def test_label_entity_serialization(self):
"""
This test serializes LabelEntity and checks serialized representation.
Then it compares deserialized LabelEntity with original one.
"""
cur_date = now()
red = randint(0, 255) # nosec
green = randint(0, 255) # nosec
blue = randint(0, 255) # nosec
alpha = randint(0, 255) # nosec
label = LabelEntity(
name="my_label",
domain=Domain.DETECTION,
color=Color(red, green, blue, alpha),
hotkey="ctrl+1",
creation_date=cur_date,
is_empty=False,
id=ID("0000213"),
)
serialized = LabelMapper.forward(label)
assert serialized == {
"_id": "0000213",
"name": "my_label",
"color": {"red": red, "green": green, "blue": blue, "alpha": alpha},
"hotkey": "ctrl+1",
"domain": "DETECTION",
"creation_date": DatetimeMapper.forward(cur_date),
"is_empty": False,
}
deserialized = LabelMapper.backward(serialized)
assert label == deserialized
def convert_to_annotation(
self,
predictions: np.ndarray,
metadata: Optional[Dict] = None) -> AnnotationSceneEntity:
"""
Converts a set of predictions into an AnnotationScene object
:param predictions: Prediction with shape [num_predictions, 6] or
[num_predictions, 7]
Supported detection formats are
* [label, confidence, x1, y1, x2, y2]
* [_, label, confidence, x1, y1, x2, y2]
.. note::
`label` can be any integer that can be mapped to `self.labels`
`confidence` should be a value between 0 and 1
`x1`, `x2`, `y1` and `y2` are expected to be normalized.
:returns AnnotationScene: AnnotationScene Object containing the boxes
obtained from the prediction
"""
annotations = self.__convert_to_annotations(predictions)
# media_identifier = ImageIdentifier(image_id=ID())
annotation_scene = AnnotationSceneEntity(
id=ID(),
kind=AnnotationSceneKind.PREDICTION,
editor="ote",
creation_date=now(),
annotations=annotations,
)
return annotation_scene
def __init__(
self,
points: List[Point],
labels: Optional[List[ScoredLabel]] = None,
modification_date: Optional[datetime.datetime] = None,
):
labels = [] if labels is None else labels
modification_date = now(
) if modification_date is None else modification_date
super().__init__(
type=ShapeType.POLYGON,
labels=labels,
modification_date=modification_date,
)
if len(points) == 0:
raise ValueError("Cannot create polygon with no points")
self.points = points
self.min_x = min(points, key=attrgetter("x")).x
self.max_x = max(points, key=attrgetter("x")).x
self.min_y = min(points, key=attrgetter("y")).y
self.max_y = max(points, key=attrgetter("y")).y
is_valid = True
for (x, y) in [(self.min_x, self.min_y), (self.max_x, self.max_y)]:
is_valid = is_valid and self._validate_coordinates(x, y)
if not is_valid:
points_str = "; ".join(str(p) for p in self.points)
warnings.warn(
f"{type(self).__name__} coordinates are invalid : {points_str}",
UserWarning,
)
def __init__(
self,
x1: float,
y1: float,
x2: float,
y2: float,
labels: Optional[List[ScoredLabel]] = None,
modification_date: Optional[datetime.datetime] = None,
):
labels = [] if labels is None else labels
modification_date = now(
) if modification_date is None else modification_date
super().__init__(
type=ShapeType.ELLIPSE,
labels=labels,
modification_date=modification_date,
)
for (x, y) in [(x1, y1), (x2, y2)]:
self._validate_coordinates(x, y)
self.x1 = x1
self.y1 = y1
self.x2 = x2
self.y2 = y2
if self.width <= 0 or self.height <= 0:
raise ValueError(
f"Invalid Ellipse with coordinates: x1={self.x1}, y1={self.y1}, x2={self.x2},"
f" y2={self.y2}")
def __init__(
self,
x1: float,
y1: float,
x2: float,
y2: float,
labels: Optional[List[ScoredLabel]] = None,
modification_date: Optional[datetime.datetime] = None,
):
labels = [] if labels is None else labels
modification_date = now(
) if modification_date is None else modification_date
super().__init__(
type=ShapeType.RECTANGLE,
labels=labels,
modification_date=modification_date,
)
is_valid = True
for (x, y) in [(x1, y1), (x2, y2)]:
is_valid = is_valid and self._validate_coordinates(x, y)
if not is_valid:
warnings.warn(
f"{type(self).__name__} coordinates are invalid : x1={x1}, y1={y1}, x2={x2}, y2={y2}",
UserWarning,
)
self.x1 = x1
self.y1 = y1
self.x2 = x2
self.y2 = y2
if self.width <= 0 or self.height <= 0:
raise ValueError(
f"Invalid rectangle with coordinates: x1={self.x1}, y1={self.y1}, "
f"x2={self.x2}, y2={self.y2}")
def backward(instance: Union[None, str]) -> datetime.datetime:
"""Deserializes datetime from str or create new one if it is None"""
if isinstance(instance, str):
modification_date = datetime.datetime.strptime(
instance, "%Y-%m-%dT%H:%M:%S.%f"
)
return modification_date.replace(tzinfo=datetime.timezone.utc)
return now()
def test_serialization_deserialization(self):
"""
This test serializes datetime, deserializes serialized datetime and compares with original one.
"""
original_time = now()
serialized_time = DatetimeMapper.forward(original_time)
assert serialized_time == original_time.strftime(
"%Y-%m-%dT%H:%M:%S.%f")
deserialized_time = DatetimeMapper.backward(serialized_time)
assert original_time == deserialized_time
def __init__(
self,
annotations: List[Annotation],
kind: AnnotationSceneKind,
editor: str = "",
creation_date: Optional[datetime.datetime] = None,
id: Optional[ID] = None,
):
self.__annotations = annotations
self.__kind = kind
self.__editor = editor
self.__creation_date = now(
) if creation_date is None else creation_date
self.__id = ID() if id is None else id
def __init__(
self,
model: ModelEntity,
ground_truth_dataset: DatasetEntity,
prediction_dataset: DatasetEntity,
purpose: ResultsetPurpose = ResultsetPurpose.EVALUATION,
performance: Optional[Performance] = None,
creation_date: Optional[datetime.datetime] = None,
id: Optional[ID] = None,
):
id = ID() if id is None else id
performance = NullPerformance() if performance is None else performance
creation_date = now() if creation_date is None else creation_date
self.__id = id
self.__model = model
self.__prediction_dataset = prediction_dataset
self.__ground_truth_dataset = ground_truth_dataset
self.__performance = performance
self.__purpose = purpose
self.__creation_date = creation_date
def __init__(
self,
name: str,
domain: Domain,
color: Optional[Color] = None,
hotkey: str = "",
creation_date: Optional[datetime.datetime] = None,
is_empty: bool = False,
id: Optional[ID] = None,
):
id = ID() if id is None else id
color = Color.random() if color is None else color
creation_date = now() if creation_date is None else creation_date
if not hotkey and is_empty:
hotkey = "ctrl+0"
self._name = name
self._color = color
self._hotkey = hotkey
self._domain = domain
self._is_empty = is_empty
self._creation_date = creation_date
self._id = id
class TestLabelEntity:
creation_date = now()
label_car_params = {
"name": "car",
"domain": Domain.DETECTION,
"color": Color(255, 0, 0),
"hotkey": "ctrl+1",
"creation_date": creation_date,
"is_empty": False,
"id": ID(123456789),
}
label_person_params = {
"name": "person",
"domain": Domain.DETECTION,
"color": Color(255, 17, 17),
"hotkey": "ctrl+2",
"creation_date": creation_date,
"is_empty": False,
"id": ID(987654321),
}
car = LabelEntity(**label_car_params) # type: ignore
empty = LabelEntity(name="empty",
domain=Domain.SEGMENTATION,
is_empty=True)
person = LabelEntity(**label_person_params) # type: ignore
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_label_entity(self):
"""
<b>Description:</b>
Check the LabelEntity can correctly return the value
<b>Input data:</b>
Dummy data
<b>Expected results:</b>
Test passes if incoming data is processed correctly
<b>Steps</b>
1. Use already created dummy data
2. Check the processing of default values
3. Check the processing of changed values
"""
assert self.car == LabelEntity(**self.label_car_params)
assert self.car != Domain
assert self.car != self.person
for attr in [
"name",
"domain",
"color",
"hotkey",
"creation_date",
"is_empty",
"id",
]:
assert getattr(self.car, attr) == self.label_car_params[attr]
label_car_new_name = "electric car"
label_car_new_domain = Domain.CLASSIFICATION
label_car_new_color = Color(0, 255, 0)
label_car_new_hotkey = "ctrl+2"
label_car_new_id = ID(987654321)
setattr(self.car, "name", label_car_new_name)
setattr(self.car, "domain", label_car_new_domain)
setattr(self.car, "color", label_car_new_color)
setattr(self.car, "hotkey", label_car_new_hotkey)
setattr(self.car, "id", label_car_new_id)
assert self.car.name == label_car_new_name
assert self.car.domain == label_car_new_domain
assert self.car.color == label_car_new_color
assert self.car.hotkey == label_car_new_hotkey
assert self.car.id == label_car_new_id
test_label_entity_repr = [
f"{self.car.id}",
f"name={self.car.name}",
f"hotkey={self.car.hotkey}",
f"domain={self.car.domain}",
f"color={self.car.color}",
]
for i in test_label_entity_repr:
