[OTE][release]Fix ignore labels handling in multilabel cls (#1627)

* Fix ignore handling in mpa dataset

* Always add ignore to label schema

* Update MPA

Author: sovrasov

external/model-preparation-algorithm/mpa_tasks/extensions/datasets/mpa_cls_dataset.py

@@ -169,21 +169,17 @@ def get_indices(self, new_classes):
     def load_annotations(self):
         include_empty = self.empty_label in self.labels
         for i, _ in enumerate(self.ote_dataset):
-            class_indices = []
             item_labels = self.ote_dataset[i].get_roi_labels(self.labels, include_empty=include_empty)
             ignored_labels = self.ote_dataset[i].ignored_labels
+            onehot_indices = np.zeros(len(self.labels))
             if item_labels:
                 for ote_lbl in item_labels:
                     if ote_lbl not in ignored_labels:
-                        class_indices.append(self.label_names.index(ote_lbl.name))
+                        onehot_indices[self.label_names.index(ote_lbl.name)] = 1
                     else:
-                        class_indices.append(-1)
-            else:  # this supposed to happen only on inference stage or if we have a negative in multilabel data
-                class_indices.append(-1)
-            onehot_indices = np.zeros(len(self.labels))
-            for idx in class_indices:
-                if idx != -1:  # TODO: handling ignored label?
-                    onehot_indices[idx] = 1
+                        # during training we filter ignored classes out,
+                        # during validation mmcv's mAP also filters -1 labels
+                        onehot_indices[self.label_names.index(ote_lbl.name)] = -1
             self.gt_labels.append(onehot_indices)
         self.gt_labels = np.array(self.gt_labels)
 

external/model-preparation-algorithm/submodule

@@ -220,13 +220,8 @@ def add_subtask_labels(dataset, info):
                     for stask in subtask:  # if has several subtasks
                         add_subtask_labels(dataset, stask)
 
+            label_schema.add_group(empty_group) # empty group is always added in geti
             for info in hierarchy_info:
-                if info[
-                    "task_type"
-                ] == "multi-label" and emptylabel not in label_schema.get_labels(
-                    include_empty=True
-                ):
-                    label_schema.add_group(empty_group)
                 add_subtask_labels(dataset, info)
         else:
             main_group = LabelGroup(