Source code for pyctools.components.colourspace.quantise

#  Pyctools - a picture processing algorithm development kit.
#  http://github.com/jim-easterbrook/pyctools
#  Copyright (C) 2016-19  Pyctools contributors
#
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#  but WITHOUT ANY WARRANTY; without even the implied warranty of
#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
#  General Public License for more details.
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__all__ = ['ErrorFeedbackQuantise']
__docformat__ = 'restructuredtext en'

import numpy

from pyctools.core.base import Transformer

[docs] class ErrorFeedbackQuantise(Transformer): """Quantisation with error feedback. Round data to integer values, using error feedback (see http://www.bbc.co.uk/rd/publications/rdreport_1987_12) to reduce the visibility of quantisation effects. Note that if the input image is already quantised this component will have no effect. Hence it is recommended always to be used before any component that truncates the data, such as :py:class:`~pyctools.components.io.imagefilepil.ImageFileWriterPIL`. """ def transform(self, in_frame, out_frame): self.update_config() # get data data = in_frame.as_numpy(copy=True) h, w, c = data.shape if data.dtype == numpy.uint8: pass elif w >= h: # seed error feedback with random numbers in range [0, 1) # mean value 0.5 means numpy.floor is effectively 'round' residue = numpy.random.random((h, c)).astype(data.dtype) for x in range(w): # add residue c_data = data[::, x, ::] + residue # quantise q_data = numpy.floor(c_data) data[::, x, ::] = q_data # compute new residue residue = c_data - q_data else: # seed error feedback with random numbers in range [0, 1) # mean value 0.5 means numpy.floor is effectively 'round' residue = numpy.random.random((w, c)).astype(data.dtype) for y in range(h): # add residue c_data = data[y, ::, ::] + residue # quantise q_data = numpy.floor(c_data) data[y, ::, ::] = q_data # compute new residue residue = c_data - q_data out_frame.data = data # add audit audit = out_frame.metadata.get('audit') audit += 'data = ErrorFeedbackQuantise(data)\n' out_frame.metadata.set('audit', audit) return True