1], np.uint8), np.array([255, 255, 255], np.uint8))
         else:
             binary = self.image.copy()
         contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, 2)
@@ -1255,7 +1255,7 @@ class Image(object):
         and central normalized moments are prefixed with 'nu'.  This function
         is a wrapper to the OpenCV function `moments <http://docs.opencv.org/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html#moments>`_.
         """
-        moments = cv2.moments(cv2.inRange(self.image, np.array([1, 1, 1], np.uint8), np.array([255, 255, 255], np.uint8)))
+        moments = cv2.moments(cv2.inRange(self.image, np.array([0, 0, 1], np.uint8), np.array([255, 255, 255], np.uint8)))
         if self.conn:
             for id in moments:
                 self._addColumn(id)
@@ -1320,7 +1320,7 @@ class Image(object):
         Returns the center and radius of the minimum enclosing circle of all
         non-black pixels in the image.  The point of this function
         is not to threshold, so the contours are generated from
-        all the pixels that fall into the range [1, 1, 1], [255, 255, 255].
+        all the pixels that fall into the range [0, 0, 1], [255, 255, 255].
         """
         circle = cv2.minEnclosingCircle(self._getMergedContour())
         if self.conn:
@@ -1339,7 +1339,7 @@ class Image(object):
 
         Returns the area of the convex hull around all non black pixels in the image.
         The point of this function is not to threshold, so the contours are generate from
-        all the pixels that fall into the range [1, 1, 1], [255, 255, 255]
+        all the pixels that fall into the range [0, 0, 1], [255, 255, 255]
         """
         hull = cv2.contourArea(
                  cv2.approxPolyDP(
@@ -1362,9 +1362,9 @@ class Image(object):
         Returns the number of non-black pixels in the image.  Creates
         a temporary binary image to do this.  The point of this function
         is not to threshold, so the binary image is created by all
-        pixels that fall into the range [1, 1, 1], [255, 255, 255].
+        pixels that fall into the range [0, 0, 1], [255, 255, 255].
         """
-        pixelCount = cv2.countNonZero(cv2.inRange(self.image, np.array([1, 1, 1], np.uint8), np.array([255, 255, 255], np.uint8)))
+        pixelCount = cv2.countNonZero(cv2.inRange(self.image, np.array([0, 0, 1], np.uint8), np.array([255, 255, 255], np.uint8)))
         if self.conn:
             self._addColumn("pixels")
             self.conn.execute("update images set pixels=? where pegasusid=?", (pixelCount, self.dbid))