Fix df_

Author: dshabin

src/superannotate/lib/app/interface/sdk_interface.py

@@ -3409,7 +3409,7 @@ def aggregate_annotations_as_df(
     """
     from superannotate.lib.app.analytics.common import aggregate_annotations_as_df
 
-    aggregate_annotations_as_df(
+    return aggregate_annotations_as_df(
         project_root,
         include_classes_wo_annotations,
         include_comments,

src/superannotate/lib/core/usecases.py

@@ -10,7 +10,6 @@
 import zipfile
 from abc import ABC
 from abc import abstractmethod
-from collections import Counter
 from collections import defaultdict
 from collections import namedtuple
 from functools import cached_property
@@ -3178,12 +3177,6 @@ def execute(self):
                     ),
                 )
             )
-        image_names = [
-            annotation_path.replace(constances.PIXEL_ANNOTATION_POSTFIX, "").replace(
-                constances.VECTOR_ANNOTATION_POSTFIX, ""
-            )
-            for annotation_path in annotation_paths
-        ]
         images_data = self._backend_service.get_bulk_images(
             images=[image.name for image in images_detail],
             folder_id=self._folder.uuid,
@@ -3201,7 +3194,7 @@ def execute(self):
         annotations_to_upload = list(
             filter(lambda detail: detail.id is not None, images_detail)
         )
-        if len(images_data) < (len(image_names)):
+        if missing_annotations:
             self._response.errors = AppException(
                 f"Couldn't find image {','.join(map(lambda x: x.path, missing_annotations))} for annotation upload."
             )
@@ -4052,11 +4045,13 @@ def __init__(
     def extensions(self):
         if not self._extensions:
             return constances.DEFAULT_IMAGE_EXTENSIONS
+        return self._extensions
 
     @property
     def exclude_file_patterns(self):
         if not self._exclude_file_patterns:
             return constances.DEFAULT_FILE_EXCLUDE_PATTERNS
+        return self._exclude_file_patterns
 
     def validate_project_type(self):
         if self._project.project_type == constances.ProjectType.VIDEO.value:
@@ -4181,7 +4176,9 @@ def execute(self):
         images_to_upload = images_to_upload[: self.auth_data["availableImageCount"]]
         uploaded_images = []
         failed_images = []
-        with concurrent.futures.ThreadPoolExecutor(max_workers=self.MAX_WORKERS) as executor:
+        with concurrent.futures.ThreadPoolExecutor(
+            max_workers=self.MAX_WORKERS
+        ) as executor:
             results = [
                 executor.submit(self._upload_image, image_path)
                 for image_path in images_to_upload
@@ -4195,7 +4192,6 @@ def execute(self):
                 yield
 
         uploaded = []
-        # duplicates = []
         for i in range(0, len(uploaded_images), 500):
             response = AttachFileUrlsUseCase(
                 project=self._project,

tests/convertors/test_consensus.py

@@ -26,11 +26,17 @@ def export_path(self):
         return os.path.join(dirname(dirname(__file__)), self.TEST_EXPORT_ROOT)
 
     def test_consensus(self):
-        annot_types = ['polygon', 'bbox', 'point']
-        folder_names = ['consensus_1', 'consensus_2', 'consensus_3']
+        annot_types = ["polygon", "bbox", "point"]
+        folder_names = ["consensus_1", "consensus_2", "consensus_3"]
         df_column_names = [
-            'creatorEmail', 'imageName', 'instanceId', 'area', 'className',
-            'attributes', 'folderName', 'score'
+            "creatorEmail",
+            "imageName",
+            "instanceId",
+            "area",
+            "className",
+            "attributes",
+            "folderName",
+            "score",
         ]
         export_path = self.export_path
         for i in range(1, 4):
@@ -39,47 +45,53 @@ def test_consensus(self):
             self.PROJECT_NAME, self.export_path + "/classes/classes.json"
         )
         sa.upload_images_from_folder_to_project(
-            self.PROJECT_NAME, self.export_path + "/images", annotation_status="Completed"
+            self.PROJECT_NAME,
+            self.export_path + "/images",
+            annotation_status="Completed",
         )
         for i in range(1, 4):
             sa.upload_images_from_folder_to_project(
-                self.PROJECT_NAME + f'/{self.CONSENSUS_PREFIX}' + str(i),
+                self.PROJECT_NAME + f"/{self.CONSENSUS_PREFIX}" + str(i),
                 self.export_path + "/images",
-                annotation_status="Completed"
+                annotation_status="Completed",
             )
         time.sleep(2)
-        sa.upload_annotations_from_folder_to_project(self.PROJECT_NAME, self.export_path)
+        sa.upload_annotations_from_folder_to_project(
+            self.PROJECT_NAME, self.export_path
+        )
         for i in range(1, 4):
             sa.upload_annotations_from_folder_to_project(
-                self.PROJECT_NAME + f'/{self.CONSENSUS_PREFIX}' + str(i),
-                self.export_path + f'/{self.CONSENSUS_PREFIX}' + str(i)
+                self.PROJECT_NAME + f"/{self.CONSENSUS_PREFIX}" + str(i),
+                self.export_path + f"/{self.CONSENSUS_PREFIX}" + str(i),
             )
 
