Merge pull request #627 from superannotateai/friday

Friday

Author: nareksa

docs/source/api_reference/helpers.rst

@@ -22,10 +22,3 @@ ________________________
 .. _ref_aggregate_annotations_as_df:
 .. automethod:: superannotate.SAClient.validate_annotations
 .. automethod:: superannotate.SAClient.aggregate_annotations_as_df
-
-----------
-
-Utility functions
---------------------------------
-
-.. autofunction:: superannotate.SAClient.consensus

docs/source/userguide/quickstart.rst

@@ -25,13 +25,6 @@ It can be installed on Ubuntu with:
 
    sudo apt-get install ffmpeg
 
-To use the :py:obj:`consensus` function on Windows and Mac platforms, you might also need to install the shapely package
-beforehand. The package works well only under the Anaconda distribution with:
-
-.. code-block:: bash
-
-   conda install shapely
-
 ----------
 
 

docs/source/userguide/utilities.rst

@@ -126,64 +126,3 @@ Example of created DataFrame:
 
 Each row represents annotation information. One full annotation with multiple
 attribute groups can be grouped under :code:`instanceId` field.
-
-
-Working with DICOM files
-------------------------
-
-JPEG images with names :file:`<dicom_file_name>_<frame_num>.jpg` will be created
-in :file:`<path_to_output_dir>`. Those JPEG images can be uploaded to
-SuperAnnotate platform using the regular:
-
-.. code-block:: python
-
-   sa.upload_images_from_folder_to_project(project, "<path_to_output_dir>")
-
-Some DICOM files can have image frames that are compressed. To load them, `GDCM :
-Grassroots DICOM library <http://gdcm.sourceforge.net/wiki/index.php/Main_Page>`_ needs to be installed:
-
-.. code-block:: bash
-
-   # using conda
-   conda install -c conda-forge gdcm
-
-   # or on Ubuntu with versions above 19.04
-   sudo apt install python3-gdcm
-
-Computing consensus scores for instances between several projects
------------------------------------------------------------------
-
-
-Consensus is a tool to compare the quallity of the annotations of the same image that is present in several projects.
-To compute the consensus scores:
-
-.. code-block:: python
-
-   res_df = sa.consensus([project_names], "<path_to_export_folder>", [image_list], "<annotation_type>")
-
-Here pandas DataFrame with following columns is returned: creatorEmail, imageName, instanceId, className, area, attribute, projectName, score
-
-.. image:: images/consensus_dataframe.png
-
-Besides the pandas DataFrame there is an option to get the following plots by setting the show_plots flag to True:
-
-* Box plot of consensus scores for each annotators
-* Box plot of consensus scores for each project
-* Scatter plots of consensus score vs instance area for each project
-
-.. code-block:: python
-
-   sa.consensus([project_names], "<path_to_export_folder>", [image_list], "<annotation_type>", show_plots=True)
-
-To the left of each box plot the original score points of that annotator is depicted, the box plots are colored by annotator.
-
-.. image:: images/consensus_annotators_box.png
-
-Analogically the box plots of consensus scores for each project are colored according to project name.
-
-.. image:: images/consensus_projects_box.png
-
-Scatter plot of consensus score vs instance area is separated by projects. Hovering on a point reveals its annotator and image name.
-The points are colored according to class name. Each annotator is represented with separate symbol.
-
-.. image:: images/consensus_scatter.png

requirements.txt

@@ -9,7 +9,7 @@ pandas~=1.3
 ffmpeg-python~=0.2
 pillow~=9.5
 aiofiles==23.1.0
-requests==2.30.0
+requests==2.31.0
 tqdm==4.64.0
 fire==0.4.0
 mixpanel==4.8.3

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

@@ -156,8 +156,8 @@ def get_folder_by_id(self, project_id: int, folder_id: int):
         response = self.controller.get_folder_by_id(
             folder_id=folder_id, project_id=project_id
         )
-
-        return FolderSerializer(response).serialize(
+        response.raise_for_status()
+        return FolderSerializer(response.data).serialize(
             exclude={"completedCount", "is_root"}
         )
 
@@ -173,12 +173,13 @@ def get_item_by_id(self, project_id: int, item_id: int):
         :return: item metadata
         :rtype: dict
         """
-
+        project_response = self.controller.get_project_by_id(project_id=project_id)
+        project_response.raise_for_status()
         response = self.controller.get_item_by_id(
-            item_id=item_id, project_id=project_id
+            item_id=item_id, project=project_response.data
         )
 
