haar_like_feature_coord(width, height, feature_type=None)

Parameters

width : int

Width of the detection window.

height : int

Height of the detection window.

feature_type : str or list of str or None, optional

The type of feature to consider:

• 'type-2-x': 2 rectangles varying along the x axis;

• 'type-2-y': 2 rectangles varying along the y axis;

• 'type-3-x': 3 rectangles varying along the x axis;

• 'type-3-y': 3 rectangles varying along the y axis;

• 'type-4': 4 rectangles varying along x and y axis.

By default all features are extracted.

Returns

feature_coord : (n_features, n_rectangles, 2, 2), ndarray of list of tuple coord

Coordinates of the rectangles for each feature.

feature_type : (n_features,), ndarray of str

The corresponding type for each feature.

Compute the coordinates of Haar-like features.

Examples

This example is valid syntax, but we were not able to check execution

>>> import numpy as np
... from skimage.transform import integral_image
... from skimage.feature import haar_like_feature_coord
... feat_coord, feat_type = haar_like_feature_coord(2, 2, 'type-4')
... feat_coord # doctest: +SKIP
array([ list([[(0, 0), (0, 0)], [(0, 1), (0, 1)],
              [(1, 1), (1, 1)], [(1, 0), (1, 0)]])], dtype=object)

This example is valid syntax, but we were not able to check execution

>>> feat_type
array(['type-4'], dtype=object)

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

skimage.feature.haar.haar_like_feature skimage.feature.haar.draw_haar_like_feature skimage.feature.haar.haar_like_feature_coord

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