assert i in self.car.__repr__()
assert hash(self.car) == hash(str(self.car))
assert self.car.__lt__(Domain) is False
assert self.car.__gt__(Domain) is False
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_empty_label_entity(self):
"""
<b>Description:</b>
Check the LabelEntity can correctly return the value for empty label
<b>Input data:</b>
Dummy data
<b>Expected results:</b>
Test passes if incoming data is processed correctly
<b>Steps</b>
1. Use already created dummy data
2. Check the processing of default values
"""
assert self.empty.hotkey == "ctrl+0"
assert self.empty.id == ID()
assert type(self.empty.color) == Color
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_label_comparison(self):
"""
<b>Description:</b>
Check the LabelEntity __lt__, __gt__ methods with changed id
<b>Input data:</b>
Dummy data
<b>Expected results:</b>
Test passes if incoming data is processed correctly
<b>Steps</b>
1. Use already created dummy data
2. Check the processing of changed id
"""
self.empty.id = ID(999999999)
assert self.empty > self.car
assert self.car < self.empty
class TestModelEntity:
creation_date = now()
def generate_random_image(self):
with generate_random_single_image() as path:
image = Image(file_path=path)
return DatasetItemEntity(
media=image, annotation_scene=NullAnnotationSceneEntity())
def dataset(self):
return DatasetEntity(items=[self.generate_random_image()])
def configuration(self):
parameters = ConfigurableParameters(header="Test header")
label_schema = LabelSchemaEntity()
return ModelConfiguration(configurable_parameters=parameters,
label_schema=label_schema)
def other_configuration(self):
parameters = ConfigurableParameters(header="Other test header")
label_schema = LabelSchemaEntity()
return ModelConfiguration(configurable_parameters=parameters,
label_schema=label_schema)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_model_entity_default_values(self):
"""
<b>Description:</b>
Check that ModelEntity correctly returns the default values
<b>Expected results:</b>
Test passes if ModelEntity correctly returns the default values
<b>Steps</b>
1. Check default values in the ModelEntity
"""
model_entity = ModelEntity(train_dataset=self.dataset(),
configuration=self.configuration())
assert model_entity.id == ID()
assert type(model_entity.configuration) == ModelConfiguration
assert type(model_entity.creation_date) == datetime
assert type(model_entity.train_dataset) == DatasetEntity
assert model_entity.version == 1
assert model_entity.model_status == ModelStatus.SUCCESS
assert model_entity.model_format == ModelFormat.OPENVINO
assert model_entity.precision == [ModelPrecision.FP32]
assert model_entity.target_device == TargetDevice.CPU
assert model_entity.optimization_type == ModelOptimizationType.NONE
assert model_entity.performance == NullPerformance()
for default_val_none in [
"previous_trained_revision",
"previous_revision",
"target_device_type",
]:
assert getattr(model_entity, default_val_none) is None
for default_val_0_0 in ["training_duration", "model_size_reduction"]:
assert getattr(model_entity, default_val_0_0) == 0.0
for default_val_empty_list in ["tags", "optimization_methods"]:
assert getattr(model_entity, default_val_empty_list) == []
for default_val_empty_dict in [
"model_adapters",
"optimization_objectives",
"performance_improvement",
]:
assert getattr(model_entity, default_val_empty_dict) == {}
for default_val_zero in ["latency", "fps_throughput"]:
assert getattr(model_entity, default_val_zero) == 0
assert model_entity.is_optimized() is False
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_model_entity_sets_values(self):
"""
<b>Description:</b>
Check that ModelEntity correctly returns the set values
<b>Expected results:</b>
Test passes if ModelEntity correctly returns the set values
<b>Steps</b>
1. Check set values in the ModelEntity
"""
def __get_path_to_file(filename: str):
"""
Return the path to the file named 'filename', which lives in the tests/entities directory
"""
return str(Path(__file__).parent / Path(filename))
car = LabelEntity(name="car", domain=Domain.DETECTION)
labels_list = [car]
dummy_template = __get_path_to_file("./dummy_template.yaml")
model_template = parse_model_template(dummy_template)
hyper_parameters = model_template.hyper_parameters.data
params = ote_config_helper.create(hyper_parameters)
labels_schema = LabelSchemaEntity.from_labels(labels_list)
environment = TaskEnvironment(
model=None,
hyper_parameters=params,
label_schema=labels_schema,
model_template=model_template,
)
item = self.generate_random_image()
dataset = DatasetEntity(items=[item])
score_metric = ScoreMetric(name="Model accuracy", value=0.5)
model_entity = ModelEntity(train_dataset=self.dataset(),
configuration=self.configuration())
set_params = {
"configuration": environment.get_model_configuration(),
"train_dataset": dataset,
"id": ID(1234567890),
"creation_date": self.creation_date,
"previous_trained_revision": 5,
"previous_revision": 2,
"version": 2,
"tags": ["tree", "person"],
"model_status": ModelStatus.TRAINED_NO_STATS,
"model_format": ModelFormat.BASE_FRAMEWORK,
"performance": Performance(score_metric),
"training_duration": 5.8,
"precision": [ModelPrecision.INT8],
"latency": 328,
"fps_throughput": 20,
"target_device": TargetDevice.GPU,
"target_device_type": "notebook",
"optimization_methods": [OptimizationMethod.QUANTIZATION],
"optimization_type": ModelOptimizationType.MO,
"optimization_objectives": {
"param": "Test param"
},
"performance_improvement": {"speed", 0.5},
"model_size_reduction": 1.0,
}
for key, value in set_params.items():
setattr(model_entity, key, value)
assert getattr(model_entity, key) == value
assert model_entity.is_optimized() is True
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_model_entity_model_adapters(self):
"""
<b>Description:</b>
Check that ModelEntity correctly returns the adapters
<b>Expected results:</b>
Test passes if ModelEntity correctly returns the adapters
<b>Steps</b>
1. Create a ModelEntity with adapters
2. Change data source for an adapter
3. Remove an adapter
"""
data_source_0 = b"{0: binaryrepo://localhost/repo/data_source/0}"
data_source_1 = b"binaryrepo://localhost/repo/data_source/1"
data_source_2 = b"binaryrepo://localhost/repo/data_source/2"
data_source_3 = b"binaryrepo://localhost/repo/data_source/3"
temp_dir = tempfile.TemporaryDirectory()
temp_file = os.path.join(temp_dir.name, "data_source_0")
with open(temp_file, "wb") as tmp:
tmp.write(data_source_0)
model_adapters = {
"0": ModelAdapter(data_source=data_source_0),
"1": ModelAdapter(data_source=data_source_1),
"2": ModelAdapter(data_source=data_source_2),
}
model_entity = ModelEntity(
train_dataset=self.dataset(),
configuration=self.configuration(),
model_adapters=model_adapters,
)
assert model_entity.weight_paths == {}
# Adapter with key 0 not from file
assert model_entity.model_adapters["0"].from_file_storage is False
model_entity.set_data("0", temp_file)
for adapter in model_entity.model_adapters:
if adapter == "0":
# Adapter with key 0 from file
assert model_entity.model_adapters[
adapter].from_file_storage is True
else:
assert model_entity.model_adapters[
adapter].from_file_storage is False
assert model_entity.get_data("1") == data_source_1
model_entity.set_data("2", data_source_1)
assert model_entity.get_data("2") == data_source_1
assert len(model_entity.model_adapters) == 3
model_entity.set_data("3", data_source_3)
assert model_entity.get_data("3") == data_source_3
assert len(model_entity.model_adapters) == 4
model_entity.delete_data("3")
assert len(model_entity.model_adapters) == 3
# Attempt to retrieve a missing and deleted key
with pytest.raises(KeyError):
model_entity.get_data("5")
with pytest.raises(KeyError):
model_entity.get_data("3")
# The presence of outdated code in ModelEntity "model_adapter.data_source.binary_url"
with pytest.raises(AttributeError):
assert model_entity.weight_paths == {"0": temp_file}
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_model_entity__eq__(self):
"""
<b>Description:</b>
Check that ModelEntity __eq__ method
<b>Expected results:</b>
Test passes if ModelEntity equal ModelEntity and not equal another type
"""
dataset = self.dataset()
other_model_entity = ModelEntity(train_dataset=dataset,
configuration=self.configuration())
model_entity = ModelEntity(train_dataset=dataset,
configuration=self.configuration())
third_model_entity = ModelEntity(
train_dataset=self.dataset(),
configuration=self.other_configuration())
assert model_entity.__eq__("") is False
assert model_entity == other_model_entity
assert model_entity != third_model_entity
def test_flat_label_schema_serialization(self):
"""
This test serializes flat LabelSchema and checks serialized representation.
