pixano_inference.models.tracking

Tracking model base class and I/O types.

TrackingBoxPrompt(**data)

Bases: BaseModel

Box prompt for a tracking keyframe.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )

TrackingInput(**data)

Bases: BaseModel

Input for video mask generation / tracking.

Attributes:

Name	Type	Description
video	list[str | Path | bytes] | str | Path | bytes	Path to the video, list of frame paths, or base64 encoded video/frames.
points	list[list[list[int]]] | None	Legacy point prompts [num_objects, num_points, 2].
labels	list[list[int]] | None	Legacy labels for points [num_objects, num_points].
boxes	list[list[int]] | None	Legacy box prompts [num_objects, 4].
propagate	bool | None	Whether to propagate masks beyond the prompted frames.
interval	TrackingInterval | None	Optional propagation interval relative to the provided frame window.
keyframes	list[TrackingKeyframe] | None	Optional structured prompt payloads for each object.
objects_ids	list[int]	IDs of the objects to generate masks for.
frame_indexes	list[int]	Indexes of the prompted frames.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )

TrackingInterval(**data)

Bases: BaseModel

Optional propagation window relative to the provided video frames.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )

TrackingKeyframe(**data)

Bases: BaseModel

Prompt payload for a single tracking keyframe.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )

TrackingModel(config)

Bases: InferenceModel

Base class for video mask generation / tracking models.

Example

@register_model("my-tracker")
class MyTracker(TrackingModel):
    def load_model(self):
        self.model = load_weights(self.config.model_params["path"])

    def predict(self, input: TrackingInput) -> TrackingOutput:
        ...
        return TrackingOutput(objects_ids=..., frame_indexes=..., masks=...)

Source code in pixano_inference/models/base.py

def __init__(self, config: ModelDeploymentConfig) -> None:
    """Initialize the model with deployment config.

    Args:
        config: Model deployment configuration.
    """
    self._config = config

predict(input) abstractmethod

Run video mask generation / tracking.

Parameters:

Name	Type	Description	Default
input	TrackingInput	Tracking input with video, prompts, and object IDs.	required

Returns:

Type	Description
TrackingOutput	Tracking output with objects_ids, frame_indexes, and masks.

Source code in pixano_inference/models/tracking.py

@abstractmethod
def predict(self, input: TrackingInput) -> TrackingOutput:
    """Run video mask generation / tracking.

    Args:
        input: Tracking input with video, prompts, and object IDs.

    Returns:
        Tracking output with objects_ids, frame_indexes, and masks.
    """

TrackingOutput(**data)

Bases: BaseModel

Output for video mask generation / tracking.

Attributes:

Name	Type	Description
objects_ids	list[int]	IDs of the objects.
frame_indexes	list[int]	Indexes of the frames where the objects are located.
masks	list[CompressedRLE]	Masks for the objects.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )

TrackingPointPrompt(**data)

Bases: BaseModel

Point prompt for a tracking keyframe.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )