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

Author: agyurjin

.coveragerc

@@ -1,3 +1,3 @@
 [report]
 exclude_lines =
-    raise AOBaseException\(
+    raise SABaseException\(

docs/source/tutorial.sdk.rst

@@ -239,7 +239,7 @@ to convert them to other annotation formats:
 
 .. code-block:: python
 
-    sa.export_annotation_format("<input_folder>", "<output_folder>", "<dataset_format>", "<dataset_name>", 
+    sa.export_annotation_format("<input_folder>", "<output_folder>", "<dataset_format>", "<dataset_name>",
     "<project_type>", "<task>", "<platform>")
 
 .. note::
@@ -256,7 +256,7 @@ You can find more information annotation format conversion :ref:`here <ref_conve
 
     # From SA panoptic format to COCO panoptic format
     sa.export_annotation_format(
-       "tests/converter_test/COCO/input/fromSuperAnnotate/cats_dogs_panoptic_segm", 
+       "tests/converter_test/COCO/input/fromSuperAnnotate/cats_dogs_panoptic_segm",
        "tests/converter_test/COCO/output/panoptic",
        "COCO", "panoptic_test", "Pixel","panoptic_segmentation","Web"
     )
@@ -277,8 +277,8 @@ You can find more information annotation format conversion :ref:`here <ref_conve
 
     # YOLO annotation format to SA Web platform annotation format
     sa.import_annotation_format(
-      'tests/converter_test/YOLO/input/toSuperAnnotate', 
-      'tests/converter_test/YOLO/output', 
+      'tests/converter_test/YOLO/input/toSuperAnnotate',
+      'tests/converter_test/YOLO/output',
       'YOLO', '', 'Vector', 'object_detection', 'Web'
       )
 

superannotate/analytics/common.py

@@ -1,6 +1,7 @@
 import json
 import logging
 from pathlib import Path
+import glob
 
 import pandas as pd
 from ..exceptions import SABaseException
@@ -215,21 +216,46 @@ def __get_image_metadata(image_name, annotations):
                 break
         return image_metadata
 
+    def __get_user_metadata(annotation):
+        annotation_created_at = pd.to_datetime(annotation.get("createdAt"))
+        annotation_created_by = annotation.get("createdBy")
+        annotation_creator_email = None
+        annotation_creator_role = None
+        if annotation_created_by:
+            annotation_creator_email = annotation_created_by.get("email")
+            annotation_creator_role = annotation_created_by.get("role")
+        annotation_creation_type = annotation.get("creationType")
+        annotation_updated_at = pd.to_datetime(annotation.get("updatedAt"))
+        annotation_updated_by = annotation.get("updatedBy")
+        annotation_updator_email = None
+        annotation_updator_role = None
+        if annotation_updated_by:
+            annotation_updator_email = annotation_updated_by.get("email")
+            annotation_updator_role = annotation_updated_by.get("role")
+        user_metadata = {                   
+            "createdAt": annotation_created_at,
+            "creatorRole": annotation_creator_role,
+            "creatorEmail": annotation_creator_email,
+            "creationType": annotation_creation_type,
+            "updatedAt": annotation_updated_at,
+            "updatorRole": annotation_updator_role,
+            "updatorEmail": annotation_updator_email
+        }
+        return user_metadata
+    
     annotations_paths = []
-
+    
     for path in Path(project_root).glob('*.json'):
-        if path.name.endswith('___objects.json'
-                             ) or path.name.endswith('___pixel.json'):
-            annotations_paths.append(path)
+        annotations_paths.append(path)
 
