"""Create statistical appearance model (SAM) for a set of samples."""
from copy import copy
import numpy as np
from . import StatisticalModelBase
[docs]
class SAM(StatisticalModelBase):
"""Create statistical appearance model for a set of samples.
Parameters
----------
appearance : array_like
Appearances for landmarks in dataset, with 2 dimensions.
First dimension has size equal to the number of samples.
Second dimension has size equal to the number of landmarks per sample.
Examples
========
>>> import numpy as np
>>> import pyssam
>>> num_samples = 5
>>> num_landmarks = 10
>>> appearances = np.random.normal(size=(num_samples, num_landmarks))
>>> sam = pyssam.SAM(appearances)
>>> print(sam.appearance_scale.shape)
(5, 10, 1)
>>> print(sam.compute_dataset_mean().shape)
(10,)
"""
def __init__(self, appearance: np.ndarray):
# initialise variables
self._num_landmarks = appearance.shape[1]
self.appearance_base = copy(appearance)
self.appearance_scale = self.scale_dataset(appearance)
self.appearance_columns_scale = self.landmark_data_to_column(
self.appearance_scale
)
[docs]
def compute_dataset_mean(self) -> np.array:
"""Average over all samples to produce a column-vector of the mean
appearance.
Returns
-------
mean_columnvector : array_like
mean appearance of all samples in dataset
"""
return np.mean(self.appearance_columns_scale, axis=0)