Friday

src/superannotate/__init__.py

@@ -1,10 +1,7 @@
 import os
 import sys
 
-
-
-__version__ = "4.4.7dev2"
-
+__version__ = "4.4.7dev6"
 
 sys.path.append(os.path.split(os.path.realpath(__file__))[0])
 

src/superannotate/lib/app/analytics/common.py

@@ -4,7 +4,6 @@
 import pandas as pd
 import plotly.express as px
 from lib.app.exceptions import AppException
-from lib.core import DEPRICATED_DOCUMENT_VIDEO_MESSAGE
 from superannotate.logger import get_default_logger
 
 
@@ -44,14 +43,6 @@ def aggregate_image_annotations_as_df(
     :rtype: pandas DataFrame
     """
 
-    json_paths = list(Path(str(project_root)).glob("*.json"))
-    if (
-        json_paths
-        and "___pixel.json" not in json_paths[0].name
-        and "___objects.json" not in json_paths[0].name
-    ):
-        raise AppException(DEPRICATED_DOCUMENT_VIDEO_MESSAGE)
-
     logger.info("Aggregating annotations from %s as pandas DataFrame", project_root)
 
     annotation_data = {
@@ -101,12 +92,16 @@ def aggregate_image_annotations_as_df(
     classes_json = json.load(open(classes_path))
     class_name_to_color = {}
     class_group_name_to_values = {}
+    freestyle_attributes = set()
     for annotation_class in classes_json:
         name = annotation_class["name"]
         color = annotation_class["color"]
         class_name_to_color[name] = color
         class_group_name_to_values[name] = {}
         for attribute_group in annotation_class["attribute_groups"]:
+            group_type = attribute_group.get("group_type")
+            if group_type and group_type in ["text", "numeric"]:
+                freestyle_attributes.add(attribute_group["name"])
             class_group_name_to_values[name][attribute_group["name"]] = []
             for attribute in attribute_group["attributes"]:
                 class_group_name_to_values[name][attribute_group["name"]].append(
@@ -175,10 +170,14 @@ def __get_user_metadata(annotation):
 
     if not annotations_paths:
         logger.warning(f"Could not find annotations in {project_root}.")
-    if len(list(Path(project_root).rglob("*___objects.json"))) > 0:
+
+    if "___objects.json" in annotations_paths[0].name:
         type_postfix = "___objects.json"
-    else:
+    elif "___pixel.json" in annotations_paths[0].name:
         type_postfix = "___pixel.json"
+    else:
+        type_postfix = ".json"
+
     for annotation_path in annotations_paths:
         annotation_json = json.load(open(annotation_path))
         parts = annotation_path.name.split(type_postfix)
@@ -294,6 +293,7 @@ def __get_user_metadata(annotation):
                         not in class_group_name_to_values[annotation_class_name][
                             attribute_group
                         ]
+                        and attribute_group not in freestyle_attributes
                     ):
                         logger.warning(
                             "Annotation class group value %s not in classes json. Skipping.",
@@ -383,9 +383,9 @@ def instance_consensus(inst_1, inst_2):
 
     :param inst_1: First instance for consensus score.
     :type inst_1: shapely object
+
     :param inst_2: Second instance for consensus score.
     :type inst_2: shapely object
-
     """
     if inst_1.type == inst_2.type == "Polygon":
         intersect = inst_1.intersection(inst_2)
@@ -404,19 +404,19 @@ def image_consensus(df, image_name, annot_type):
 
     :param df: Annotation data of all images
     :type df: pandas.DataFrame
+
     :param image_name: The image name for which the consensus score will be computed
     :type image_name: str
+
     :param annot_type: Type of annotation instances to consider. Available candidates are: ["bbox", "polygon", "point"]
     :type dataset_format: str
-
     """
 
     try:
         from shapely.geometry import Point, Polygon, box
     except ImportError:
         raise ImportError(
-            "To use superannotate.benchmark or superannotate.consensus functions please install "
-            "shapely package in Anaconda enviornment with # conda install shapely"
+            "To use superannotate.benchmark or superannotate.consensus functions please install shapely package."
         )
 
     image_df = df[df["imageName"] == image_name]