     if not annotations_paths:
         logger.warning(
             "No annotations found in project export root %s", project_root
         )
-
+    type_postfix = "___objects.json" if glob.glob("{}/*___objects.json".format(project_root)) else "___pixel.json"
     for annotation_path in annotations_paths:
         annotation_json = json.load(open(annotation_path))
-        image_name = annotation_path.name.split("___objects.json")[0]
+        image_name = annotation_path.name.split(type_postfix)[0]
         image_metadata = __get_image_metadata(image_name, annotation_json)
         annotation_instance_id = 0
         for annotation in annotation_json:
@@ -249,8 +275,9 @@ def __get_image_metadata(image_name, annotations):
                         "meta": comment_meta,
                         "commentResolved": comment_resolved,
                     }
+                    user_metadata = __get_user_metadata(annotation)
+                    annotation_dict.update(user_metadata)
                     annotation_dict.update(image_metadata)
-
                     __append_annotation(annotation_dict)
                 continue
             if annotation_type == "tag":
@@ -276,21 +303,6 @@ def __get_image_metadata(image_name, annotations):
             annotation_locked = annotation.get("locked")
             annotation_visible = annotation.get("visible")
             annotation_tracking_id = annotation.get("trackingId")
-            annotation_created_at = annotation.get("createdAt")
-            annotation_created_by = annotation.get("createdBy")
-            annotation_creator_email = None
-            annotation_creator_role = None
-            if annotation_created_by:
-                annotation_creator_email = annotation_created_by.get("email")
-                annotation_creator_role = annotation_created_by.get("role")
-            annotation_creation_type = annotation.get("creationType")
-            annotation_updated_at = annotation.get("updatedAt")
-            annotation_updated_by = annotation.get("updatedBy")
-            annotation_updator_email = None
-            annotation_updator_role = None
-            if annotation_updated_by:
-                annotation_updator_email = annotation_updated_by.get("email")
-                annotation_updator_role = annotation_updated_by.get("role")
             annotation_meta = None
             if annotation_type in ["bbox", "polygon", "polyline", "cuboid"]:
                 annotation_meta = {"points": annotation["points"]}
@@ -315,7 +327,7 @@ def __get_image_metadata(image_name, annotations):
             annotation_probability = annotation.get("probability")
             annotation_point_labels = annotation.get("pointLabels")
             attributes = annotation.get("attributes")
-
+            user_metadata = __get_user_metadata(annotation)
             if not attributes:
                 annotation_dict = {
                     "imageName": image_name,
@@ -331,14 +343,8 @@ def __get_image_metadata(image_name, annotations):
                     "pointLabels": annotation_point_labels,
                     "classColor": annotation_class_color,
                     "groupId": annotation_group_id,
-                    "createdAt": annotation_created_at,
-                    "creatorRole": annotation_creator_role,
-                    "creatorEmail": annotation_creator_email,
-                    "creationType": annotation_creation_type,
-                    "updatedAt": annotation_updated_at,
-                    "updatorRole": annotation_updator_role,
-                    "updatorEmail": annotation_updator_email
                 }
+                annotation_dict.update(user_metadata)
                 annotation_dict.update(image_metadata)
                 __append_annotation(annotation_dict)
             else:
@@ -375,14 +381,8 @@ def __get_image_metadata(image_name, annotations):
                         "pointLabels": annotation_point_labels,
                         "classColor": annotation_class_color,
                         "groupId": annotation_group_id,
-                        "createdAt": annotation_created_at,
-                        "creatorRole": annotation_creator_role,
-                        "creatorEmail": annotation_creator_email,
-                        "creationType": annotation_creation_type,
-                        "updatedAt": annotation_updated_at,
-                        "updatorRole": annotation_updator_role,
-                        "updatorEmail": annotation_updator_email
                     }
+                    annotation_dict.update(user_metadata)
                     annotation_dict.update(image_metadata)
                     __append_annotation(annotation_dict)
 

superannotate/db/projects.py

@@ -529,7 +529,7 @@ def upload_images_from_folder_to_project(
     if not isinstance(project, dict):
         project = get_project_metadata(project)
     if recursive_subfolders:
-        logger.warning(
+        logger.info(
             "When using recursive subfolder parsing same name images in different subfolders will overwrite each other."
         )
     if exclude_file_patterns is None:
@@ -910,14 +910,14 @@ def upload_annotations_from_folder_to_project(
 ):
     """Finds and uploads all JSON files in the folder_path as annotations to the project.
 
