pixano_inference.providers.base

Base classes for providers.

APIProvider(**kwargs)

Bases: BaseProvider

Base class for API providers.

Source code in pixano_inference/providers/base.py

def __init__(self, **kwargs: Any):
    """Initialize the provider."""
    pass

api_url abstractmethod property

URL of the API.

send_request(request) abstractmethod

Send a request to the API and return the response.

Parameters:

Name	Type	Description	Default
request	APIRequest	Request to send.	required

Returns:

Type	Description
BaseResponse	Response from the API.

Source code in pixano_inference/providers/base.py

@abstractmethod
def send_request(self, request: APIRequest) -> BaseResponse:
    """Send a request to the API and return the response.

    Args:
        request: Request to send.

    Returns:
        Response from the API.
    """
    ...

BaseProvider(**kwargs)

Bases: ABC

Base class for providers.

Source code in pixano_inference/providers/base.py

def __init__(self, **kwargs: Any):
    """Initialize the provider."""
    pass

image_mask_generation(request, model, *args, **kwargs)

Generate a mask from the image.

Parameters:

Name	Type	Description	Default
request	ImageMaskGenerationRequest	Request for the generation.	required
model	BaseInferenceModel	Model to use for the generation.	required
args	Any	Additional arguments.	()
kwargs	Any	Additional keyword arguments.	{}

Source code in pixano_inference/providers/base.py

def image_mask_generation(
    self, request: ImageMaskGenerationRequest, model: BaseInferenceModel, *args: Any, **kwargs: Any
) -> ImageMaskGenerationOutput:
    """Generate a mask from the image.

    Args:
        request: Request for the generation.
        model: Model to use for the generation.
        args: Additional arguments.
        kwargs: Additional keyword arguments.
    """
    raise NotImplementedError("This provider does not support image mask generation.")

image_zero_shot_detection(request, model, *args, **kwargs)

Perform zero-shot image detection.

Source code in pixano_inference/providers/base.py

def image_zero_shot_detection(
    self, request: ImageZeroShotDetectionRequest, model: BaseInferenceModel, *args: Any, **kwargs: Any
) -> ImageZeroShotDetectionOutput:
    """Perform zero-shot image detection."""
    raise NotImplementedError("This provider does not support image zero-shot detection.")

text_image_conditional_generation(request, model, *args, **kwargs)

Generate an image from the text and image.

Parameters:

Name	Type	Description	Default
request	TextImageConditionalGenerationRequest	Request for the generation.	required
model	BaseInferenceModel	Model to use for the generation.	required
args	Any	Additional arguments.	()
kwargs	Any	Additional keyword arguments.	{}

Returns:

Type	Description
TextImageConditionalGenerationOutput	Output of the generation

Source code in pixano_inference/providers/base.py

def text_image_conditional_generation(
    self, request: TextImageConditionalGenerationRequest, model: BaseInferenceModel, *args: Any, **kwargs: Any
) -> TextImageConditionalGenerationOutput:
    """Generate an image from the text and image.

    Args:
        request: Request for the generation.
        model: Model to use for the generation.
        args: Additional arguments.
        kwargs: Additional keyword arguments.

    Returns:
        Output of the generation
    """
    raise NotImplementedError("This provider does not support text-image conditional generation.")

video_mask_generation(request, model, *args, **kwargs)

Generate a mask from the video.

Parameters:

Name	Type	Description	Default
request	VideoMaskGenerationRequest	Request for the generation.	required
model	BaseInferenceModel	Model to use for the generation.	required
args	Any	Additional arguments.	()
kwargs	Any	Additional keyword arguments.	{}

Returns:

Type	Description
VideoMaskGenerationOutput	Output of the generation

Source code in pixano_inference/providers/base.py

def video_mask_generation(
    self, request: VideoMaskGenerationRequest, model: BaseInferenceModel, *args: Any, **kwargs: Any
) -> VideoMaskGenerationOutput:
    """Generate a mask from the video.

    Args:
        request: Request for the generation.
        model: Model to use for the generation.
        args: Additional arguments.
        kwargs: Additional keyword arguments.

    Returns:
        Output of the generation
    """
    raise NotImplementedError("This provider does not support video mask generation.")

ModelProvider(**kwargs)

Bases: BaseProvider

Base class for model providers.

Source code in pixano_inference/providers/base.py

def __init__(self, **kwargs: Any):
    """Initialize the provider."""
    pass

load_model(name, task, device, path=None, processor_config={}, config={}) abstractmethod

Load the model from the provider.

Parameters:

Name	Type	Description	Default
name	str	Name of the model.	required
task	Task | str	Task of the model.	required
device	device	Device to use for the model.	required
path	Path | str | None	Path to the model.	None
processor_config	dict	Processor configuration.	{}
config	dict	Configuration for the model.	{}

Returns:

Type	Description
BaseInferenceModel	The loaded model.

Source code in pixano_inference/providers/base.py

@abstractmethod
def load_model(
    self,
    name: str,
    task: Task | str,
    device: "torch.device",
    path: Path | str | None = None,
    processor_config: dict = {},
    config: dict = {},
) -> "BaseInferenceModel":
    """Load the model from the provider.

    Args:
        name: Name of the model.
        task: Task of the model.
        device: Device to use for the model.
        path: Path to the model.
        processor_config: Processor configuration.
        config: Configuration for the model.

    Returns:
        The loaded model.
    """
    ...