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

@@ -174,7 +174,7 @@ def _make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFram
     # TODO: make this contingent on whether seg is included
     def _make_binary_mask(r):
         acc = InMemoryDataAccessor(acc_obj_ids.data == r.label)
-        cropped = acc.get_mono(0, mip=True).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data
+        cropped = acc.get_mono(0, mip=True).crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data[:, :, 0, 0]
         return cropped
 
     df['binary_mask'] = df.apply(
@@ -251,7 +251,8 @@ def _make_object_ids_from_df(df: pd.DataFrame, sd: dict) -> InMemoryDataAccessor
 
     def _label_obj(r):
         sl = np.s_[r.y0:r.y1, r.x0:r.x1, :, r.zi:r.zi + 1]
-        id_mask[sl] = id_mask[sl] + r.label * r.binary_mask
+        mask = np.expand_dims(r.binary_mask, (2, 3))
+        id_mask[sl] = id_mask[sl] + r.label * mask
 
     df.apply(_label_obj, axis=1)
     return InMemoryDataAccessor(id_mask)
@@ -523,10 +524,11 @@ class RoiSet(object):
                 patch = np.zeros((roi.ebb_h, roi.ebb_w, 1, 1), dtype='uint8')
                 patch[roi.relative_slice][:, :, 0, 0] = roi.binary_mask * 255
             else:
+                # TODO: shape issues here
                 patch = (roi.binary_mask * 255).astype('uint8')
             if pad_to:
                 patch = pad(patch, pad_to)
-            return patch
+            return np.expand_dims(patch, (2, 3))
 
         dfe = self._df.copy()
         dfe['patch_mask'] = dfe.apply(_make_patch_mask, axis=1)
@@ -787,7 +789,7 @@ class RoiSet(object):
             try:
                 ma_acc = generate_file_accessor(where / 'tight_patch_masks' / fname)
                 assert ma_acc.chroma == 1 and ma_acc.nz == 1
-                mask_data = ma_acc.data / np.iinfo(ma_acc.data.dtype).max
+                mask_data = ma_acc.data[:, :, 0, 0] / np.iinfo(ma_acc.data.dtype).max
                 return mask_data
             except Exception as e:
                 raise DeserializeRoiSet(e)