def test_measurement_duplicate_not_allowed(self):
measurement = MeasurementAnnotationFactory()
try:
measuremt_duplicate = MeasurementAnnotationFactory(
image=measurement.image,
grader=measurement.grader,
created=measurement.created,
start_voxel=measurement.start_voxel,
end_voxel=measurement.end_voxel,
)
pytest.fail(
"No integrity error when submitting duplicate measurement annotation"
)
except IntegrityError:
pass
def generate_annotation_set(retina_grader=False):
grader = UserFactory()
if retina_grader:
add_to_graders_group([grader])
measurement = MeasurementAnnotationFactory(grader=grader)
boolean = BooleanClassificationAnnotationFactory(grader=grader)
integer = IntegerClassificationAnnotationFactory(grader=grader)
polygon = PolygonAnnotationSetFactory(grader=grader)
coordinatelist = CoordinateListAnnotationFactory(grader=grader)
landmark = LandmarkAnnotationSetFactory(grader=grader)
etdrs = ETDRSGridAnnotationFactory(grader=grader)
# Create child models for polygon annotation set
SinglePolygonAnnotationFactory.create_batch(10, annotation_set=polygon)
# Create child models for landmark annotation set (3 per image)
for i in range(5):
image = ImageFactory()
SingleLandmarkAnnotationFactory(annotation_set=landmark, image=image)
return AnnotationSet(
grader=grader,
measurement=measurement,
boolean=boolean,
polygon=polygon,
coordinatelist=coordinatelist,
landmark=landmark,
etdrs=etdrs,
integer=integer,
)
def create_load_data(data_type, ds, grader):
if data_type == "Registration":
model = LandmarkAnnotationSetFactory(grader=grader)
SingleLandmarkAnnotationFactory(
annotation_set=model, image=ds["image_cf"]
),
if ds["archive"].name == "Australia":
# Australia does not allow obs images so create a new cf image for Australia test
img = ImageFactory(study=ds["study"])
SingleLandmarkAnnotationFactory(annotation_set=model, image=img)
else:
SingleLandmarkAnnotationFactory(
annotation_set=model, image=ds["image_obs"]
),
elif data_type == "ETDRS":
model = ETDRSGridAnnotationFactory(grader=grader, image=ds["image_cf"])
elif data_type == "GA" or data_type == "kappa":
model_macualar = PolygonAnnotationSetFactory(
grader=grader, image=ds["image_cf"], name="macular"
)
SinglePolygonAnnotationFactory(annotation_set=model_macualar)
SinglePolygonAnnotationFactory(annotation_set=model_macualar)
SinglePolygonAnnotationFactory(annotation_set=model_macualar)
model_peripapillary = PolygonAnnotationSetFactory(
grader=grader, image=ds["image_cf"], name="peripapillary"
)
SinglePolygonAnnotationFactory(annotation_set=model_peripapillary)
SinglePolygonAnnotationFactory(annotation_set=model_peripapillary)
SinglePolygonAnnotationFactory(annotation_set=model_peripapillary)
model = [model_macualar, model_peripapillary]
elif data_type == "Measure":
model = [
MeasurementAnnotationFactory(grader=grader, image=ds["image_cf"]),
MeasurementAnnotationFactory(grader=grader, image=ds["image_cf"]),
MeasurementAnnotationFactory(grader=grader, image=ds["image_cf"]),
]
elif data_type == "Fovea":
model = BooleanClassificationAnnotationFactory(
grader=grader, image=ds["image_cf"], name="fovea_affected"
)
return model
def generate_annotation_set(retina_grader=False, image=False):
grader = UserFactory()
if retina_grader:
add_to_graders_group([grader])
create_options = {"grader": grader}
if image:
create_options_with_image = {"image": image, **create_options}
else:
create_options_with_image = create_options
measurement = MeasurementAnnotationFactory(**create_options_with_image)
boolean = BooleanClassificationAnnotationFactory(
**create_options_with_image
)
integer = IntegerClassificationAnnotationFactory(
**create_options_with_image
)
polygon = PolygonAnnotationSetFactory(**create_options_with_image)
coordinatelist = CoordinateListAnnotationFactory(
**create_options_with_image
)
etdrs = ETDRSGridAnnotationFactory(**create_options_with_image)
landmark = LandmarkAnnotationSetFactory(**create_options)
# Create child models for polygon annotation set
SinglePolygonAnnotationFactory.create_batch(10, annotation_set=polygon)
# Create child models for landmark annotation set (3 per image)
single_landmarks = []
for i in range(5):
if i > 0 or not image:
image = ImageFactory()
single_landmarks.append(
SingleLandmarkAnnotationFactory(
annotation_set=landmark, image=image
)
)
return AnnotationSet(
grader=grader,
measurement=measurement,
boolean=boolean,
polygon=polygon,
coordinatelist=coordinatelist,
landmark=landmark,
singlelandmarks=single_landmarks,
etdrs=etdrs,
integer=integer,
)