         for annot_type in annot_types:
-            res_df = sa.consensus(self.PROJECT_NAME, folder_names, annot_type=annot_type)
-            #test content of projectName column
-            assert sorted(res_df['folderName'].unique()) == folder_names
+            res_df = sa.consensus(
+                self.PROJECT_NAME, folder_names, annot_type=annot_type
+            )
+            # test content of projectName column
+            assert sorted(res_df["folderName"].unique()) == folder_names
 
-            #test structure of resulting DataFrame
+            # test structure of resulting DataFrame
             assert sorted(res_df.columns) == sorted(df_column_names)
 
-            #test lower bound of the score
-            assert (res_df['score'] >= 0).all()
+            # test lower bound of the score
+            assert (res_df["score"] >= 0).all()
 
-            #test upper bound of the score
-            assert (res_df['score'] <= 1).all()
+            # test upper bound of the score
+            assert (res_df["score"] <= 1).all()
 
         image_names = [
-            'bonn_000000_000019_leftImg8bit.png',
-            'bielefeld_000000_000321_leftImg8bit.png'
+            "bonn_000000_000019_leftImg8bit.png",
+            "bielefeld_000000_000321_leftImg8bit.png",
         ]
 
-        #test filtering images with given image names list
+        # test filtering images with given image names list
         res_images = sa.consensus(
             self.PROJECT_NAME,
             folder_names,
             export_root=export_path,
-            image_list=image_names
+            image_list=image_names,
         )
 
-        assert sorted(res_images['imageName'].unique()) == sorted(image_names)
+        assert sorted(res_images["imageName"].unique()) == sorted(image_names)

tests/convertors/test_dataloop.py

@@ -1,6 +1,6 @@
 from pathlib import Path
-import pytest
 
+import pytest
 import superannotate as sa
 
 
@@ -20,6 +20,7 @@ def test_dataloop_convert_vector(tmpdir):
     ptype = "Vector"
     # upload_project(out_dir, project_name, description, ptype)
 
+
 @pytest.mark.skip(reason="Need to adjust")
 def test_dataloop_convert_object(tmpdir):
     project_name = "dataloop2sa_vector_object"

tests/convertors/test_googlecloud.py

@@ -1,8 +1,8 @@
 from pathlib import Path
 
+import pytest
 import superannotate as sa
 
-import pytest
 
 @pytest.mark.skip(reason="Need to adjust")
 def test_googlecloud_convert_web(tmpdir):

tests/convertors/test_labelbox.py

@@ -1,8 +1,8 @@
 from pathlib import Path
 
+import pytest
 import superannotate as sa
 
-import pytest
 
 @pytest.mark.skip(reason="Need to adjust")
 def test_labelbox_convert_vector(tmpdir):

tests/convertors/test_sagemaker.py

@@ -1,8 +1,7 @@
 from pathlib import Path
 
-import superannotate as sa
-
 import pytest
+import superannotate as sa
 
 
 @pytest.mark.skip(reason="Need to adjust")

tests/convertors/test_supervisely.py

@@ -1,8 +1,7 @@
 from pathlib import Path
 
-import superannotate as sa
-
 import pytest
+import superannotate as sa
 
 
 @pytest.mark.skip(reason="Need to adjust")
@@ -90,8 +89,11 @@ def test_supervisely_convert_keypoint(tmpdir):
     description = "supervisely keypoint"
     ptype = "Vector"
     # upload_project(out_dir, project_name, description, ptype)
+
+
 #
 
+
 @pytest.mark.skip(reason="Need to adjust")
 def test_supervisely_convert_instance_pixel(tmpdir):
     project_name = "supervisely_test_instance_pixel"

tests/convertors/test_vgg.py

@@ -1,8 +1,8 @@
 from pathlib import Path
 
+import pytest
 import superannotate as sa
 
-import pytest
 
 @pytest.mark.skip(reason="Need to adjust")
 def test_vgg_convert_object(tmpdir):

tests/convertors/test_voc.py

@@ -1,8 +1,7 @@
 from pathlib import Path
 
-import superannotate as sa
-
 import pytest
+import superannotate as sa
 
 
 @pytest.mark.skip(reason="Need to adjust")