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/roiset.py

@@ -128,6 +128,8 @@ def filter_df_overlap_bbox(df1: pd.DataFrame, df2: pd.DataFrame = None) -> pd.Da
     :param df1: DataFrame with potentially overlapping bounding boxes
     :param df2: (optional) second DataFrame
     :return DataFrame describing subset of overlapping ROIs
+        bbox_overlaps_with: index of ROI that overlaps
+        bbox_intersec: pixel area of intersecting region
     """
 
     def _compare(r0, r1):
@@ -136,14 +138,21 @@ def filter_df_overlap_bbox(df1: pd.DataFrame, df2: pd.DataFrame = None) -> pd.Da
         olz = (r0.zi == r1.zi)
         return olx and oly and olz
 
+    def _intersec(r0, r1):
+        return (r0.x1 - r1.x0) * (r0.y1 - r1.y0)
+
     first = []
     second = []
+    intersec = []
 
     if df2 is not None:
         for pair in itertools.product(df1.index, df2.index):
             if _compare(df1.iloc[pair[0]], df2.iloc[pair[1]]):
                 first.append(pair[0])
                 second.append(pair[1])
+                intersec.append(
+                    _intersec(df1.iloc[pair[0]], df2.iloc[pair[1]])
+                )
     else:
         for pair in itertools.combinations(df1.index, 2):
             if _compare(df1.iloc[pair[0]], df1.iloc[pair[1]]):
@@ -151,9 +160,13 @@ def filter_df_overlap_bbox(df1: pd.DataFrame, df2: pd.DataFrame = None) -> pd.Da
                 second.append(pair[1])
                 first.append(pair[1])
                 second.append(pair[0])
+                isc = _intersec(df1.iloc[pair[0]], df1.iloc[pair[1]])
+                intersec.append(isc)
+                intersec.append(isc)
 
     sdf = df1.iloc[first]
     sdf.loc[:, 'bbox_overlaps_with'] = second
+    sdf.loc[:, 'bbox_intersec'] = intersec
     return sdf
 
 # TODO: option to quantify overlap e.g. IOU