-    WARNING: The JSON files should follow specific naming convention. For Vector
+    The JSON files should follow specific naming convention. For Vector
     projects they should be named "<image_filename>___objects.json" (e.g., if
     image is cats.jpg the annotation filename should be cats.jpg___objects.json), for Pixel projects
     JSON file should be named "<image_filename>___pixel.json" and also second mask
     image file should be present with the name "<image_name>___save.png". In both cases
     image with <image_name> should be already present on the platform.
 
-    WARNING: Existing annotations will be overwritten.
+    Existing annotations will be overwritten.
 
     :param project: project name or metadata of the project to upload annotations to
     :type project: str or dict
@@ -932,15 +932,15 @@ def upload_annotations_from_folder_to_project(
     :rtype: list of strs
     """
     if recursive_subfolders:
-        logger.warning(
+        logger.info(
             "When using recursive subfolder parsing same name annotations in different subfolders will overwrite each other."
         )
 
-    logger.warning(
+    logger.info(
         "The JSON files should follow specific naming convention. For Vector projects they should be named '<image_name>___objects.json', for Pixel projects JSON file should be names '<image_name>___pixel.json' and also second mask image file should be present with the name '<image_name>___save.png'. In both cases image with <image_name> should be already present on the platform."
     )
 
-    logger.warning("Existing annotations will be overwritten.")
+    logger.info("Existing annotations will be overwritten.")
     if not isinstance(project, dict):
         project = get_project_metadata(project)
 
@@ -1155,14 +1155,14 @@ def upload_preannotations_from_folder_to_project(
 ):
     """Finds and uploads all JSON files in the folder_path as pre-annotations to the project.
 
-    WARNING: The JSON files should follow specific naming convention. For Vector
+    The JSON files should follow specific naming convention. For Vector
     projects they should be named "<image_filename>___objects.json" (e.g., if
     image is cats.jpg the annotation filename should be cats.jpg___objects.json), for Pixel projects
     JSON file should be named "<image_filename>___pixel.json" and also second mask
     image file should be present with the name "<image_name>___save.png". In both cases
     image with <image_name> should be already present on the platform.
 
-    WARNING: Existing pre-annotations will be overwritten.
+    Existing pre-annotations will be overwritten.
 
     :param project: project name or metadata of the project to upload pre-annotations to
     :type project: str or dict
@@ -1177,14 +1177,14 @@ def upload_preannotations_from_folder_to_project(
     :rtype: list of strs
     """
     if recursive_subfolders:
-        logger.warning(
+        logger.info(
             "When using recursive subfolder parsing same name pre-annotations in different subfolders will overwrite each other."
         )
-    logger.warning(
+    logger.info(
         "The JSON files should follow specific naming convention. For Vector projects they should be named '<image_name>___objects.json', for Pixel projects JSON file should be names '<image_name>___pixel.json' and also second mask image file should be present with the name '<image_name>___save.png'. In both cases image with <image_name> should be already present on the platform."
     )
 
-    logger.warning(
+    logger.info(
         "Identically named existing pre-annotations will be overwritten."
     )
     if not isinstance(project, dict):

superannotate/input_converters/conversion.py

@@ -321,7 +321,7 @@ def import_annotation_format(
     :type input_dir: str
     :param output_dir: Path to the folder, where you want to have converted dataset.
     :type output_dir: str
-    :param dataset_format: Annotation format to convert SuperAnnotate annotation format. Available candidates are: ["COCO", "VOC", "LabelBox", "DataLoop", 
+    :param dataset_format: Annotation format to convert SuperAnnotate annotation format. Available candidates are: ["COCO", "VOC", "LabelBox", "DataLoop",
                         "Supervisely", 'VGG', 'YOLO', 'SageMake', 'VoTT', 'GoogleCloud']
     :type dataset_format: str
     :param dataset_name: Name of the json file in the input_dir, which should be converted.

superannotate/input_converters/import_to_sa_conversions.py

@@ -1,13 +1,11 @@
 """
-Module which will run converters and convert from other 
+Module which will run converters and convert from other
 annotation formats to superannotate annotation format
 """
-import sys
-import os
 import glob
-import shutil
 import logging
-from argparse import Namespace
+import os
+import shutil
 
 from .converters.converters import Converter
 from ..exceptions import SABaseException