Then it compares deserialized LabelSchema with original one.
"""
cur_date = now()
names = ["cat", "dog", "mouse"]
colors = [
Color(
randint(0, 255), # nosec
randint(0, 255), # nosec
randint(0, 255), # nosec
randint(0, 255), # nosec
) # nosec # noqa
for _ in range(3)
]
labels = [
LabelEntity(
name=name,
domain=Domain.CLASSIFICATION,
creation_date=cur_date,
id=ID(i),
color=colors[i],
)
for i, name in enumerate(names)
]
label_shema = LabelSchemaEntity.from_labels(labels)
serialized = LabelSchemaMapper.forward(label_shema)
assert serialized == {
"label_tree": {"type": "tree", "directed": True, "nodes": [], "edges": []},
"exclusivity_graph": {
"type": "graph",
"directed": False,
"nodes": [],
"edges": [],
},
"label_groups": [
{
"_id": label_shema.get_groups()[0].id,
"name": "from_label_list",
"label_ids": ["0", "1", "2"],
"relation_type": "EXCLUSIVE",
}
],
"all_labels": {
"0": {
"_id": "0",
"name": "cat",
"color": ColorMapper.forward(colors[0]),
"hotkey": "",
"domain": "CLASSIFICATION",
"creation_date": DatetimeMapper.forward(cur_date),
"is_empty": False,
},
"1": {
"_id": "1",
"name": "dog",
"color": ColorMapper.forward(colors[1]),
"hotkey": "",
"domain": "CLASSIFICATION",
"creation_date": DatetimeMapper.forward(cur_date),
"is_empty": False,
},
"2": {
"_id": "2",
"name": "mouse",
"color": ColorMapper.forward(colors[2]),
"hotkey": "",
"domain": "CLASSIFICATION",
"creation_date": DatetimeMapper.forward(cur_date),
"is_empty": False,
},
},
}
deserialized = LabelSchemaMapper.backward(serialized)
assert label_shema == deserialized
class TestAnnotationSceneEntity:
creation_date = now()
labels: List[ScoredLabel] = []
rectangle = Rectangle(x1=0.5, x2=1.0, y1=0.0, y2=0.5)
annotation = Annotation(shape=rectangle, labels=labels)
point1 = Point(0.3, 0.1)
point2 = Point(0.8, 0.3)
point3 = Point(0.6, 0.2)
points = [point1, point2, point3]
polygon = Polygon(points=points)
annotation2 = Annotation(shape=polygon, labels=labels)
annotations = [annotation, annotation2]
annotation_scene_entity = AnnotationSceneEntity(
annotations=annotations, kind=AnnotationSceneKind.ANNOTATION)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_default_value(self):
"""
<b>Description:</b>
Check that AnnotationSceneEntity default values
<b>Input data:</b>
AnnotationSceneEntity class
<b>Expected results:</b>
Test passes if the AnnotationSceneEntity return correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Check default values
"""
annotation_scene_entity = self.annotation_scene_entity
assert annotation_scene_entity.id == ID()
assert annotation_scene_entity.kind == AnnotationSceneKind.ANNOTATION
assert annotation_scene_entity.editor_name == ""
assert type(annotation_scene_entity.creation_date) == datetime.datetime
assert "Annotation(shape=Rectangle" in str(
annotation_scene_entity.annotations)
assert "Annotation(shape=Polygon" in str(
annotation_scene_entity.annotations)
assert annotation_scene_entity.shapes == [self.rectangle, self.polygon]
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_setters(self):
"""
<b>Description:</b>
Check that AnnotationSceneEntity can correctly return modified property value
<b>Input data:</b>
Annotation class
<b>Expected results:</b>
Test passes if the AnnotationSceneEntity return correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Set another values
3. Check changed values
"""
annotation_scene_entity = self.annotation_scene_entity
creation_date = self.creation_date
annotation_scene_entity.id = ID(123456789)
annotation_scene_entity.kind = AnnotationSceneKind.PREDICTION
annotation_scene_entity.editor_name = "editor"
annotation_scene_entity.creation_date = creation_date
annotation_scene_entity.annotations = self.annotation
assert annotation_scene_entity.id == ID(123456789)
assert annotation_scene_entity.kind == AnnotationSceneKind.PREDICTION
assert annotation_scene_entity.editor_name == "editor"
assert annotation_scene_entity.creation_date == creation_date
assert annotation_scene_entity.annotations == self.annotation
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_magic_methods(self):
"""
<b>Description:</b>
Check Annotation __repr__ method
<b>Input data:</b>
Initialized instance of AnnotationSceneEntity
<b>Expected results:</b>
Test passes if AnnotationSceneEntity magic method returns correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Check returning value of magic method
"""
annotation_scene_entity = self.annotation_scene_entity
annotation_scene_entity_repr = [
f"{annotation_scene_entity.__class__.__name__}("
f"annotations={annotation_scene_entity.annotations}, "
f"kind={annotation_scene_entity.kind}, "
f"editor={annotation_scene_entity.editor_name}, "
f"creation_date={annotation_scene_entity.creation_date}, "
f"id={annotation_scene_entity.id})"
]
for i in annotation_scene_entity_repr:
assert i in repr(annotation_scene_entity)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_contains_any(self):
"""
<b>Description:</b>
Check Annotation contains_any method
<b>Input data:</b>
Initialized instance of AnnotationSceneEntity
<b>Expected results:</b>
Test passes if AnnotationSceneEntity contains_any method returns correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Check returning value of contains_any method
"""
annotation_scene_entity = self.annotation_scene_entity
annotation_scene_entity.annotations = self.annotations
car = LabelEntity(name="car", domain=Domain.DETECTION, is_empty=True)
person = LabelEntity(name="person", domain=Domain.DETECTION)
tree = LabelEntity(name="tree", domain=Domain.DETECTION)
car_label = ScoredLabel(car)
person_label = ScoredLabel(person)
tree_label = ScoredLabel(tree)
labels = [car_label]
labels2 = [car_label, person_label]
annotation = Annotation(shape=self.rectangle, labels=labels2)
annotations = [annotation]
annotation_scene_entity2 = AnnotationSceneEntity(
annotations=annotations, kind=AnnotationSceneKind.ANNOTATION)
assert annotation_scene_entity.contains_any(labels=labels) is False
assert annotation_scene_entity2.contains_any(labels=labels2) is True
assert annotation_scene_entity2.contains_any(
labels=[tree_label]) is False
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_append_annotation(self):
"""
<b>Description:</b>
Check Annotation append_annotation method
<b>Input data:</b>
Initialized instance of AnnotationSceneEntity
<b>Expected results:</b>
Test passes if AnnotationSceneEntity append_annotation method returns correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Check returning value of append_annotation method
"""
annotation_scene_entity = self.annotation_scene_entity
tree = LabelEntity(name="tree", domain=Domain.DETECTION)
tree_label = ScoredLabel(tree)
labels = [tree_label]
annotation = Annotation(shape=self.rectangle, labels=labels)
assert len(annotation_scene_entity.annotations) == 2
annotation_scene_entity.append_annotation(annotation)
assert len(annotation_scene_entity.annotations) == 3
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_append_annotations(self):
"""
<b>Description:</b>
Check Annotation append_annotations method
<b>Input data:</b>
Initialized instance of AnnotationSceneEntity
<b>Expected results:</b>
Test passes if AnnotationSceneEntity append_annotations method returns correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Check returning value of append_annotations method
"""
annotation_scene_entity = self.annotation_scene_entity
annotation_scene_entity.append_annotations(self.annotations)
assert len(annotation_scene_entity.annotations) == 6
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_get_labels(self):
"""
<b>Description:</b>
Check Annotation get_labels method
<b>Input data:</b>
Initialized instance of AnnotationSceneEntity
