def test_single_image_upload_bytesio(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME_BYTES,
return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME_BYTES, "test", "Vector")
with open("./tests/sample_project_vector/example_image_1.jpg", "rb") as f:
img = io.BytesIO(f.read())
try:
sa.upload_image_to_project(project,
img,
annotation_status="InProgress")
except sa.SABaseException as e:
assert e.message == "Image name img_name should be set if img is not Pathlike"
else:
assert False
sa.upload_image_to_project(project,
img,
image_name="rr.jpg",
annotation_status="InProgress")
images = sa.search_images(project)
assert len(images) == 1
image = images[0]
assert sa.annotation_status_int_to_str(
sa.get_image_metadata(project,
image)["annotation_status"]) == "InProgress"
assert image == "rr.jpg"
def test_fuse_image_create_pixel(tmpdir):
tmpdir = Path(tmpdir)
projects = sa.search_projects(PROJECT_NAME_PIXEL, return_metadata=True)
for project in projects:
sa.delete_project(project)
project = sa.create_project(PROJECT_NAME_PIXEL, "test", "Pixel")
sa.upload_image_to_project(
project,
"./tests/sample_project_pixel/example_image_1.jpg",
annotation_status="QualityCheck"
)
sa.create_annotation_classes_from_classes_json(
project, "./tests/sample_project_pixel/classes/classes.json"
)
sa.upload_image_annotations(
PROJECT_NAME_PIXEL, "example_image_1.jpg",
"./tests/sample_project_pixel/example_image_1.jpg___pixel.json",
"./tests/sample_project_pixel/example_image_1.jpg___save.png"
)
export = sa.prepare_export(project, include_fuse=True)
(tmpdir / "export").mkdir()
sa.download_export(project, export, (tmpdir / "export"))
# sa.create_fuse_image(
# "./tests/sample_project_vector/example_image_1.jpg",
# "./tests/sample_project_vector/classes/classes.json", "Vector"
# )
paths = sa.download_image(
project,
"example_image_1.jpg",
tmpdir,
include_annotations=True,
include_fuse=True
)
print(paths, paths[2])
im1 = Image.open(tmpdir / "export" / "example_image_1.jpg___fuse.png")
im1_array = np.array(im1)
im2 = Image.open(paths[2][0])
im2_array = np.array(im2)
assert im1_array.shape == im2_array.shape
assert im1_array.dtype == im2_array.dtype
assert np.array_equal(im1_array, im2_array)
def test_image_move(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME_MOVE,
return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME_MOVE, "test", "Vector")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_1.jpg",
annotation_status="InProgress")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_2.jpg",
annotation_status="InProgress")
images = sa.search_images(project)
assert len(images) == 2
image = images[0]
try:
sa.move_image(project, image, project)
except sa.SABaseException as e:
assert e.message == "Cannot move image if source_project == destination_project."
else:
assert False
projects_found = sa.search_projects(PROJECT_NAME_MOVE + "dif",
return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
dest_project = sa.create_project(PROJECT_NAME_MOVE + "dif", "test",
"Vector")
sa.move_image(project, image, dest_project)
di = sa.search_images(dest_project, image)
assert len(di) == 1
assert di[0] == image
si = sa.search_images(project, image)
assert len(si) == 0
si = sa.search_images(project)
assert len(si) == 1
def test_image_copy_mult(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME_CPY_MULT,
return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME_CPY_MULT, "test", "Vector")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_1.jpg",
annotation_status="InProgress")
sa.create_annotation_classes_from_classes_json(
project, "./tests/sample_project_vector/classes/classes.json")
sa.upload_image_annotations(
project, "example_image_1.jpg",
"./tests/sample_project_vector/example_image_1.jpg___objects.json")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_2.jpg",
annotation_status="InProgress")
sa.pin_image(project, "example_image_1.jpg")
images = sa.search_images(project)
assert len(images) == 2
image = images[0]
for _ in range(3):
sa.copy_image(project,
image,
project,
include_annotations=True,
copy_annotation_status=True,
copy_pin=True)
assert len(sa.search_images(project)) == 5
images = sa.search_images(project)
for i in range(3):
assert f"example_image_1_({i+1}).jpg" in images