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

@@ -2176,8 +2176,10 @@ def attach_items_from_integrated_storage(
         """
         project, folder = self.controller.get_project_folder_by_path(project)
         _integration = None
+        if isinstance(integration, str):
+            integration = IntegrationEntity(name=integration)
         for i in self.controller.integrations.list().data:
-            if integration == i.name:
+            if integration.name == i.name:
                 _integration = i
                 break
         else:

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

@@ -1,4 +1,5 @@
 import copy
+import traceback
 from collections import defaultdict
 from concurrent.futures import as_completed
 from concurrent.futures import ThreadPoolExecutor
@@ -942,12 +943,10 @@ def execute(
             for future in as_completed(futures):
                 try:
                     ids = future.result()
-                except Exception as e:
-                    continue
-
-                self.item_ids.extend(ids)
+                    self.item_ids.extend(ids)
+                except Exception:
+                    logger.debug(traceback.format_exc())
 
-            futures = []
             subsets = self._service_provider.subsets.list(self.project).data
             subset = None
             for s in subsets:

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

@@ -140,6 +140,7 @@ def execute(self):
 
 
 class DownloadExportUseCase(BaseReportableUseCase):
+    FORBIDDEN_CHARS = "*./\[]:;|,\"\'"
     def __init__(
         self,
         service_provider: BaseServiceProvider,
@@ -204,8 +205,10 @@ def download_to_local_storage(self, destination: str, extract_zip=False):
                     raise AppException("Couldn't download export.")
                 time.sleep(1)
             self.reporter.stop_spinner()
-        filename = Path(export["path"]).name
-        filepath = Path(destination) / filename
+        filename = Path(export["path"]).stem
+        for char in DownloadExportUseCase.FORBIDDEN_CHARS:
+            filename=filename.replace(char, "_")
+        filepath = Path(destination) / (filename+'.zip')
         with requests.get(export["download"], stream=True) as response:
             response.raise_for_status()
             with open(filepath, "wb") as f:

tests/integration/annotations/video/test_get_annotations_per_frame.py

@@ -2,7 +2,6 @@
 import math
 import os
 from os.path import dirname
-from pathlib import Path
 
 from src.superannotate import SAClient
 from tests.integration.base import BaseTestCase
@@ -24,7 +23,7 @@ class TestGetAnnotations(BaseTestCase):
 
     @property
     def csv_path(self):
-        return os.path.join(dirname(dirname(dirname(__file__))), self.PATH_TO_URLS)
+        return os.path.join(DATA_SET_PATH, self.PATH_TO_URLS)
 
     @property
     def classes_path(self):

tests/integration/classes/test_create_annotation_class.py

@@ -146,21 +146,6 @@ def test_create_annotation_class(self):
             msg = str(e)
         self.assertEqual(msg, "Predefined tagging functionality is not supported for projects of type Video.")
 
-    def test_create_supported_annotation_class(self):
-        msg = ""
-        try:
-            sa.create_annotation_class(
-                self.PROJECT_NAME, "test_add", "#FF0000",
-                attribute_groups=[
-                    {
-                        "group_type": "text",
-                        "name": "name",
-                    }
-                ]
-            )
-        except Exception as e:
-            msg = str(e)
-        self.assertEqual(msg, "This project type doesn't support the attribute group types 'text' and 'numeric'.")
 
     def test_create_radio_annotation_class_attr_required(self):
         msg = ""

tests/integration/subsets/test_subsets.py

@@ -0,0 +1,28 @@
+from src.superannotate import SAClient
+
+from tests.integration.base import BaseTestCase
+
+sa = SAClient()
+
+
+class TestSubSets(BaseTestCase):
+    PROJECT_NAME = "Test-TestSubSets"
+    PROJECT_DESCRIPTION = "Desc"
+    PROJECT_TYPE = "Vector"
+    SUBSET_NAME = "SUBSET"
+
+    def test_add_items_to_subset(self):
+        item_names = [{"name": f"earth_mov_00{i}.jpg", "url": f"url_{i}"} for i in range(1, 6)]
+        sa.attach_items(
+            self.PROJECT_NAME,
+            item_names  # noqa
+        )
+        subset_data = []
+        for i in item_names:
+            subset_data.append(
+                {
+                    "name": i['name'],
+                    "path": self.PROJECT_NAME
+                }
+            )
+        sa.add_items_to_subset(self.PROJECT_NAME, self.SUBSET_NAME, subset_data)