<b>Expected results:</b>
Test passes if AnnotationSceneEntity get_labels method returns correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Check returning value of get_labels method
"""
annotation_scene_entity = self.annotation_scene_entity
assert len(annotation_scene_entity.get_labels()) == 1
assert "name=tree" in str(annotation_scene_entity.get_labels())
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_annotation_scene_entity_get_label_ids(self):
"""
<b>Description:</b>
Check Annotation get_label_ids method
<b>Input data:</b>
Initialized instance of AnnotationSceneEntity
<b>Expected results:</b>
Test passes if AnnotationSceneEntity get_label_ids method returns correct values
<b>Steps</b>
1. Create AnnotationSceneEntity instances
2. Check returning value of get_label_ids method
"""
annotation_scene_entity = self.annotation_scene_entity
assert annotation_scene_entity.get_label_ids() == {ID()}
bus = LabelEntity(id=ID(123456789),
name="bus",
domain=Domain.DETECTION)
bus_label = ScoredLabel(bus)
labels = [bus_label]
annotation = Annotation(shape=self.rectangle, labels=labels)
annotation_scene_entity.append_annotation(annotation)
assert annotation_scene_entity.get_label_ids() == {ID(), ID(123456789)}
def __init__(
self,
train_dataset: "DatasetEntity",
configuration: ModelConfiguration,
*,
creation_date: Optional[datetime.datetime] = None,
performance: Optional[Performance] = None,
previous_trained_revision: Optional["ModelEntity"] = None,
previous_revision: Optional["ModelEntity"] = None,
version: int = 1,
tags: Optional[List[str]] = None,
model_status: ModelStatus = ModelStatus.SUCCESS,
model_format: ModelFormat = ModelFormat.OPENVINO,
training_duration: float = 0.0,
model_adapters: Optional[Dict[str, ModelAdapter]] = None,
exportable_code_adapter: Optional[ExportableCodeAdapter] = None,
precision: Optional[List[ModelPrecision]] = None,
latency: int = 0,
fps_throughput: int = 0,
target_device: TargetDevice = TargetDevice.CPU,
target_device_type: Optional[str] = None,
optimization_type: ModelOptimizationType = ModelOptimizationType.NONE,
optimization_methods: List[OptimizationMethod] = None,
optimization_objectives: Dict[str, str] = None,
performance_improvement: Dict[str, float] = None,
model_size_reduction: float = 0.0,
_id: Optional[ID] = None,
):
_id = ID() if _id is None else _id
performance = NullPerformance() if performance is None else performance
creation_date = now() if creation_date is None else creation_date
optimization_methods = (
[] if optimization_methods is None else optimization_methods
)
optimization_objectives = (
{} if optimization_objectives is None else optimization_objectives
)
performance_improvement = (
{} if performance_improvement is None else performance_improvement
)
tags = [] if tags is None else tags
precision = [ModelPrecision.FP32] if precision is None else precision
if model_adapters is None:
model_adapters = {}
self.__id = _id
self.__creation_date = creation_date
self.__train_dataset = train_dataset
self.__previous_trained_revision = previous_trained_revision
self.__previous_revision = previous_revision
self.__version = version
self.__tags = tags
self.__model_status = model_status
self.__model_format = model_format
self.__performance = performance
self.__training_duration = training_duration
self.__configuration = configuration
self.__model_adapters = model_adapters
self.__exportable_code_adapter = exportable_code_adapter
self.model_adapters_to_delete: List[ModelAdapter] = []
self.__precision = precision
self.__latency = latency
self.__fps_throughput = fps_throughput
self.__target_device = target_device
self.__target_device_type = target_device_type
self.__optimization_type = optimization_type
self.__optimization_methods = optimization_methods
self.__optimization_objectives = optimization_objectives
self.__performance_improvement = performance_improvement
self.__model_size_reduction = model_size_reduction
class TestRectangle:
modification_date = now()
@staticmethod
def rectangle_labels() -> list:
rectangle_label = LabelEntity(
name="Rectangle label",
domain=Domain.DETECTION,
color=Color(red=100, green=50, blue=200),
id=ID("rectangle_label_1"),
)
other_rectangle_label = LabelEntity(
name="Other rectangle label",
domain=Domain.SEGMENTATION,
color=Color(red=200, green=80, blue=100),
id=ID("rectangle_label_2"),
)
return [
ScoredLabel(label=rectangle_label),
ScoredLabel(label=other_rectangle_label),
]
@staticmethod
def horizontal_rectangle_params() -> dict:
return {"x1": 0.1, "y1": 0.0, "x2": 0.4, "y2": 0.2}
def horizontal_rectangle(self) -> Rectangle:
return Rectangle(**self.horizontal_rectangle_params())
def vertical_rectangle_params(self) -> dict:
return {
"x1": 0.1,
"y1": 0.1,
"x2": 0.3,
"y2": 0.4,
"labels": self.rectangle_labels(),
"modification_date": datetime(
year=2020, month=1, day=1, hour=9, minute=30, second=15, microsecond=2
),
}
def vertical_rectangle(self) -> Rectangle:
return Rectangle(**self.vertical_rectangle_params())
@staticmethod
def square_params() -> dict:
return {"x1": 0.1, "y1": 0.1, "x2": 0.3, "y2": 0.3}
def square(self) -> Rectangle:
return Rectangle(**self.square_params())
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_required_parameters(self):
"""
<b>Description:</b>
Check Rectangle class instance required parameters
<b>Input data:</b>
Rectangle class initiation parameters
<b>Expected results:</b>
Test passes if Rectangle instance has expected attributes specified during required parameters initiation
<b>Steps</b>
1. Compare x1, y1, x2, y2 and type Rectangle instance parameters with expected values
"""
rectangle = self.horizontal_rectangle()
assert rectangle.x1 == 0.1
assert rectangle.y1 == 0.0
assert rectangle.x2 == 0.4
assert rectangle.y2 == 0.2
assert rectangle.type == ShapeType.RECTANGLE
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_optional_parameters(self):
"""
<b>Description:</b>
Check Rectangle optional parameters
<b>Input data:</b>
Instance of Rectangle class
<b>Expected results:</b>
Test passes if Rectangle instance has expected labels and modification attributes specified during Rectangle
class object initiation with optional parameters
<b>Steps</b>
1. Compare default label Rectangle instance attribute with expected value
2. Check type of default modification_date Rectangle instance attribute
3. Compare specified label Rectangle instance attribute with expected value
4. Compare specified modification_date Rectangle instance attribute with expected value
"""
# Checking default values of optional parameters
default_params_rectangle = self.horizontal_rectangle()
assert default_params_rectangle._labels == []
assert isinstance(default_params_rectangle.modification_date, datetime)
# check for specified values of optional parameters
specified_params_rectangle = self.vertical_rectangle()
assert specified_params_rectangle._labels == self.rectangle_labels()
assert specified_params_rectangle.modification_date == datetime(
year=2020, month=1, day=1, hour=9, minute=30, second=15, microsecond=2
)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_coordinates_validation(self):
"""
<b>Description:</b>
Check Rectangle coordinates
<b>Input data:</b>
Rectangle class initiation parameters
<b>Expected results:</b>
Test passes if Rectangle correctly checks coordinates during initiation of Rectangle object
<b>Steps</b>
1. Check Rectangle coordinates with correct width and height
2. Check Rectangle coordinates with incorrect width: (x2 - x1) <= 0
3. Check Rectangle coordinates with incorrect height: (y2 - y1) <= 0
4. Check Rectangle coordinates with all coordinates equal 0
"""
# checks for correct width and height
self.horizontal_rectangle()
self.vertical_rectangle()
