def __init__()

in models/vision/detection/awsdet/core/anchor/anchor_generator.py [0:0]

• 45 lines of code
• 12 McCabe index (conditional complexity)

    def __init__(self,
                 strides,
                 ratios,
                 scales=None,
                 base_sizes=None,
                 scale_major=True,
                 octave_base_scale=None,
                 scales_per_octave=None,
                 centers=None,
                 center_offset=0.):
        # check center and center_offset
        if center_offset != 0:
            assert centers is None, 'center cannot be set when center_offset' \
                f'!=0, {centers} is given.'
        if not (0 <= center_offset <= 1):
            raise ValueError('center_offset should be in range [0, 1], '
                             f'{center_offset} is given.')
        if centers is not None:
            assert len(centers) == len(strides), \
                'The number of strides should be the same as centers, got ' \
                f'{strides} and {centers}'

        # calculate base sizes of anchors
        self.strides = strides
        self.base_sizes = list(strides) if base_sizes is None else base_sizes
        assert len(self.base_sizes) == len(self.strides), \
            'The number of strides should be the same as base sizes, got ' \
            f'{self.strides} and {self.base_sizes}'

        # calculate scales of anchors
        assert ((octave_base_scale is not None
                and scales_per_octave is not None) ^ (scales is not None)), \
            'scales and octave_base_scale with scales_per_octave cannot' \
            ' be set at the same time'
        if scales is not None:
            self.scales = tf.constant(scales)
        elif octave_base_scale is not None and scales_per_octave is not None:
            octave_scales = [2**(i / scales_per_octave) for i in range(scales_per_octave)]
            scales = [octave_base_scale * octave_scale for octave_scale in octave_scales] 
            self.scales = tf.constant(scales)
        else:
            raise ValueError('Either scales or octave_base_scale with '
                             'scales_per_octave should be set')

        self.octave_base_scale = octave_base_scale
        self.scales_per_octave = scales_per_octave
        self.ratios = tf.constant(ratios)
        self.scale_major = scale_major
        self.centers = centers
        self.center_offset = center_offset
        self.base_anchors = self.gen_base_anchors()