pocketpose.models.body.rtmpose#

Module Contents#

Classes#

RTMPose

Base class for RTMPose models.

RTMPoseM

MoveNet Lightning model.

class pocketpose.models.body.rtmpose.RTMPose(model_path: str, model_url: str, input_size: tuple)#

Bases: pocketpose.models.interfaces.ONNXModel

Base class for RTMPose models.

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]).

postprocess_prediction(prediction, original_size) List[List[float]]#

Postprocesses the prediction to get the keypoints.

Args:
prediction (Any): The raw prediction returned by the model. This can

be a single tensor or a tuple of tensors, depending on the model.

original_size (tuple): The original size of the input image as (height, width).

Returns:

The predicted keypoints as a list of (x, y, score) tuples.

class pocketpose.models.body.rtmpose.RTMPoseM#

Bases: RTMPose

MoveNet Lightning model.