self.square()
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
Rectangle(x1=0.2, y1=0.1, x2=1.4, y2=1.5)
Rectangle(x1=0.2, y1=0.1, x2=0.4, y2=0.5)
# checks for incorrect coordinates
width_less_than_zero_params = {"x1": 0.4, "y1": 0.0, "x2": 0.1, "y2": 0.2}
width_equal_zero_params = {"x1": 0.1, "y1": 0.0, "x2": 0.1, "y2": 0.2}
height_less_than_zero_params = {"x1": 0.1, "y1": 0.4, "x2": 0.3, "y2": 0.1}
height_params_equal_zero_params = {"x1": 0.1, "y1": 0.4, "x2": 0.3, "y2": 0.4}
zero_rectangle_params = {"x1": 0.0, "x2": 0.0, "y1": 0.0, "y2": 0.0}
for incorrect_coordinates in [
width_less_than_zero_params,
width_equal_zero_params,
height_less_than_zero_params,
height_params_equal_zero_params,
zero_rectangle_params,
]:
with pytest.raises(ValueError):
Rectangle(**incorrect_coordinates)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_repr(self):
"""
<b>Description:</b>
Check Rectangle __repr__ method
<b>Input data:</b>
Instance of Rectangle class
<b>Expected results:</b>
Test passes if __repr__ method prints expected message for Rectangle class instance
<b>Steps</b>
1. Check message printed by __repr__ method
"""
rectangle = self.horizontal_rectangle()
assert (
repr(rectangle)
== "Rectangle(x=0.1, y=0.0, width=0.30000000000000004, height=0.2)"
)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_eq(self):
"""
<b>Description:</b>
Check Rectangle __eq__ method
<b>Input data:</b>
Instances of Rectangle class
<b>Expected results:</b>
Test passes if __eq__ method returns expected bool value
<b>Steps</b>
1. Check __eq__ method for instances of Rectangle class with equal parameters
2. Check __eq__ method for different instances of Rectangle class
3. Check __eq__ method for instances of different classes
4. Check __eq__ method for instances of Rectangle class with unequal labels attribute
5. Check __eq__ method for instances of Rectangle class with unequal x1, y1, x2, y2 and
modification_date attributes
"""
rectangle = self.vertical_rectangle()
# Check for instances with equal parameters
equal_rectangle = self.vertical_rectangle()
assert rectangle == equal_rectangle
# Check for different instances of Rectangle class
assert rectangle != self.horizontal_rectangle()
# Check for different types branch
assert rectangle != str
# Check for unequal labels parameters. Expected that different labels are not affecting equality
unequal_label = LabelEntity(
name="Unequal label", domain=Domain.SEGMENTATION, id=ID("unequal_label_1")
)
unequal_scored_label = ScoredLabel(label=unequal_label)
equal_rectangle._labels.append(unequal_scored_label)
assert rectangle == equal_rectangle
# Check for instances with unequal parameters combinations
# Generating all possible scenarios of parameter values submission
keys_list = ["x1", "y1", "x2", "y2", "modification_date"]
parameter_combinations = []
for i in range(1, len(keys_list) + 1):
parameter_combinations.append(list(itertools.combinations(keys_list, i)))
# In each of scenario creating a copy of equal Rectangle parameters and replacing to values from prepared
# dictionary
unequal_values_dict = {
"x1": 0.09,
"y1": 0.09,
"x2": 0.29,
"y2": 0.39,
"modification_date": datetime(
year=2019, month=2, day=3, hour=7, minute=15, second=10, microsecond=1
),
}
for scenario in parameter_combinations:
for rectangle_parameters in scenario:
unequal_rectangle_params_dict = dict(self.vertical_rectangle_params())
for key in rectangle_parameters:
unequal_rectangle_params_dict[key] = unequal_values_dict.get(key)
unequal_rectangle = Rectangle(**unequal_rectangle_params_dict)
assert rectangle != unequal_rectangle, (
"Failed to check that Rectangle instances with different "
f"{rectangle_parameters} are unequal"
)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_hash(self):
"""
<b>Description:</b>
Check Rectangle __hash__ method
<b>Input data:</b>
Instance of Rectangle class
<b>Expected results:</b>
Test passes if __hash__ method returns expected value
<b>Steps</b>
1. Check value returned by __hash__ method
"""
rectangle = self.horizontal_rectangle()
assert hash(rectangle) == hash(str(rectangle))
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_clip_to_visible_region(self):
"""
<b>Description:</b>
Check Rectangle clip_to_visible_region method
<b>Input data:</b>
Rectangle class initiation parameters
<b>Expected results:</b>
Test passes if clip_to_visible_region method return correct value
<b>Steps</b>
1. Check values returned by clip_to_visible_region method for 0<x1<x2, 0<y1<y2, x1<x2<1, y1<y2<1
2. Check values returned by clip_to_visible_region method for x1<0, y1<0, x2>1, y2>1
3. Check values returned by clip_to_visible_region method for x1=0, y1=0, x2=1, y2=1
4. Check ValueError exception raised if x1<0 and x1<x2<0: clipped Rectangle width will be equal 0
5. Check ValueError exception raised if 1<x1<x2 and x2>1: clipped Rectangle width will be equal 0
6. Check ValueError exception raised if y1<0 and y1<y2<0: clipped Rectangle height will be equal 0
7. Check ValueError exception raised if 1<y1<y2 and y2>1: clipped Rectangle height will be equal 0
"""
positive_scenarios = [
{
"input_params": {
"x1": 0.3,
"y1": 0.2,
"x2": 0.6,
"y2": 0.4,
"labels": self.rectangle_labels(),
},
"params_expected": {"x1": 0.3, "y1": 0.2, "x2": 0.6, "y2": 0.4},
},
{
"input_params": {
"x1": -0.2,
"y1": -0.3,
"x2": 1.6,
"y2": 1.4,
"labels": self.rectangle_labels(),
},
"params_expected": {"x1": 0.0, "y1": 0.0, "x2": 1.0, "y2": 1.0},
},
{
"input_params": {
"x1": 0.0,
"y1": 0.0,
"x2": 1.0,
"y2": 1.0,
"labels": self.rectangle_labels(),
},
"params_expected": {"x1": 0.0, "y1": 0.0, "x2": 1.0, "y2": 1.0},
},
]
for scenario in positive_scenarios:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
rectangle_actual = Rectangle(**scenario.get("input_params"))
rectangle_expected = Rectangle(**scenario.get("params_expected"))
rectangle_actual.modification_date = self.modification_date
rectangle_expected.modification_date = self.modification_date
assert rectangle_actual.clip_to_visible_region() == rectangle_expected
negative_scenarios = [
{"x1": -0.4, "y1": 0.2, "x2": -0.2, "y2": 0.4},
{"x1": 1.2, "y1": 0.2, "x2": 1.6, "y2": 0.4},
{"x1": 0.4, "y1": -0.4, "x2": 0.6, "y2": -0.2},
{"x1": 1.2, "y1": 1.2, "x2": 1.6, "y2": 1.4},
]
for scenario in negative_scenarios:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
rectangle_actual = Rectangle(**scenario)
with pytest.raises(ValueError):
rectangle_actual.clip_to_visible_region()
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_normalize_wrt_roi_shape(self):
"""
<b>Description:</b>
Check Rectangle normalize_wrt_roi_shape method
<b>Input data:</b>
Instance of Rectangle class
<b>Expected results:</b>
Test passes if normalize_wrt_roi_shape method returns expected instance of Rectangle class
<b>Steps</b>
1. Check values returned by normalized Rectangle instance
2. Check raise ValueError exception when roi parameter has unexpected type
"""
# Positive scenario
rectangle = self.horizontal_rectangle()
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
roi_shape = Rectangle(x1=0.0, y1=0.0, x2=2.1, y2=2.2)
normalized = rectangle.normalize_wrt_roi_shape(roi_shape)
assert normalized.x1 == 0.1
assert normalized.y1 == 0.0
assert normalized.x2 == 0.4
assert normalized.y2 == 0.2
assert normalized.modification_date == rectangle.modification_date
# Negative scenario
with pytest.raises(ValueError):
rectangle.normalize_wrt_roi_shape(str)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_denormalize_wrt_roi_shape(self):
"""
<b>Description:</b>
Check Rectangle denormalize_wrt_roi_shape method
<b>Input data:</b>
Instance of Rectangle class
<b>Expected results:</b>
Test passes if denormalize_wrt_roi_shape method return expected instance of Rectangle class
