Fix seg-pred-add logs

Author: dshabin

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

@@ -2599,9 +2599,25 @@ def upload_preannotations_from_folder_to_project(
             "The function does not support projects containing videos attached with URLs"
         )
 
+    if recursive_subfolders:
+        logger.info(
+            "When using recursive subfolder parsing same name annotations in different subfolders will overwrite each other.",
+        )
+
+    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.info("Existing annotations will be overwritten.",)
+    logger.info(
+        "Uploading all annotations from %s to project %s.", folder_path, project_name
+    )
+
     annotation_paths = get_annotation_paths(
         folder_path, from_s3_bucket, recursive_subfolders
     )
+    logger.info(
+        "Uploading %s annotations to project %s.", len(annotation_paths), project_name
+    )
     uploaded_annotations = []
     failed_annotations = []
     missing_annotations = []

src/superannotate/lib/core/usecases.py

@@ -4075,12 +4075,14 @@ def execute(self):
         image_ids = [image["id"] for image in images]
         image_names = [image["name"] for image in images]
 
-        self._service.run_segmentation(
+        res = self._service.run_segmentation(
             self._project.team_id,
             self._project.uuid,
             model_name=self._ml_model_name,
             image_ids=image_ids,
         )
+        if not res.ok:
+            return self._response
 
         succeded_imgs = []
         failed_imgs = []
@@ -4156,12 +4158,14 @@ def execute(self):
             if model.name == self._ml_model_name:
                 ml_model = model
 
-        self._service.run_prediction(
+        res = self._service.run_prediction(
             team_id=self._project.team_id,
             project_id=self._project.uuid,
             ml_model_id=ml_model.uuid,
             image_ids=image_ids,
         )
+        if not res.ok:
+            return self._response
 
         success_images = []
         failed_images = []

src/superannotate/lib/infrastructure/controller.py

@@ -62,7 +62,7 @@ def __init__(self, logger, config_path=constances.CONFIG_FILE_LOCATION):
             api_url=self.configs.get_one("main_endpoint").value,
             auth_token=ConfigRepository().get_one("token").value,
             logger=logger,
-            verify_ssl=verify_ssl
+            verify_ssl=verify_ssl,
         )
         self._s3_upload_auth_data = None
         self._projects = None

src/superannotate/lib/infrastructure/services.py

@@ -1,4 +1,3 @@
-import os
 from contextlib import contextmanager
 from datetime import datetime
 from typing import Dict
@@ -27,7 +26,9 @@ class BaseBackendService(SuerannotateServiceProvider):
     Base service class
     """
 
-    def __init__(self, api_url: str, auth_token: str, logger, paginate_by=None, verify_ssl=True):
+    def __init__(
+        self, api_url: str, auth_token: str, logger, paginate_by=None, verify_ssl=True
+    ):
         self.api_url = api_url
         self._auth_token = auth_token
         self.logger = logger
@@ -932,7 +933,7 @@ def run_segmentation(
             params={"team_id": team_id, "project_id": project_id},
             data={"model_name": model_name, "image_ids": image_ids},
         )
-        return res.json()
+        return res
 
     def run_prediction(
         self, team_id: int, project_id: int, ml_model_id: int, image_ids: list
@@ -948,7 +949,7 @@ def run_prediction(
                 "image_ids": image_ids,
             },
         )
-        return res.json()
+        return res
 
     def delete_image_annotations(
         self,