Fix frame step export for image tasks (#1615)

* use absolute frame numbers in interface

* update changelog

Co-authored-by: Nikita Manovich <40690625+nmanovic@users.noreply.github.com>

CHANGELOG.md

@@ -25,6 +25,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 -
 
 ### Fixed
+- Problem with exported frame stepped image task (<https://github.com/opencv/cvat/issues/1613>)
 - Fixed dataset filter item representation for imageless dataset items (<https://github.com/opencv/cvat/pull/1593>)
 - Fixed interpreter crash when trying to import `tensorflow` with no AVX instructions available (<https://github.com/opencv/cvat/pull/1567>)
 - Kibana wrong working time calculation with new annotation UI use (<https://github.com/opencv/cvat/pull/1654>)
@@ -85,6 +86,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - A problem with mask to polygons conversion when polygons are too small (<https://github.com/opencv/cvat/pull/1581>)
 - Unable to upload video with uneven size (<https://github.com/opencv/cvat/pull/1594>)
 - Fixed an issue with `z_order` having no effect on segmentations (<https://github.com/opencv/cvat/pull/1589>)
+
+### Security
 - Permission group whitelist check for analytics view (<https://github.com/opencv/cvat/pull/1608>)
 
 ## [1.0.0-beta.2] - 2020-04-30

cvat/apps/dataset_manager/bindings.py

@@ -97,16 +97,21 @@ class TaskData:
     def _get_immutable_attribute_id(self, label_id, attribute_name):
         return self._get_attribute_id(label_id, attribute_name, 'immutable')
 
+    def abs_frame_id(self, relative_id):
+        return relative_id * self._frame_step + self._db_task.data.start_frame
+
+    def rel_frame_id(self, absolute_id):
+        return (absolute_id - self._db_task.data.start_frame) // self._frame_step
+
     def _init_frame_info(self):
         if hasattr(self._db_task.data, 'video'):
             self._frame_info = {frame: {
-                "path": "frame_{:06d}".format(
-                    self._db_task.data.start_frame + frame * self._frame_step),
+                "path": "frame_{:06d}".format(self.abs_frame_id(frame)),
                 "width": self._db_task.data.video.width,
                 "height": self._db_task.data.video.height,
             } for frame in range(self._db_task.data.size)}
         else:
-            self._frame_info = {db_image.frame: {
+            self._frame_info = {self.rel_frame_id(db_image.frame): {
                 "path": db_image.path,
                 "width": db_image.width,
                 "height": db_image.height,
@@ -193,8 +198,7 @@ class TaskData:
     def _export_tracked_shape(self, shape):
         return TaskData.TrackedShape(
             type=shape["type"],
-            frame=self._db_task.data.start_frame +
-                shape["frame"] * self._frame_step,
+            frame=self.abs_frame_id(shape["frame"]),
             label=self._get_label_name(shape["label_id"]),
             points=shape["points"],
             occluded=shape["occluded"],
@@ -210,8 +214,7 @@ class TaskData:
         return TaskData.LabeledShape(
             type=shape["type"],
             label=self._get_label_name(shape["label_id"]),
-            frame=self._db_task.data.start_frame +
-                shape["frame"] * self._frame_step,
+            frame=self.abs_frame_id(shape["frame"]),
             points=shape["points"],
             occluded=shape["occluded"],
             z_order=shape.get("z_order", 0),
@@ -221,8 +224,7 @@ class TaskData:
 
     def _export_tag(self, tag):
         return TaskData.Tag(
-            frame=self._db_task.data.start_frame +
-                tag["frame"] * self._frame_step,
+            frame=self.abs_frame_id(tag["frame"]),
             label=self._get_label_name(tag["label_id"]),
             group=tag.get("group", 0),
             attributes=self._export_attributes(tag["attributes"]),
@@ -232,7 +234,7 @@ class TaskData:
         frames = {}
         def get_frame(idx):
             frame_info = self._frame_info[idx]
-            frame = self._db_task.data.start_frame + idx * self._frame_step
+            frame = self.abs_frame_id(idx)
             if frame not in frames:
                 frames[frame] = TaskData.Frame(
                     idx=idx,
@@ -299,8 +301,7 @@ class TaskData:
     def _import_tag(self, tag):
         _tag = tag._asdict()
         label_id = self._get_label_id(_tag.pop('label'))
-        _tag['frame'] = (int(_tag['frame']) -
-            self._db_task.data.start_frame) // self._frame_step
+        _tag['frame'] = self.rel_frame_id(int(_tag['frame']))
         _tag['label_id'] = label_id
         _tag['attributes'] = [self._import_attribute(label_id, attrib)
             for attrib in _tag['attributes']
@@ -316,8 +317,7 @@ class TaskData:
     def _import_shape(self, shape):
         _shape = shape._asdict()
         label_id = self._get_label_id(_shape.pop('label'))
-        _shape['frame'] = (int(_shape['frame']) -
-            self._db_task.data.start_frame) // self._frame_step
+        _shape['frame'] = self.rel_frame_id(int(_shape['frame']))
         _shape['label_id'] = label_id
         _shape['attributes'] = [self._import_attribute(label_id, attrib)
             for attrib in _shape['attributes']
@@ -327,14 +327,13 @@ class TaskData:
     def _import_track(self, track):
         _track = track._asdict()
         label_id = self._get_label_id(_track.pop('label'))
-        _track['frame'] = (min(int(shape.frame) for shape in _track['shapes']) -
-            self._db_task.data.start_frame) // self._frame_step
+        _track['frame'] = self.rel_frame_id(
+            min(int(shape.frame) for shape in _track['shapes']))
         _track['label_id'] = label_id
         _track['attributes'] = []
         _track['shapes'] = [shape._asdict() for shape in _track['shapes']]
         for shape in _track['shapes']:
-            shape['frame'] = (int(shape['frame']) - \
-                self._db_task.data.start_frame) // self._frame_step
+            shape['frame'] = self.rel_frame_id(int(shape['frame']))
             _track['attributes'] = [self._import_attribute(label_id, attrib)
                 for attrib in shape['attributes']
                 if self._get_immutable_attribute_id(label_id, attrib.name)]
@@ -567,7 +566,7 @@ def import_dm_annotations(dm_dataset, task_data):
     label_cat = dm_dataset.categories()[datumaro.AnnotationType.label]
 
     for item in dm_dataset:
-        frame_number = match_frame(item, task_data)
+        frame_number = task_data.abs_frame_id(match_frame(item, task_data))
 
         # do not store one-item groups
         group_map = {0: 0}

cvat/apps/dataset_manager/formats/mot.py

@@ -40,7 +40,7 @@ def _import(src_file, task_data):
 
         for item in dataset:
             item = item.wrap(id=int(item.id) - 1) # NOTE: MOT frames start from 1
-            frame_id = match_frame(item, task_data)
+            frame_number = task_data.abs_frame_id(match_frame(item, task_data))
 
             for ann in item.annotations:
                 if ann.type != datumaro.AnnotationType.bbox:
@@ -57,7 +57,7 @@ def _import(src_file, task_data):
                     outside=False,
                     keyframe=False,
                     z_order=ann.z_order,
-                    frame=frame_id,
+                    frame=frame_number,
                     attributes=[],
                 )