pocketpose.models.interfaces.tflitemodel
#
Module Contents#
Classes#
Interface for all TensorFlow Lite models. |
- class pocketpose.models.interfaces.tflitemodel.TFLiteModel(model_path: str, model_url: str, **kwargs)#
Bases:
pocketpose.models.interfaces.imodel.IModel
Interface for all TensorFlow Lite 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]).
- get_output(output_idx: int) numpy.ndarray #
Returns the output tensor of the model.
- Args:
output_idx (int): The index of the output tensor to return.
- Returns:
The output tensor as a numpy array.
- 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.