def test_add_bbox_noinit(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(
PROJECT_NAME_NOINIT, return_metadata=True
)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(
PROJECT_NAME_NOINIT, PROJECT_DESCRIPTION, "Vector"
)
sa.upload_images_from_folder_to_project(
project, PATH_TO_SAMPLE_PROJECT, annotation_status="InProgress"
)
sa.create_annotation_classes_from_classes_json(
project, PATH_TO_SAMPLE_PROJECT / "classes" / "classes.json"
)
sa.create_annotation_class(project, "test_add", "#FF0000")
images = sa.search_images(project, "example_image_1")
image_name = images[0]
sa.add_annotation_bbox_to_image(
project, image_name, [10, 10, 500, 100], "test_add"
)
sa.add_annotation_polygon_to_image(
project, image_name, [100, 100, 500, 500, 200, 300], "test_add"
)
annotations_new = sa.get_image_annotations(project,
image_name)["annotation_json"]
assert len(annotations_new) == 2
export = sa.prepare_export(project, include_fuse=True)
sa.download_export(project, export, tmpdir)
assert len(list(Path(tmpdir).rglob("*.*"))) == 4
def test_anntotation_class_new():
projects = sa.search_projects(PROJECT_NAME, return_metadata=True)
for project in projects:
sa.delete_project(project)
sa.create_project(PROJECT_NAME, "tt", "Vector")
sa.create_annotation_class(PROJECT_NAME, "tt", "#FFFFFF")
assert len(sa.search_annotation_classes(PROJECT_NAME)) == 1
sa.create_annotation_class(PROJECT_NAME, "tt", "#FFFFFF")
assert len(sa.search_annotation_classes(PROJECT_NAME)) == 1
def test_add_bbox_noinit(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME_NOINIT,
return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME_NOINIT, PROJECT_DESCRIPTION,
"Vector")
sa.upload_images_from_folder_to_project(project,
PATH_TO_SAMPLE_PROJECT,
annotation_status="InProgress")
sa.create_annotation_classes_from_classes_json(
project, PATH_TO_SAMPLE_PROJECT / "classes" / "classes.json")
sa.create_annotation_class(project, "test_add", "#FF0000")
images = sa.search_images(project, "example_image_1")
image_name = images[0]
sa.add_annotation_bbox_to_image(project, image_name, [10, 10, 500, 100],
"test_add")
sa.add_annotation_polygon_to_image(project, image_name,
[100, 100, 500, 500, 200, 300],
"test_add")
annotations_new = sa.get_image_annotations(project,
image_name)["annotation_json"]
assert len(annotations_new["instances"]) == 2
export = sa.prepare_export(project, include_fuse=True)
sa.download_export(project, export, tmpdir)
non_empty_annotations = 0
json_files = tmpdir.glob("*.json")
for json_file in json_files:
json_ann = json.load(open(json_file))
if "instances" in json_ann and len(json_ann["instances"]) > 0:
non_empty_annotations += 1
assert len(json_ann["instances"]) == 2
assert non_empty_annotations == 1
def test_annotation_classes():
projects = sa.search_projects(PROJECT_NAME, return_metadata=True)
for project in projects:
sa.delete_project(project)
project = sa.create_project(PROJECT_NAME, "test1", "Vector")
clss = sa.search_annotation_classes(project)
assert len(clss) == 0
ac = sa.create_annotation_class(project, "fff", "#FFFFFF")
clss = sa.search_annotation_classes(project)
assert len(clss) == 1
ac = sa.search_annotation_classes(project, "ff")[0]
sa.delete_annotation_class(project, ac)
clss = sa.search_annotation_classes(project)
assert len(clss) == 0
sa.delete_project(project)
def test_video(tmpdir):
tmpdir = Path(tmpdir)
projects = sa.search_projects(PROJECT_NAME1, return_metadata=True)
for project in projects:
sa.delete_project(project)
project = sa.create_project(PROJECT_NAME1, "test", "Vector")
time.sleep(1)
sa.create_annotation_class(project, "fr", "#FFAAAA")
time.sleep(1)
sa.create_annotation_class(project, "fr2", "#FFAACC")
sa.upload_videos_from_folder_to_project(
project, "./tests/sample_videos", target_fps=2
)
projects = sa.search_projects(PROJECT_NAME2, return_metadata=True)
for project in projects:
sa.delete_project(project)
project = sa.create_project(PROJECT_NAME2, "test", "Vector")
subprocess.run(
f'superannotatecli upload-videos --project "{PROJECT_NAME2}" --folder ./tests/sample_videos --target-fps 2',
check=True,
shell=True
)
time.sleep(5)
sa.create_annotation_class(project, "fr2", "#FFAACC")
assert len(sa.search_images(PROJECT_NAME1)) == len(
sa.search_images(PROJECT_NAME2)
)
sa.create_folder(project, "new folder")
sa.upload_videos_from_folder_to_project(
PROJECT_NAME2 + "/new folder", "./tests/sample_videos", target_fps=2
)
assert len(sa.search_images(PROJECT_NAME2 + "/new folder")) == len(
sa.search_images(PROJECT_NAME2)
)
def sdk_uplaod(project_name, image_path):
"""Upload Images via SA sdk"""
project_metadata = sa.get_project_metadata(project_name)
_uploaded, _skipped, _duplicate = sa.upload_images_from_folder_to_project(
project=project_metadata["name"], folder_path="./images")
sa.upload_annotations_from_folder_to_project(project_name, "./annotations")
if __name__ == "__main__":
height = 1600
width = 1600
count = 100
project_name = "Large Dataset2"