-        return ItemSerializer(response).serialize(exclude={"url", "meta"})
+        return ItemSerializer(response.data).serialize(exclude={"url", "meta"})
 
     def get_team_metadata(self):
         """Returns team metadata
@@ -1513,10 +1514,6 @@ def download_export(
         to_s3_bucket=None,
     ):
         """Download prepared export.
-
-        WARNING: Starting from version 1.9.0 :ref:`download_export <ref_download_export>` additionally
-        requires :py:obj:`project` as first argument.
-
         :param project: project name
         :type project: str
         :param export: export name

src/superannotate/lib/core/__init__.py

@@ -153,6 +153,36 @@ def setup_logging(level=DEFAULT_LOGGING_LEVEL, file_path=LOG_FILE_LOCATION):
 
 INVALID_JSON_MESSAGE = "Invalid json"
 
+PROJECT_SETTINGS_VALID_ATTRIBUTES = [
+    "Brightness",
+    "Fill",
+    "Contrast",
+    "ShowLabels",
+    "ShowComments",
+    "Image",
+    "Lines",
+    "AnnotatorFinish",
+    "PointSize",
+    "FontSize",
+    "WorkflowEnable",
+    "ClassChange",
+    "ShowEntropy",
+    "UploadImages",
+    "DeleteImages",
+    "Download",
+    "RunPredictions",
+    "RunSegmentations",
+    "ImageQuality",
+    "ImageAutoAssignCount",
+    "FrameMode",
+    "FrameRate",
+    "JumpBackward",
+    "JumpForward",
+    "UploadFileType",
+    "Tokenization",
+    "ImageAutoAssignEnable",
+]
+
 __alL__ = (
     FolderStatus,
     ProjectStatus,

src/superannotate/lib/core/repositories.py

@@ -36,11 +36,13 @@ def __init__(
         secret_key: str,
         session_token: str,
         bucket: str,
+        region: str,
     ):
         self._session = boto3.Session(
             aws_access_key_id=access_key,
             aws_secret_access_key=secret_key,
             aws_session_token=session_token,
+            region_name=region,
         )
 
         self._resource = self._session.resource("s3")

src/superannotate/lib/core/usecases/annotations.py

@@ -591,13 +591,20 @@ def prepare_annotation(self, annotation: dict, size) -> dict:
         )
         return annotation
 
+    @staticmethod
+    def get_mask_path(path: str) -> str:
+        if path.endswith(constants.PIXEL_ANNOTATION_POSTFIX):
+            replacement = constants.PIXEL_ANNOTATION_POSTFIX
+        else:
+            replacement = ".json"
+        parts = path.rsplit(replacement, 1)
+        return constants.ANNOTATION_MASK_POSTFIX.join(parts)
+
     async def get_annotation(
         self, path: str
     ) -> (Optional[Tuple[io.StringIO]], Optional[io.BytesIO]):
         mask = None
-        mask_path = path.replace(
-            constants.PIXEL_ANNOTATION_POSTFIX, constants.ANNOTATION_MASK_POSTFIX
-        )
+        mask_path = self.get_mask_path(path)
         if self._client_s3_bucket:
             content = self.get_annotation_from_s3(self._client_s3_bucket, path).read()
             if self._project.type == constants.ProjectType.PIXEL.value:

src/superannotate/lib/core/usecases/folders.py

@@ -29,14 +29,12 @@ def execute(self):
                 project_id=self._project_id,
                 team_id=self._team_id,
             )
+            if not response.ok:
+                self._response.errors = AppException(response.error)
         except AppException as e:
             self._response.errors = e
         else:
             self._response.data = response.data
-
-        if not response.ok:
-            self._response.errors = AppException(response.error)
-
         return self._response
 
 

src/superannotate/lib/core/usecases/images.py

@@ -756,6 +756,7 @@ def s3_repo(self):
             self._auth_data.data["secretAccessKey"],
             self._auth_data.data["sessionToken"],
             self._auth_data.data["bucket"],
+            self._auth_data.data["region"],
         )
 
     def validate_project_type(self):
@@ -952,6 +953,7 @@ def s3_repository(self):
                 self.auth_data["secretAccessKey"],
                 self.auth_data["sessionToken"],
                 self.auth_data["bucket"],
+                self.auth_data["region"],
             )
         return self._s3_repo_instance