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

@@ -172,8 +172,15 @@ def _make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFram
     df = _df_insert_slices(df, acc_raw.shape_dict, expand_box_by)
 
     # TODO: make this contingent on whether seg is included
+    def _make_binary_mask(r):
+        acc = InMemoryDataAccessor(acc_obj_ids.data == r.label)
+        acc.get_mono(0, mip=True)
+        cropped = acc.crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data
+        return cropped
+
     df['binary_mask'] = df.apply(
-        lambda r: (acc_obj_ids.data == r.label).max(axis=-1)[r.y0: r.y1, r.x0: r.x1, 0],
+        # lambda r: (acc_obj_ids.data == r.label).max(axis=-1)[r.y0: r.y1, r.x0: r.x1, 0],
+        _make_binary_mask,
         axis=1,
         result_type='reduce',
     )
@@ -327,7 +334,7 @@ class RoiSet(object):
         :param params: optional arguments that influence the definition and representation of ROIs
         :return: object identities map
         """
-        return __class__.from_object_ids(acc_raw, _get_label_ids(acc_seg, allow_3d=allow_3d, connect_3d=connect_3d), params)
+        return RoiSet.from_object_ids(acc_raw, _get_label_ids(acc_seg, allow_3d=allow_3d, connect_3d=connect_3d), params)
 
 
     # TODO: generate overlapping RoiSet from multiple masks
@@ -519,13 +526,14 @@ class RoiSet(object):
                 patch[roi.relative_slice][:, :, 0, 0] = roi.binary_mask * 255
             else:
                 patch = np.zeros((roi.y1 - roi.y0, roi.x1 - roi.x0, 1, 1), dtype='uint8')
-                patch[:, :, 0, 0] = roi.binary_mask * 255
+                patch = roi.binary_mask * 255
 
             if pad_to:
                 patch = pad(patch, pad_to)
             return patch
 
         dfe = self._df.copy()
+        # TODO: can just pass function handle
         dfe['patch_mask'] = dfe.apply(lambda r: _make_patch_mask(r), axis=1)
         return dfe