added emoji

PyNutil/coordinate_extraction.py

@@ -17,8 +17,8 @@ def getCentroidsAndArea(Segmentation, pixelCutOff=0):
     """this function returns the center coordinate of each object in the segmentation.
     You can set a pixelCutOff to remove objects that are smaller than that number of pixels
     """
-    SegmentationBinary = ~np.all(Segmentation == 255, axis=2)
-    labels = measure.label(SegmentationBinary)
+    # SegmentationBinary = ~np.all(Segmentation == 255, axis=2)
+    labels = measure.label(Segmentation)
     # this finds all the objects in the image
     labelsInfo = measure.regionprops(labels)
     # remove objects that are less than pixelCutOff
@@ -144,11 +144,6 @@ def SegmentationToAtlasSpace(
     """combines many functions to convert a segmentation to atlas space. It takes care
     of deformations"""
     Segmentation = cv2.imread(SegmentationPath)
-    if method in ["per_object", "all"]:
-        # this function returns the centroids, area and coordinates of all the objects in the segmentation
-        # right now we only use centroids
-        centroids, area, coords = getCentroidsAndArea(Segmentation, pixelCutOff=0)
-        print("number of objects: ", len(centroids))
     if pixelID == "auto":
         # remove the background from the segmentation
         SegmentationNoBackGround = Segmentation[~np.all(Segmentation == 255, axis=2)]
@@ -157,7 +152,7 @@ def SegmentationToAtlasSpace(
         )  # remove background
         # currently only works for a single label
         pixelID = pixelID[0]
-    ID_pixels = findMatchingPixels(Segmentation, pixelID)
+
     # transform pixels to registration space (the registered image and segmentation have different dimensions)
     SegHeight = Segmentation.shape[0]
     SegWidth = Segmentation.shape[1]
@@ -166,8 +161,20 @@ def SegmentationToAtlasSpace(
     # this calculates reg/seg
     Yscale, Xscale = transformToRegistration(SegHeight, SegWidth, RegHeight, RegWidth)
 
-    # scale the seg coordinates to reg/seg
-    scaledY, scaledX = scalePositions(ID_pixels[0], ID_pixels[1], Yscale, Xscale)
+    if method in ["per_object", "all"]:
+        # this function returns the centroids, area and coordinates of all the objects in the segmentation
+        # right now we only use centroids
+        binary_seg = Segmentation == pixelID
+        binary_seg = np.all(binary_seg, axis=2)
+        centroids, area, coords = getCentroidsAndArea(binary_seg, pixelCutOff=0)
+        print("number of objects: ", len(centroids))
+        # print(centroids)
+
+    if method in ["per_pixel", "all"]:
+        ID_pixels = findMatchingPixels(Segmentation, pixelID)
+        # scale the seg coordinates to reg/seg
+        scaledY, scaledX = scalePositions(ID_pixels[0], ID_pixels[1], Yscale, Xscale)
+
     if nonLinear:
         if "markers" in slice:
             # this creates a triangulation using the reg width

PyNutil/main.py

@@ -53,11 +53,11 @@ class PyNutil:
         startTime = datetime.now()
         self.atlas_volume = readAtlasVolume(atlas_root_path + current_atlas_path)
         time_taken = datetime.now() - startTime
-        print(f"atlas volume loaded in: {time_taken}")
+        print(f"atlas volume loaded in: {time_taken} ✅")
         atlas_label_path = self.config["annotation_volumes"][self.atlas]["labels"]
         print("loading atlas labels")
         self.atlas_labels = pd.read_csv(atlas_root_path + atlas_label_path)
-        print("atlas labels loaded")
+        print("atlas labels loaded ✅")
 
     def get_coordinates(self, nonLinear=True, method="all"):
         if not hasattr(self, "atlas_volume"):
@@ -90,7 +90,7 @@ class PyNutil:
         self.label_df = PixelCountPerRegion(labeled_points, self.atlas_labels)
         self.labeled_points = labeled_points
 
-        print("quantification complete")
+        print("quantification complete ✅")
 
     def save_analysis(self, output_folder):
         if not hasattr(self, "pixel_points"):
@@ -113,4 +113,4 @@ class PyNutil:
                 output_folder + "/pixels_meshview.json",
                 self.atlas_labels,
             )
-        print("analysis saved")
+        print("analysis saved ✅")