comments removed

Author: agyurjin

superannotate/input_converters/import_to_sa_conversions.py

@@ -17,20 +17,19 @@ def _load_files(path_to_imgs, ptype):
     rec_search = str(Path('**') / '*.jpg')
     images_gen = Path(path_to_imgs).glob(rec_search)
     images = [path for path in images_gen]
-    # )
+
     if not images:
         logger.warning("Images doesn't exist")
 
     if ptype == 'Pixel':
         rec_search = str(Path('**') / '*.png')
         masks_gen = Path(path_to_imgs).glob(rec_search)
         masks = [path for path in masks_gen]
+        # if not masks:
+        #     logger.warning("Masks doesn't exist")
     else:
         masks = []
 
-    if not masks:
-        logger.warning("Masks doesn't exist")
-
     return images, masks
 
 

tests/converter_test/test_googlecloud.py

@@ -34,19 +34,6 @@ def googlecloud_convert_desktop(tmpdir):
         "Desktop"
     )
 
-    # project_name = "googlcloud_vector"
-
-    # projects = sa.search_projects(project_name, True)
-    # if projects:
-    #     sa.delete_project(projects[0])
-    # project = sa.create_project(project_name, "converter vector", "Vector")
-
-    # sa.create_annotation_classes_from_classes_json(
-    #     project, out_dir + "/classes/classes.json"
-    # )
-    # sa.upload_images_from_folder_to_project(project, out_dir)
-    # sa.upload_annotations_from_folder_to_project(project, out_dir)
-
     return 0
 
 

tests/converter_test/test_sagemaker.py

@@ -34,19 +34,6 @@ def sagemaker_instance_segmentation(tmpdir):
         'instance_segmentation', 'Desktop'
     )
 
-    # project_name = "sagemaker_object_detection"
-
-    # projects = sa.search_projects(project_name, True)
-    # if projects:
-    #     sa.delete_project(projects[0])
-    # project = sa.create_project(project_name, "converter vector", "Vector")
-
-    # sa.create_annotation_classes_from_classes_json(
-    #     project, out_dir + "/classes/classes.json"
-    # )
-    # sa.upload_images_from_folder_to_project(project, out_dir)
-    # sa.upload_annotations_from_folder_to_project(project, out_dir)
-
     return 0
 
 

tests/converter_test/test_supervisely.py

@@ -31,19 +31,6 @@ def supervisely_convert_object(tmpdir):
         str(out_dir), 'Supervisely', '', 'Vector', 'object_detection', 'Desktop'
     )
 
-    # project_name = "supervisely_test"
-
-    # projects = sa.search_projects(project_name, True)
-    # if projects:
-    #     sa.delete_project(projects[0])
-    # project = sa.create_project(project_name, "converter vector", "Vector")
-
-    # sa.create_annotation_classes_from_classes_json(
-    #     project, out_dir / "classes" / "classes.json"
-    # )
-    # sa.upload_images_from_folder_to_project(project, out_dir)
-    # sa.upload_annotations_from_folder_to_project(project, out_dir)
-
     return 0
 
 
@@ -55,19 +42,6 @@ def supervisely_convert_instance(tmpdir):
         'Web'
     )
 
-    # project_name = "supervisely_test"
-
-    # projects = sa.search_projects(project_name, True)
-    # if projects:
-    #     sa.delete_project(projects[0])
-    # project = sa.create_project(project_name, "converter vector", "Vector")
-
-    # sa.create_annotation_classes_from_classes_json(
-    #     project, out_dir / "classes" / "classes.json"
-    # )
-    # sa.upload_images_from_folder_to_project(project, out_dir)
-    # sa.upload_annotations_from_folder_to_project(project, out_dir)
-
     return 0
 
 

tests/converter_test/test_vgg.py

@@ -32,19 +32,6 @@ def vgg_convert_instance(tmpdir):
         "vgg_test", "Vector", "instance_segmentation", "Desktop"
     )
 
-    # project_name = "vgg_test"
-
-    # projects = sa.search_projects(project_name, True)
-    # if projects:
-    #     sa.delete_project(projects[0])
-    # project = sa.create_project(project_name, "converter vector", "Vector")
-
-    # sa.create_annotation_classes_from_classes_json(
-    #     project, out_dir / "classes" / "classes.json"
-    # )
-    # sa.upload_images_from_folder_to_project(project, out_dir)
-    # sa.upload_annotations_from_folder_to_project(project, out_dir)
-
     return 0
 
 

tests/converter_test/test_voc.py

@@ -32,20 +32,6 @@ def voc_vector_object(tmpdir):
         str(out_dir), "VOC", "", "Vector", "object_detection", "Desktop"
     )
 
-    # project_name = "voc2sa_vector_object"
-
-    # projects = sa.search_projects(project_name, True)
-
-    # if projects:
-    #     sa.delete_project(projects[0])
-    # project = sa.create_project(project_name, "converter vector", "Vector")
-
-    # sa.create_annotation_classes_from_classes_json(
-    #     project, out_dir + "/classes/classes.json"
-    # )
-    # sa.upload_images_from_folder_to_project(project, out_dir)
-    # sa.upload_annotations_from_folder_to_project(project, out_dir)
-
     return 0
 
 

tests/converter_test/test_vott.py

@@ -32,19 +32,6 @@ def vott_convert_instance(tmpdir):
         "", "Vector", "instance_segmentation", "Desktop"
     )
 
-    # project_name = "vott_vector"
-
-    # projects = sa.search_projects(project_name, True)
-    # if projects:
-    #     sa.delete_project(projects[0])
-    # project = sa.create_project(project_name, "converter vector", "Vector")
-
-    # sa.create_annotation_classes_from_classes_json(
-    #     project, out_dir + "/classes/classes.json"
-    # )
-    # sa.upload_images_from_folder_to_project(project, out_dir)
-    # sa.upload_annotations_from_folder_to_project(project, out_dir)
-
     return 0