image_path = "./images"
sa.create_project(project_name, "x", "Vector")
sa.create_annotation_class(project_name, "CUBOID", "#FFFFFF")
sa.create_annotation_class(project_name, "BBOX", "#FFFFFF")
sa.create_annotation_class(project_name, "POLYGON", "#FFFFFF")
sa.create_annotation_class(project_name, "POLYLINE", "#FFFFFF")
sa.create_annotation_class(project_name, "ELLIPSE", "#FFFFFF")
if os.path.exists("./images"):
shutil.rmtree("./images")
if os.path.exists("./annotations"):
shutil.rmtree("./annotations")
pathlib.Path("./images").mkdir(exist_ok=True)
pathlib.Path("./annotations").mkdir(exist_ok=True)
generate_images(width, height, count)
sdk_uplaod(project_name, image_path)
def test_add_bbox(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME, return_metadata=True)
for pr in projects_found:
if pr["name"] == PROJECT_NAME:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME, PROJECT_DESCRIPTION, "Vector")
sa.upload_images_from_folder_to_project(PROJECT_NAME,
PATH_TO_SAMPLE_PROJECT,
annotation_status="InProgress")
sa.create_annotation_classes_from_classes_json(
project, PATH_TO_SAMPLE_PROJECT / "classes" / "classes.json")
sa.create_annotation_class(
project, "test_add", "#FF0000",
[{
"name": "height",
"attributes": [{
"name": "tall"
}, {
"name": "short"
}]
}])
sa.upload_annotations_from_folder_to_project(project,
PATH_TO_SAMPLE_PROJECT)
images = sa.search_images(project, "example_image_1")
image_name = images[0]
annotations = sa.get_image_annotations(project,
image_name)["annotation_json"]
sa.add_annotation_bbox_to_image(project, image_name, [10, 10, 500, 100],
"test_add")
sa.add_annotation_polyline_to_image(project, image_name,
[110, 110, 510, 510, 600, 510],
"test_add")
sa.add_annotation_polygon_to_image(project, image_name,
[100, 100, 500, 500, 200, 300],
"test_add", [{
"name": "tall",
"groupName": "height"
}])
sa.add_annotation_point_to_image(project, image_name, [250, 250],
"test_add")
sa.add_annotation_ellipse_to_image(project, image_name,
[405, 405, 20, 70, 15], "test_add")
sa.add_annotation_template_to_image(project, image_name,
[600, 30, 630, 30, 615, 60],
[1, 3, 2, 3], "test_add")
sa.add_annotation_cuboid_to_image(project, image_name,
[800, 500, 900, 600, 850, 450, 950, 700],
"test_add")
sa.add_annotation_comment_to_image(project, image_name, "hey", [100, 100],
"*****@*****.**", True)
annotations_new = sa.get_image_annotations(project,
image_name)["annotation_json"]
json.dump(annotations_new, open(tmpdir / "new_anns.json", "w"))
assert len(annotations_new["instances"]) + len(
annotations_new["comments"]) == len(annotations["instances"]) + len(
annotations["comments"]) + 8
export = sa.prepare_export(project, include_fuse=True)
sa.download_export(project, export, tmpdir)
df = sa.aggregate_annotations_as_df(tmpdir)
print(df)
print(image_name)
num = len(
df[df["imageName"] == image_name]["instanceId"].dropna().unique())
assert num == len(
annotations["instances"]
) - 3 + 7 # -6 for 3 comments and 3 invalid annotations, className or attributes
def test_create_like_project(tmpdir):
tmpdir = Path(tmpdir)
projects = sa.search_projects(PROJECT_NAME, return_metadata=True)
for project in projects:
sa.delete_project(project)
sa.create_project(PROJECT_NAME, "tt", "Vector")
sa.create_annotation_class(PROJECT_NAME, "rrr", "#FFAAFF")
old_settings = sa.get_project_settings(PROJECT_NAME)
for setting in old_settings:
if "attribute" in setting and setting["attribute"] == "Brightness":
brightness_value = setting["value"]
sa.set_project_settings(PROJECT_NAME, [{
"attribute": "Brightness",
"value": brightness_value + 10
}])
sa.set_project_workflow(PROJECT_NAME, [{
"step": 1,
"className": "rrr",
"tool": 3
}])
users = sa.search_team_contributors()
sa.share_project(PROJECT_NAME, users[1], "QA")
projects = sa.search_projects(PROJECT_NAME2, return_metadata=True)
for project in projects:
sa.delete_project(project)
new_project = sa.clone_project(PROJECT_NAME2,
PROJECT_NAME,
copy_contributors=True)
assert new_project["description"] == "tt"
assert new_project["type"] == 1
time.sleep(1)
ann_classes = sa.search_annotation_classes(PROJECT_NAME2,
return_metadata=True)
assert len(ann_classes) == 1
assert ann_classes[0]["name"] == "rrr"
assert ann_classes[0]["color"] == "#FFAAFF"
new_settings = sa.get_project_settings(PROJECT_NAME2)
for setting in new_settings:
if "attribute" in setting and setting["attribute"] == "Brightness":
new_brightness_value = setting["value"]
assert new_brightness_value == brightness_value + 10
new_workflow = sa.get_project_workflow(PROJECT_NAME2)
assert len(new_workflow) == 1
assert new_workflow[0]["className"] == "rrr"
assert new_workflow[0]["tool"] == 3
new_project = sa.get_project_metadata(new_project["name"],
include_contributors=True)
assert len(new_project["contributors"]) == 1
assert new_project["contributors"][0]["user_id"] == users[1]
assert new_project["contributors"][0][
"user_role"] == sa.user_role_str_to_int("QA")