<b>Steps</b>
1. Check values returned by denormalized Rectangle instance
2. Check raise ValueError exception when roi parameter has unexpected type
"""
# Positive scenario
rectangle = self.horizontal_rectangle()
roi_shape = Rectangle(x1=0.2, y1=0.2, x2=0.4, y2=0.4)
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
denormalized = rectangle.denormalize_wrt_roi_shape(roi_shape)
assert denormalized.x1 == -0.5
assert denormalized.y1 == -1.0
assert denormalized.x2 == 1.0
assert denormalized.y2 == 0.0
assert denormalized.modification_date == rectangle.modification_date
# Negative scenario
with pytest.raises(ValueError):
rectangle.denormalize_wrt_roi_shape(str)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_as_shapely_polygon(self):
"""
<b>Description:</b>
Check Rectangle _as_shapely_polygon method
<b>Input data:</b>
Instance of Rectangle class
<b>Expected results:</b>
Test passes if _as_shapely_polygon method returns expected instance of Polygon class
<b>Steps</b>
1. Check Polygon instance returned by _as_shapely_polygon method
"""
rectangle = self.horizontal_rectangle()
shapely_polygon = rectangle._as_shapely_polygon()
assert shapely_polygon.__class__ == Polygon
assert shapely_polygon.bounds == (0.1, 0.0, 0.4, 0.2)
assert shapely_polygon.area == 0.06000000000000001
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_generate_full_box(self):
"""
<b>Description:</b>
Check Rectangle generate_full_box method
<b>Input data:</b>
Labels specified for full_box instance of Rectangle class
<b>Expected results:</b>
Test passes if generate_full_box method returns instance of Rectangle class with coordinates
(x1=0.0, y1=0.0, x2=1.0, y2=1.0)
<b>Steps</b>
1. Check generate_full_box method for Rectangle instance with no labels specified
2. Check generate_full_box method for Rectangle instance with labels specified
"""
detection_label = ScoredLabel(
LabelEntity(name="detection", domain=Domain.DETECTION)
)
for label_actual, label_expected in [
(None, []),
([detection_label], [detection_label]),
]:
full_box = Rectangle.generate_full_box(label_actual)
assert full_box.type == ShapeType.RECTANGLE
assert full_box.x1 == full_box.y1 == 0.0
assert full_box.x2 == full_box.y2 == 1.0
assert full_box._labels == label_expected
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_is_full_box(self):
"""
<b>Description:</b>
Check Rectangle is_full_box method
<b>Input data:</b>
Rectangle class initiation parameters
<b>Expected results:</b>
Test passes if is_full_box method return expected bool value
<b>Steps</b>
1. Check positive scenario for is_full_box method: x1=y1=0, x2=y2=1
2. Check negative scenarios for is_full_box method
"""
full_box_rectangle_params = {"x1": 0.0, "y1": 0.0, "x2": 1.0, "y2": 1.0}
# Positive scenario for Rectangle instance
full_box_rectangle = Rectangle(**full_box_rectangle_params)
assert Rectangle.is_full_box(full_box_rectangle)
# Negative scenarios for Rectangle instance
# Generating all scenarios when Rectangle object not a full_box
keys_list = ["x1", "y1", "x2", "y2"]
parameter_combinations = []
for i in range(1, len(keys_list) + 1):
parameter_combinations.append(list(itertools.combinations(keys_list, i)))
# In each of scenario creating a copy of full_Box rectangle parameters and replacing to values from prepared
# dictionary
not_full_box_values_dict = {"x1": 0.01, "y1": 0.01, "x2": 0.9, "y2": 0.9}
for combination in parameter_combinations:
for scenario in combination:
not_full_box_params = dict(full_box_rectangle_params)
for key in scenario:
not_full_box_params[key] = not_full_box_values_dict.get(key)
not_full_box_rectangle = Rectangle(**not_full_box_params)
assert not Rectangle.is_full_box(not_full_box_rectangle), (
f"Expected False returned by is_full_box method for rectangle with parameters "
f"{not_full_box_params}"
)
# Negative scenario for not Rectangle class instance
assert not Rectangle.is_full_box(str)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_crop_numpy_array(self):
"""
<b>Description:</b>
Check Rectangle crop_numpy_array method
<b>Input data:</b>
Rectangle class initiation parameters
<b>Expected results:</b>
Test passes if crop_numpy_array method return expected cropped array
<b>Steps</b>
1. Check crop_numpy_array method for Rectangle with parameters less than 0
2. Check crop_numpy_array method for Rectangle with parameters range from 0 to 1
3. Check crop_numpy_array method for Rectangle with parameters more than 1
"""
image_height = image_width = 128
numpy_image_array = np.random.uniform(
low=0.0, high=255.0, size=(image_height, image_width, 3)
)
scenarios = [
{
"input_params": {"x1": -0.2, "x2": -0.1, "y1": -0.3, "y2": -0.2},
"cropped_expected": {"x1": 0, "y1": 0, "x2": 0, "y2": 0},
},
{
"input_params": {"x1": 0.2, "x2": 0.3, "y1": 0.4, "y2": 0.8},
"cropped_expected": {"x1": 26, "y1": 51, "x2": 38, "y2": 102},
},
{
"input_params": {"x1": 1.1, "x2": 1.3, "y1": 1.1, "y2": 1.5},
"cropped_expected": {"x1": 141, "y1": 141, "x2": 166, "y2": 192},
},
]
for rectangle_parameters in scenarios:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
rectangle = Rectangle(**rectangle_parameters.get("input_params"))
expected_output = rectangle_parameters.get("cropped_expected")
actual_cropped_image_array = rectangle.crop_numpy_array(numpy_image_array)
expected_image_array = numpy_image_array[
expected_output.get("y1") : expected_output.get("y2"),
expected_output.get("x1") : expected_output.get("x2"),
::,
]
assert actual_cropped_image_array.shape[2] == 3
try:
assert (expected_image_array == actual_cropped_image_array).all()
except AttributeError:
raise AssertionError("Unequal expected and cropped image arrays")
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_width(self):
"""
<b>Description:</b>
Check Rectangle width method
<b>Input data:</b>
Instances of Rectangle class
<b>Expected results:</b>
Test passes if width method returns expected value of Rectangle width
<b>Steps</b>
1. Check width method for Rectangle instances
"""
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
negative_x1_rectangle = Rectangle(x1=-0.3, y1=0.2, x2=0.7, y2=0.5)
for rectangle, expected_width in [
(self.horizontal_rectangle(), 0.30000000000000004),
(self.vertical_rectangle(), 0.19999999999999998),
(self.square(), 0.19999999999999998),
(negative_x1_rectangle, 1.0),
]:
assert rectangle.width == expected_width
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_height(self):
"""
<b>Description:</b>
Check Rectangle height method
<b>Input data:</b>
Instances of Rectangle class
<b>Expected results:</b>
Test passes if height method returns expected value of Rectangle height
<b>Steps</b>
1. Check height method for Rectangle instances
"""
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Rectangle coordinates")
negative_y1_rectangle = Rectangle(x1=0.3, y1=-0.4, x2=0.7, y2=0.5)
for rectangle, expected_height in [
(self.horizontal_rectangle(), 0.2),
(self.vertical_rectangle(), 0.30000000000000004),
(self.square(), 0.19999999999999998),
(negative_y1_rectangle, 0.9),
]:
assert rectangle.height == expected_height
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_diagonal(self):
"""
<b>Description:</b>
Check Rectangle diagonal method
<b>Input data:</b>
Instances of Rectangle class
<b>Expected results:</b>
Test passes if diagonal method returns expected value of Rectangle diagonal
<b>Steps</b>
1. Check diagonal method for Rectangle instance
"""
for rectangle, expected_diagonal in [
(self.horizontal_rectangle(), 0.360555127546399),
(self.vertical_rectangle(), 0.3605551275463989),
(self.square(), 0.282842712474619),
]:
assert rectangle.diagonal == expected_diagonal
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_rectangle_get_area(self):
