82 lines
2.5 KiB
Python
82 lines
2.5 KiB
Python
import numpy as np
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__all__ = ['load_sift', 'load_surf']
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def _sift_read(filelike, mode='SIFT'):
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"""Read SIFT or SURF features from externally generated file.
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This routine reads SIFT or SURF files generated by binary utilities from
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http://people.cs.ubc.ca/~lowe/keypoints/ and
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http://www.vision.ee.ethz.ch/~surf/.
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This routine *does not* generate SIFT/SURF features from an image. These
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algorithms are patent encumbered. Please use `skimage.feature.CENSURE`
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instead.
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Parameters
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----------
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filelike : string or open file
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Input file generated by the feature detectors from
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http://people.cs.ubc.ca/~lowe/keypoints/ or
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http://www.vision.ee.ethz.ch/~surf/ .
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mode : {'SIFT', 'SURF'}, optional
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Kind of descriptor used to generate `filelike`.
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Returns
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-------
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data : record array with fields
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- row: int
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row position of feature
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- column: int
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column position of feature
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- scale: float
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feature scale
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- orientation: float
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feature orientation
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- data: array
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feature values
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"""
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if isinstance(filelike, str):
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f = open(filelike, 'r')
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filelike_is_str = True
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else:
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f = filelike
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filelike_is_str = False
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if mode == 'SIFT':
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nr_features, feature_len = map(int, f.readline().split())
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datatype = np.dtype([('row', float), ('column', float),
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('scale', float), ('orientation', float),
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('data', (float, feature_len))])
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else:
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mode = 'SURF'
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feature_len = int(f.readline()) - 1
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nr_features = int(f.readline())
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datatype = np.dtype([('column', float), ('row', float),
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('second_moment', (float, 3)),
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('sign', float), ('data', (float, feature_len))])
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data = np.fromfile(f, sep=' ')
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if data.size != nr_features * datatype.itemsize / np.dtype(float).itemsize:
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raise IOError("Invalid {} feature file.".format(mode))
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# If `filelike` is passed to the function as filename - close the file
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if filelike_is_str:
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f.close()
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return data.view(datatype)
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def load_sift(f):
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return _sift_read(f, mode='SIFT')
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def load_surf(f):
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return _sift_read(f, mode='SURF')
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load_sift.__doc__ = _sift_read.__doc__
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load_surf.__doc__ = _sift_read.__doc__
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