normalize_norm

menpo.feature.normalize_norm(pixels, mode='all', error_on_divide_by_zero=True)[source]

Normalize the pixels to be mean centred and have unit norm. The mode parameter selects whether the normalisation is computed across all pixels in the image or per-channel.

Parameters

  • pixels (Image or subclass or (C, X, Y, ..., Z) ndarray) – Either the image object itself or an array with the pixels. The first dimension is interpreted as channels. This means an N-dimensional image is represented by an N+1 dimensional array.

  • mode ({all, per_channel}, optional) – If all, the normalization is over all channels. If per_channel, each channel individually is mean centred and normalized in variance.

  • error_on_divide_by_zero (bool, optional) – If True, will raise a ValueError on dividing by zero. If False, will merely raise a warning and only those values with non-zero denominators will be normalized.

Returns

pixels (Image or subclass or (X, Y, ..., Z, C) ndarray) – A normalized copy of the image that was passed in.

Raises

ValueError – If any of the denominators are 0 and error_on_divide_by_zero is True.