def test_coco_desktop_object(tmpdir):
input_dir = Path(
"tests"
) / "converter_test" / "COCO" / "input" / "fromSuperAnnotate" / "cats_dogs_desktop"
out_dir = Path(tmpdir) / "coco_from_desktop"
sa.export_annotation_format(input_dir, out_dir, "COCO", "object_test",
"Vector", "object_detection", "Desktop")
def coco_desktop_object(tmpdir):
out_dir = tmpdir / "coco_from_desktop"
final_dir = tmpdir / "coco_to_Web"
sa.export_annotation_format(
"tests/converter_test/COCO/input/fromSuperAnnotate/cats_dogs_desktop",
str(out_dir), "COCO", "object_test", "Vector", "object_detection",
"Desktop")
image_list = glob(str(out_dir / 'train_set' / '*.jpg'))
for image in image_list:
shutil.copy(image, out_dir / Path(image).name)
shutil.rmtree(out_dir / 'train_set')
sa.import_annotation_format(str(out_dir), str(final_dir), "COCO",
"object_test_train", "Vector",
"object_detection", "Web")
project_name = "coco2sa_object_pipline"
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, final_dir / "classes" / "classes.json")
sa.upload_images_from_folder_to_project(project, final_dir)
sa.upload_annotations_from_folder_to_project(project, final_dir)
return 0
def test_instance_segmentation_sa2coco_vector(tmpdir):
input_dir = Path(
"tests"
) / "converter_test" / "COCO" / "input" / "fromSuperAnnotate" / "cats_dogs_vector_instance_segm"
out_path = Path(tmpdir) / "fromSuperAnnotate" / "instance_test_vector"
sa.export_annotation_format(
input_dir, out_path, "COCO", "instance_test_vector", "Vector",
"instance_segmentation"
)
def test_keypoint_detection_sa2coco(tmpdir):
input_dir = Path(
"tests"
) / "converter_test" / "COCO" / "input" / "fromSuperAnnotate" / "cats_dogs_vector_keypoint_det"
out_path = Path(tmpdir) / "fromSuperAnnotate" / "keypoint_test_vector"
sa.export_annotation_format(
input_dir, out_path, "COCO", "keypoint_test_vector", "Vector",
"keypoint_detection"
)
def test_panoptic_segmentation_sa2coco(tmpdir):
input_dir = Path(
"tests"
) / "converter_test" / "COCO" / "input" / "fromSuperAnnotate" / "cats_dogs_panoptic_segm"
out_path = Path(tmpdir) / "fromSuperAnnotate" / "panoptic_test"
sa.export_annotation_format(
input_dir, out_path, "COCO", "panoptic_test", "Pixel",
"panoptic_segmentation"
)
def instance_segmentation_sa2coco_vector(tmpdir):
out_path = tmpdir / "fromSuperAnnotate/instance_test_vector"
try:
sa.export_annotation_format(
"tests/converter_test/COCO/input/fromSuperAnnotate/cats_dogs_vector_instance_segm",
str(out_path), "COCO", "instance_test_vector", "Vector",
"instance_segmentation")
except Exception as e:
return 1
return 0
def keypoint_detection_sa2coco(tmpdir):
out_path = tmpdir / "fromSuperAnnotate/keypoint_test_vector"
try:
sa.export_annotation_format(
"tests/converter_test/COCO/input/fromSuperAnnotate/cats_dogs_vector_keypoint_det",
str(out_path), "COCO", "keypoint_test_vector", "Vector",
"keypoint_detection")
except Exception as e:
return 1
return 0
def panoptic_segmentation_sa2coco(tmpdir):
out_path = tmpdir / "fromSuperAnnotate/panoptic_test"
try:
sa.export_annotation_format(
"tests/converter_test/COCO/input/fromSuperAnnotate/cats_dogs_panoptic_segm",
str(out_path), "COCO", "panoptic_test", "Pixel",
"panoptic_segmentation")
except Exception as e:
return 1
return 0
def test_sa_to_coco_to_sa(tmpdir):
input_dir = Path("tests") / "sample_project_pixel"
output1 = Path(tmpdir) / 'to_coco'
output2 = Path(tmpdir) / 'to_sa'
sa.export_annotation_format(input_dir, output1, "COCO", "object_test",
"Pixel", "instance_segmentation", "Web")
sa.import_annotation_format(output1, output2, "COCO", "object_test",
"Pixel", "instance_segmentation", "Web",
'image_set')
project_name = 'coco_pipeline_new'
project = sa.search_projects(project_name, return_metadata=True)
for pr in project:
sa.delete_project(pr)
project = sa.create_project(project_name, 'test_instane', 'Pixel')
sa.upload_images_from_folder_to_project(project, output2)
sa.create_annotation_classes_from_classes_json(
project, output2 / "classes" / "classes.json")
sa.upload_annotations_from_folder_to_project(project, output2)