pocketpose.models.wholebody
#
Submodules#
Package Contents#
Classes#
Interface for all TensorFlow Lite models. |
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Base class for the BlazePose models. |
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BlazePose-Lite model. |
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BlazePose-Full model. |
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BlazePose-Heavy model. |
Attributes#
- class pocketpose.models.wholebody.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.
- pocketpose.models.wholebody.model_registry#
- class pocketpose.models.wholebody.BlazePose(model_path: str, model_url: str, input_size: tuple)#
Bases:
pocketpose.models.interfaces.TFLiteModel
Base class for the BlazePose models.
- NUM_KEYPOINTS = 33#
- NUM_LANDMARKS = 39#
- LANDMARKS_DIM = 5#
- HEATMAPS_DIM = 39#
- 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]).
- _calculate_keypoints(landmark_points, heatmap, index, original_size)#
- postprocess_prediction(prediction, original_size)#
Postprocess the prediction.
- Args:
prediction (list): List of outputs from the model. original_size (tuple): Original size of the image as (height, width).