anns = sa.get_image_annotations(project, f"example_image_1_({i+1}).jpg")
assert anns["annotation_json"] is not None
metadata = sa.get_image_metadata(project, f"example_image_1_({i+1}).jpg")
assert metadata["is_pinned"] == 1
def test_image_copy(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME_CPY, return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME_CPY, "test", "Vector")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_1.jpg",
annotation_status="InProgress")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_2.jpg",
annotation_status="InProgress")
images = sa.search_images(project)
assert len(images) == 2
image = images[0]
sa.copy_image(project, image, project)
images = sa.search_images(project)
assert len(images) == 3
image = "example_image_1_(1).jpg"
assert len(sa.search_images(project, image)) == 1
sa.copy_image(project, image, project)
image = "example_image_1_(2).jpg"
assert len(sa.search_images(project, image)) == 1
projects_found = sa.search_projects(PROJECT_NAME_CPY + "dif",
return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
dest_project = sa.create_project(PROJECT_NAME_CPY + "dif", "test",
"Vector")
sa.copy_image(project, image, dest_project)
di = sa.search_images(dest_project, image)
assert len(di) == 1
assert di[0] == image
def test_single_image_upload_s3(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME_S3, return_metadata=True)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME_S3, "test", "Vector")
sa.upload_image_to_project(project,
"sample_project_vector/example_image_1.jpg",
annotation_status="InProgress",
from_s3_bucket="superannotate-python-sdk-test")
images = sa.search_images(project)
assert len(images) == 1
image = images[0]
assert sa.get_image_metadata(project,
image)["annotation_status"] == "InProgress"
def test_single_image_upload(tmpdir):
tmpdir = Path(tmpdir)
projects_found = sa.search_projects(PROJECT_NAME, return_metadata=True)
print(projects_found)
for pr in projects_found:
sa.delete_project(pr)
project = sa.create_project(PROJECT_NAME, "test", "Vector")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_1.jpg",
annotation_status="InProgress")
images = sa.search_images(project)
assert len(images) == 1
image = images[0]
assert sa.get_image_metadata(project,
image)["annotation_status"] == "InProgress"
assert image == "example_image_1.jpg"
def test_fuse_image_create_vector(tmpdir):
tmpdir = Path(tmpdir)
projects = sa.search_projects(PROJECT_NAME_VECTOR, return_metadata=True)
for project in projects:
sa.delete_project(project)
project = sa.create_project(PROJECT_NAME_VECTOR, "test", "Vector")
sa.upload_image_to_project(
project,
"./tests/sample_project_vector/example_image_1.jpg",
annotation_status="QualityCheck")
sa.create_annotation_classes_from_classes_json(
project, "./tests/sample_project_vector/classes/classes.json")
sa.add_annotation_bbox_to_image(project, "example_image_1.jpg",
[20, 20, 40, 40], "Human")
sa.add_annotation_polygon_to_image(project, "example_image_1.jpg",
[60, 60, 100, 100, 80, 100],
"Personal vehicle")
sa.add_annotation_polyline_to_image(project, "example_image_1.jpg",
[200, 200, 300, 200, 350, 300],
"Personal vehicle")
sa.add_annotation_point_to_image(project, "example_image_1.jpg",
[400, 400], "Personal vehicle")
sa.add_annotation_ellipse_to_image(project, "example_image_1.jpg",
[600, 600, 50, 100, 20],
"Personal vehicle")
sa.add_annotation_template_to_image(
project, "example_image_1.jpg",
[600, 300, 600, 350, 550, 250, 650, 250, 550, 400, 650, 400],
[1, 2, 3, 1, 4, 1, 5, 2, 6, 2], "Human")
sa.add_annotation_cuboid_to_image(project, "example_image_1.jpg",
[60, 300, 200, 350, 120, 325, 250, 500],
"Human")
export = sa.prepare_export(project, include_fuse=True)
(tmpdir / "export").mkdir()
sa.download_export(project, export, (tmpdir / "export"))
# sa.create_fuse_image(
# "./tests/sample_project_vector/example_image_1.jpg",
# "./tests/sample_project_vector/classes/classes.json", "Vector"
# )
paths = sa.download_image(project,
"example_image_1.jpg",
tmpdir,
include_annotations=True,
include_fuse=True,
include_overlay=True)
im1 = Image.open(tmpdir / "export" / "example_image_1.jpg___fuse.png")
im1_array = np.array(im1)
im2 = Image.open(paths[2][0])
im2_array = np.array(im2)
assert im1_array.shape == im2_array.shape
assert im1_array.dtype == im2_array.dtype