Add label check on import (#2935)

* Add label check on import

* include annotation type

* update changelog

* Make the message prettier

CHANGELOG.md

@@ -37,6 +37,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Improved maintanance of popups visibility (<https://github.com/openvinotoolkit/cvat/pull/2809>)
 - Image visualizations settings on canvas for faster access (<https://github.com/openvinotoolkit/cvat/pull/2872>)
 - Better scale management of left panel when screen is too small (<https://github.com/openvinotoolkit/cvat/pull/2880>)
+- Improved error messages for annotation import (<https://github.com/openvinotoolkit/cvat/pull/2935>)
 
 ### Deprecated
 

cvat/apps/dataset_manager/bindings.py

@@ -601,6 +601,9 @@ class CvatTaskDataExtractor(datumaro.SourceExtractor):
 
         return item_anno
 
+class CvatImportError(Exception):
+    pass
+
 def match_dm_item(item, task_data, root_hint=None):
     is_video = task_data.meta['task']['mode'] == 'interpolation'
 
@@ -615,8 +618,8 @@ def match_dm_item(item, task_data, root_hint=None):
         frame_number = cast(osp.basename(item.id)[len('frame_'):], int)
 
     if not frame_number in task_data.frame_info:
-        raise Exception("Could not match item id: '%s' with any task frame" %
-            item.id)
+        raise CvatImportError("Could not match item id: "
+            "'%s' with any task frame" % item.id)
     return frame_number
 
 def find_dataset_root(dm_dataset, task_data):
@@ -631,7 +634,6 @@ def find_dataset_root(dm_dataset, task_data):
         prefix = prefix[:-1]
     return prefix
 
-
 def import_dm_annotations(dm_dataset, task_data):
     shapes = {
         datumaro.AnnotationType.bbox: ShapeType.RECTANGLE,
@@ -667,26 +669,32 @@ def import_dm_annotations(dm_dataset, task_data):
             if 1 < s and group_map[g]}
         group_map = {g: i for i, g in enumerate([0] + sorted(group_map))}
 
-        for ann in item.annotations:
-            if ann.type in shapes:
-                task_data.add_shape(task_data.LabeledShape(
-                    type=shapes[ann.type],
-                    frame=frame_number,
-                    label=label_cat.items[ann.label].name,
-                    points=ann.points,
-                    occluded=ann.attributes.get('occluded') == True,
-                    z_order=ann.z_order,
-                    group=group_map.get(ann.group, 0),
-                    source='manual',
-                    attributes=[task_data.Attribute(name=n, value=str(v))
-                        for n, v in ann.attributes.items()],
-                ))
-            elif ann.type == datumaro.AnnotationType.label:
-                task_data.add_tag(task_data.Tag(
-                    frame=frame_number,
-                    label=label_cat.items[ann.label].name,
-                    group=group_map.get(ann.group, 0),
-                    source='manual',
-                    attributes=[task_data.Attribute(name=n, value=str(v))
-                        for n, v in ann.attributes.items()],
-                ))
+        for idx, ann in enumerate(item.annotations):
+            try:
+                if hasattr(ann, 'label') and ann.label is None:
+                    raise CvatImportError("annotation has no label")
+                if ann.type in shapes:
+                    task_data.add_shape(task_data.LabeledShape(
+                        type=shapes[ann.type],
+                        frame=frame_number,
+                        label=label_cat.items[ann.label].name,
+                        points=ann.points,
+                        occluded=ann.attributes.get('occluded') == True,
+                        z_order=ann.z_order,
+                        group=group_map.get(ann.group, 0),
+                        source='manual',
+                        attributes=[task_data.Attribute(name=n, value=str(v))
+                            for n, v in ann.attributes.items()],
+                    ))
+                elif ann.type == datumaro.AnnotationType.label:
+                    task_data.add_tag(task_data.Tag(
+                        frame=frame_number,
+                        label=label_cat.items[ann.label].name,
+                        group=group_map.get(ann.group, 0),
+                        source='manual',
+                        attributes=[task_data.Attribute(name=n, value=str(v))
+                            for n, v in ann.attributes.items()],
+                    ))
+            except Exception as e:
+                raise CvatImportError("Image {}: can't import annotation "
+                    "#{} ({}): {}".format(item.id, idx, ann.type.name, e))

cvat/apps/engine/views.py

@@ -37,6 +37,7 @@ from sendfile import sendfile
 import cvat.apps.dataset_manager as dm
 import cvat.apps.dataset_manager.views # pylint: disable=unused-import
 from cvat.apps.authentication import auth
+from cvat.apps.dataset_manager.bindings import CvatImportError
 from cvat.apps.dataset_manager.serializers import DatasetFormatsSerializer
 from cvat.apps.engine.frame_provider import FrameProvider
 from cvat.apps.engine.models import (
@@ -1030,7 +1031,17 @@ def _import_annotations(request, rq_id, rq_func, pk, format_name):
             os.remove(rq_job.meta['tmp_file'])
             exc_info = str(rq_job.exc_info)
             rq_job.delete()
-            return Response(data=exc_info, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
+
+            # RQ adds a prefix with exception class name
+            import_error_prefix = '{}.{}'.format(
+                CvatImportError.__module__, CvatImportError.__name__)
+            if exc_info.startswith(import_error_prefix):
+                exc_info = exc_info.replace(import_error_prefix + ': ', '')
+                return Response(data=exc_info,
+                    status=status.HTTP_400_BAD_REQUEST)
+            else:
+                return Response(data=exc_info,
+                    status=status.HTTP_500_INTERNAL_SERVER_ERROR)
 
     return Response(status=status.HTTP_202_ACCEPTED)