"""
<b>Description:</b>
Check Rectangle get_area method
<b>Input data:</b>
Instances of Rectangle class
<b>Expected results:</b>
Test passes if get_area method returns expected value of Rectangle diagonal
<b>Steps</b>
1. Check get_area method for Rectangle instance
"""
for rectangle, expected_area in [
(self.horizontal_rectangle(), 0.06000000000000001),
(self.vertical_rectangle(), 0.060000000000000005),
(self.square(), 0.039999999999999994),
]:
assert rectangle.get_area() == expected_area
class TestResultset:
creation_date = now()
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_resultset_purpose(self):
"""
<b>Description:</b>
Check the ResultsetPurpose can correctly return the value
<b>Input data:</b>
Denotes, stages
<b>Expected results:</b>
Test passes if the results match
"""
denotes = ["EVALUATION", "TEST", "PREEVALUATION"]
stages = ["Validation", "Test", "Pre-validation"]
resultset_purpose = ResultsetPurpose
assert len(resultset_purpose) == 3
for i in ResultsetPurpose:
resultset_purpose = ResultsetPurpose(i)
assert repr(resultset_purpose) == denotes[i.value]
assert str(resultset_purpose) == stages[i.value]
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_resultset_entity(self):
"""
<b>Description:</b>
Check the ResultSetEntity can correctly return the value
<b>Input data:</b>
Mock data
<b>Expected results:</b>
Test passes if incoming data is processed correctly
<b>Steps</b>
1. Create dummy data
2. Check the processing of default values
3. Check the processing of changed values
"""
test_data = {
"model": None,
"ground_truth_dataset": None,
"prediction_dataset": None,
"purpose": None,
"performance": None,
"creation_date": None,
"id": None,
}
result_set = ResultSetEntity(**test_data)
for name, value in test_data.items():
set_attr_name = f"test_{name}"
if name in [
"model",
"ground_truth_dataset",
"prediction_dataset",
"purpose",
]:
assert getattr(result_set, name) == value
setattr(result_set, name, set_attr_name)
assert getattr(result_set, name) == set_attr_name
assert result_set.performance == NullPerformance()
assert type(result_set.creation_date) == datetime.datetime
assert result_set.id == ID()
assert result_set.has_score_metric() is False
result_set.performance = "test_performance"
assert result_set.performance != NullPerformance()
assert result_set.has_score_metric() is True
creation_date = self.creation_date
result_set.creation_date = creation_date
assert result_set.creation_date == creation_date
set_attr_id = ID(123456789)
result_set.id = set_attr_id
assert result_set.id == set_attr_id
test_result_set_repr = [
f"model={result_set.model}",
f"ground_truth_dataset={result_set.ground_truth_dataset}",
f"prediction_dataset={result_set.prediction_dataset}",
f"purpose={result_set.purpose}",
f"performance={result_set.performance}",
f"creation_date={result_set.creation_date}",
f"id={result_set.id}",
]
for i in test_result_set_repr:
assert i in repr(result_set)
def __init__(self, name: str, date: Optional[datetime.datetime] = None):
self.name = name
if date is None:
date = now()
self.date = date
class TestEllipse:
modification_date = now()
def ellipse_params(self):
ellipse_params = {
"x1": 0.5,
"x2": 1.0,
"y1": 0.0,
"y2": 0.5,
"modification_date": self.modification_date,
}
return ellipse_params
def ellipse(self):
return Ellipse(**self.ellipse_params())
def width_gt_height_ellipse_params(self):
width_gt_height_ellipse_params = {
"x1": 0.5,
"x2": 0.8,
"y1": 0.1,
"y2": 0.3,
}
return width_gt_height_ellipse_params
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_ellipse(self):
"""
<b>Description:</b>
Check ellipse parameters
<b>Input data:</b>
Coordinates
<b>Expected results:</b>
Test passes if Ellipse correctly calculates parameters and returns default values
<b>Steps</b>
1. Check ellipse params
2. Check ellipse default values
3. Check ellipse with incorrect coordinates
"""
ellipse = self.ellipse()
modification_date = self.modification_date
assert ellipse.width == 0.5
assert ellipse.height == 0.5
assert ellipse.x_center == 0.75
assert ellipse.y_center == 0.25
assert ellipse.minor_axis == 0.25
assert ellipse.major_axis == 0.25
assert ellipse._labels == []
assert ellipse.modification_date == modification_date
incorrect_ellipse_params = {
"x1": 0,
"x2": 0,
"y1": 0,
"y2": 0,
}
with pytest.raises(ValueError):
Ellipse(**incorrect_ellipse_params)
width_lt_height_ellipse_params = {
"x1": 0.4,
"x2": 0.5,
"y1": 0.3,
"y2": 0.4,
}
width_lt_height_ellipse = Ellipse(**width_lt_height_ellipse_params)
assert width_lt_height_ellipse.height > width_lt_height_ellipse.width
assert width_lt_height_ellipse.major_axis == width_lt_height_ellipse.height / 2
assert width_lt_height_ellipse.width == 0.09999999999999998
assert width_lt_height_ellipse.height == 0.10000000000000003
assert width_lt_height_ellipse.x_center == 0.45
assert width_lt_height_ellipse.y_center == 0.35
assert width_lt_height_ellipse.minor_axis == 0.04999999999999999
assert width_lt_height_ellipse.major_axis == 0.05000000000000002
width_gt_height_ellipse = Ellipse(
**self.width_gt_height_ellipse_params())
assert width_gt_height_ellipse.height < width_gt_height_ellipse.width
assert width_gt_height_ellipse.minor_axis == width_gt_height_ellipse.height / 2
assert width_gt_height_ellipse.width == 0.30000000000000004
assert width_gt_height_ellipse.height == 0.19999999999999998
assert width_gt_height_ellipse.x_center == 0.65
assert width_gt_height_ellipse.y_center == 0.2
assert width_gt_height_ellipse.minor_axis == 0.09999999999999999
assert width_gt_height_ellipse.major_axis == 0.15000000000000002
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_ellipse_magic_methods(self):
"""
<b>Description:</b>
Check Ellipse __repr__, __eq__, __hash__ methods
<b>Input data:</b>
Initialized instance of Ellipse
<b>Expected results:</b>
Test passes if Ellipse magic methods returns correct values
<b>Steps</b>
1. Initialize Ellipse instance
2. Check returning value of magic methods
"""
x1 = self.ellipse_params()["x1"]
x2 = self.ellipse_params()["x2"]
y1 = self.ellipse_params()["y1"]
y2 = self.ellipse_params()["y2"]
ellipse = self.ellipse()
assert repr(ellipse) == f"Ellipse(x1={x1}, y1={y1}, x2={x2}, y2={y2})"
other_ellipse_params = {
"x1": 0.5,
"x2": 1.0,
"y1": 0.0,
"y2": 0.5,
"modification_date": self.modification_date,
}
third_ellipse_params = {
"x1": 0.3,
"y1": 0.5,
"x2": 0.4,
"y2": 0.6,
"modification_date": self.modification_date,
}
other_ellipse = Ellipse(**other_ellipse_params)
third_ellipse = Ellipse(**third_ellipse_params)
assert ellipse == other_ellipse
assert ellipse != third_ellipse
assert ellipse != str
assert hash(ellipse) == hash(str(ellipse))
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_ellipse_normalize_wrt_roi_shape(self):
"""
<b>Description:</b>
Check Ellipse normalize_wrt_roi_shape methods
<b>Input data:</b>
Initialized instance of Ellipse
Initialized instance of Rectangle
<b>Expected results:</b>
Test passes if Ellipse normalize_wrt_roi_shape returns correct values
<b>Steps</b>
1. Initialize Ellipse instance
2. Check returning value
"""
ellipse = self.ellipse()
roi = Rectangle(x1=0.0, x2=0.5, y1=0.0, y2=0.5)
normalized = ellipse.normalize_wrt_roi_shape(roi)
assert normalized.x1 == 0.25
assert normalized.y1 == 0.0
assert normalized.x2 == 0.5
assert normalized.y2 == 0.25
with pytest.raises(ValueError):
ellipse.normalize_wrt_roi_shape("123")
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_ellipse_denormalize_wrt_roi_shape(self):
"""
<b>Description:</b>
Check Ellipse denormalize_wrt_roi_shape methods
<b>Input data:</b>
Initialized instance of Ellipse
Initialized instance of Rectangle
<b>Expected results:</b>
