RoiSet facilitates object detection models

• created distinct generator class methods for RoiSet
• RoiSet.from_bounding_boxes can create RoiSet with just YXWH coordinates and no segmentation, e.g. as output from object detection models
• can also inspect and quantify overlap between and within RoiSet(s), at both bounding box and segmentation level
• can generate RoiSet from polygon segmentation e.g. in COCO segmentation models

model_server/base/process.py

@@ -18,7 +18,7 @@ def is_mask(img):
         return True
     elif img.dtype == 'uint8':
         unique = np.unique(img)
-        if unique.shape[0] == 2 and np.all(unique == [0, 255]):
+        if unique.shape[0] <= 2 and np.all(unique == [0, 255]):
             return True
     return False
 
@@ -136,7 +136,14 @@ def smooth(img: np.ndarray, sig: float) -> np.ndarray:
     :param sig: threshold parameter
     :return: smoothed image
     """
-    return gaussian(img, sig)
+    ga = gaussian(img, sig, preserve_range=True)
+    if is_mask(img):
+        if img.dtype == 'bool':
+            return ga > ga.mean()
+        elif img.dtype == 'uint8':
+            return (255 * (ga > ga.mean())).astype('uint8')
+    else:
+        return ga
 
 class Error(Exception):
     pass