Merge branch 'master' of https://github.com/superannotateai/superannotate-python-sdk

Author: agyurjin

docs/source/index.rst

@@ -82,6 +82,7 @@ __________________
 - Convert annotation format from/to COCO
 - Add annotations to local SuperAnnotate format JSONs
 - CLI commands for simple tasks
+- Aggregate class/attribute distribution as histogram
 
 ----------
 

docs/source/superannotate.sdk.rst

@@ -330,3 +330,8 @@ ____________________
 .. autofunction:: superannotate.add_annotation_template_to_json
 .. autofunction:: superannotate.add_annotation_cuboid_to_json
 
+Aggregating class distribution from annotations
+_____________________________________________________________
+
+.. autofunction:: superannotate.class_distribution
+.. autofunction:: superannotate.attribute_distribution

docs/source/tutorial.sdk.rst

@@ -341,3 +341,26 @@ project with the found contributor as an QA:
 .. code-block:: python
 
    sa.share_project(project, "hovnatan@superannotate.com", user_role="QA")
+
+Aggregating class distribution across multiple projects
+______________________________
+
+After exporting annotations from multiple projects, it is possible to aggregate class distribution of annotated instances as follows
+
+.. code-block:: python
+
+   df = sa.class_distribution("<path_to_export_folder>", [project_names])
+
+Aggregated distribution is returned as pandas dataframe with columns class_name and count. Enabling visualize flag plots histogram of obtained distribution.
+
+.. code-block:: python
+
+   df = sa.class_distribution("<path_to_export_folder>", [project_names], visualize = True)
+
+Similarly aggregation of class attributes across multiple projects can be obtained with
+
+.. code-block:: python
+
+   df = sa.attribute_distribution("<path_to_export_folder>", [project_names], visualize = True)
+
+Here pandas dataframe with columns identifying attribute and corresponding instance count is returned. Within visualized histogram attributes of the same class are grouped by color and sorted accordingly.

superannotate/analytics/common.py

@@ -93,7 +93,7 @@ def __append_annotation(annotation_dict):
             annotation_point_labels = annotation["pointLabels"
                                                 ] if vector and len(
                                                     annotation["pointLabels"]
-                                                ) == 0 else None
+                                                ) != 0 else None
 
             attributes = annotation["attributes"]
             if not attributes: