pocketpose.models.interfaces.onnxmodel
#
Module Contents#
Classes#
Interface for all ONNX models. |
- class pocketpose.models.interfaces.onnxmodel.ONNXModel(model_path: str, model_url: str, **kwargs)#
Bases:
pocketpose.models.interfaces.imodel.IModel
Interface for all ONNX models.
We assume that the model has a single input, but it can have multiple outputs.
- process_image(image)#
Default implementation of process_image() for models that don’t need preprocessing.
This method can be overridden by subclasses to implement model-specific preprocessing.
- Args:
- image (np.ndarray): The image to prepare for prediction. The image is a numpy
array with shape (1, height, width, channels) and dtype uint8 (range [0, 255]).
- predict(image: numpy.ndarray) Any #
Predicts the pose of the image.
- Args:
- image (np.ndarray): The image to predict the pose of. The image has
the shape and dtype expected by the model.
- Returns:
The prediction returned by the model. This can be a single tensor or a tuple of tensors, depending on the model.