Test passes if Ellipse denormalize_wrt_roi_shape returns correct values
<b>Steps</b>
1. Initialize Ellipse instance
2. Check returning value
"""
ellipse = self.ellipse()
roi = Rectangle(x1=0.5, x2=1.0, y1=0.0, y2=1.0)
denormalized = ellipse.denormalize_wrt_roi_shape(roi)
assert denormalized.x1 == 0.0
assert denormalized.y1 == 0.0
assert denormalized.x2 == 1.0
assert denormalized.y2 == 0.5
with pytest.raises(ValueError):
ellipse.denormalize_wrt_roi_shape("123")
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_ellipse_get_evenly_distributed_ellipse_coordinates(self):
"""
<b>Description:</b>
Check Ellipse get_evenly_distributed_ellipse_coordinates methods
<b>Input data:</b>
Initialized instance of Ellipse
<b>Expected results:</b>
Test passes if Ellipse get_evenly_distributed_ellipse_coordinates returns correct values
<b>Steps</b>
1. Initialize Ellipse instance
2. Check returning value
"""
ellipse = self.ellipse()
number_of_coordinates = 3
coordinates_ellipse_line = ellipse.get_evenly_distributed_ellipse_coordinates(
number_of_coordinates)
assert len(coordinates_ellipse_line) == 3
assert coordinates_ellipse_line[0] == (1.0, 0.25)
assert coordinates_ellipse_line[1] == (0.625, 0.4665063509461097)
assert coordinates_ellipse_line[2] == (0.6249999999999999,
0.033493649053890406)
width_gt_height_ellipse = Ellipse(
**self.width_gt_height_ellipse_params())
coordinates_ellipse_line = (
width_gt_height_ellipse.get_evenly_distributed_ellipse_coordinates(
number_of_coordinates))
assert width_gt_height_ellipse.height < width_gt_height_ellipse.width
assert len(coordinates_ellipse_line) == 3
assert coordinates_ellipse_line[0] == (0.65, 0.3)
assert coordinates_ellipse_line[1] == (0.7666223198362645,
0.1371094972158116)
assert coordinates_ellipse_line[2] == (0.5333776801637811,
0.13710949721577403)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_ellipse__as_shapely_polygon(self):
"""
<b>Description:</b>
Check Ellipse _as_shapely_polygon methods
<b>Input data:</b>
Initialized instance of Ellipse
<b>Expected results:</b>
Test passes if Ellipse _as_shapely_polygon returns correct values
<b>Steps</b>
1. Initialize Ellipse instance
2. Check returning value
"""
ellipse = self.ellipse()
shapely_polygon = ellipse._as_shapely_polygon()
assert shapely_polygon.__class__ == Polygon
assert shapely_polygon.area == 0.1958331774442254
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_ellipse_get_area(self):
"""
<b>Description:</b>
Check Ellipse get_area methods
<b>Input data:</b>
Initialized instance of Ellipse
<b>Expected results:</b>
Test passes if Ellipse get_area returns correct values
<b>Steps</b>
1. Initialize Ellipse instance
2. Check returning value
"""
ellipse = self.ellipse()
area = ellipse.get_area()
assert area == 0.19634954084936207
class TestPolygon:
modification_date = now()
def points(self):
point1 = Point(0.5, 0.0)
point2 = Point(0.75, 0.2)
point3 = Point(0.6, 0.1)
return [point1, point2, point3]
def other_points(self):
point1 = Point(0.3, 0.1)
point2 = Point(0.8, 0.3)
point3 = Point(0.6, 0.2)
return [point1, point2, point3]
def polygon(self):
return Polygon(self.points(), modification_date=self.modification_date)
def other_polygon(self):
return Polygon(self.other_points(),
modification_date=self.modification_date)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_polygon(self):
"""
<b>Description:</b>
Check Polygon parameters
<b>Input data:</b>
Points
<b>Expected results:</b>
Test passes if Polygon correctly calculates parameters and returns default values
<b>Steps</b>
1. Check Polygon params
2. Check Polygon default values
3. Check Polygon with empty points
"""
polygon = self.polygon()
modification_date = self.modification_date
assert len(polygon.points) == 3
assert polygon.modification_date == modification_date
assert polygon.points == self.points()
empty_points_list = []
with pytest.raises(ValueError):
Polygon(empty_points_list)
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_polygon_magic_methods(self):
"""
<b>Description:</b>
Check Polygon __repr__, __eq__, __hash__ methods
<b>Input data:</b>
Initialized instance of Polygon
<b>Expected results:</b>
Test passes if Polygon magic methods returns correct values
<b>Steps</b>
1. Initialize Polygon instance
2. Check returning value of magic methods
"""
polygon = self.polygon()
points_len = len(self.points())
min_x = min(self.points(), key=attrgetter("x")).x
max_x = max(self.points(), key=attrgetter("x")).x
min_y = min(self.points(), key=attrgetter("y")).y
max_y = max(self.points(), key=attrgetter("y")).y
assert f"Polygon(len(points)={points_len}, min_x={min_x}" in repr(
polygon)
assert f", max_x={max_x}, min_y={min_y}, max_y={max_y})" in repr(
polygon)
other_polygon = self.polygon()
thirs_polygon = self.other_polygon()
assert polygon == other_polygon
assert polygon != thirs_polygon
assert polygon != str
assert hash(polygon) == hash(str(polygon))
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_polygon_normalize_wrt_roi_shape(self):
"""
<b>Description:</b>
Check Polygon normalize_wrt_roi_shape methods
<b>Input data:</b>
Initialized instance of Polygon
Initialized instance of Rectangle
<b>Expected results:</b>
Test passes if Polygon normalize_wrt_roi_shape returns correct values
<b>Steps</b>
1. Initialize Polygon instance
2. Check returning value
"""
polygon = self.polygon()
roi = Rectangle(x1=0.0, x2=0.5, y1=0.0, y2=0.5)
normalized = polygon.normalize_wrt_roi_shape(roi)
assert len(normalized.points) == 3
assert normalized.min_x == 0.25
assert normalized.max_x == 0.375
assert normalized.min_y == 0.0
assert normalized.max_y == 0.1
with pytest.raises(ValueError):
polygon.normalize_wrt_roi_shape("123")
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_polygon_denormalize_wrt_roi_shape(self):
"""
<b>Description:</b>
Check Polygon denormalize_wrt_roi_shape methods
<b>Input data:</b>
Initialized instance of Polygon
Initialized instance of Rectangle
<b>Expected results:</b>
Test passes if Polygon denormalize_wrt_roi_shape returns correct values
<b>Steps</b>
1. Initialize Polygon instance
2. Check returning value
"""
polygon = self.polygon()
roi = Rectangle(x1=0.5, x2=1.0, y1=0.0, y2=1.0)
denormalized = polygon.denormalize_wrt_roi_shape(roi)
assert len(denormalized.points) == 3
assert denormalized.min_x == 0.0
assert denormalized.max_x == 0.5
assert denormalized.min_y == 0.0
assert denormalized.max_y == 0.2
with pytest.raises(ValueError):
polygon.denormalize_wrt_roi_shape("123")
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_polygon__as_shapely_polygon(self):
"""
<b>Description:</b>
Check Polygon _as_shapely_polygon methods
<b>Input data:</b>
Initialized instance of Polygon
<b>Expected results:</b>
Test passes if Polygon _as_shapely_polygon returns correct values
<b>Steps</b>
1. Initialize Polygon instance
2. Check returning value
"""
polygon = self.polygon()
polygon2 = self.other_polygon()
shapely_polygon = polygon._as_shapely_polygon()
shapely_polygon2 = polygon2._as_shapely_polygon()
assert shapely_polygon.area == 0.0025000000000000022
assert str(
shapely_polygon) == "POLYGON ((0.5 0, 0.75 0.2, 0.6 0.1, 0.5 0))"
assert shapely_polygon != shapely_polygon2
@pytest.mark.priority_medium
@pytest.mark.component
@pytest.mark.reqids(Requirements.REQ_1)
def test_polygon_get_area(self):
"""
<b>Description:</b>
Check Polygon get_area method
<b>Input data:</b>
Initialized instance of Polygon
<b>Expected results:</b>
Test passes if Polygon get_area returns correct values
<b>Steps</b>
1. Initialize Polygon instance
2. Check returning value
"""
polygon = self.polygon()
polygon2 = self.other_polygon()
area = polygon.get_area()
area2 = polygon2.get_area()
assert area == 0.0025000000000000022
assert area != area2
