colour.characterisation.training_data_sds_to_RGB¶
- colour.characterisation.training_data_sds_to_RGB(training_data: colour.colorimetry.spectrum.MultiSpectralDistributions, sensitivities: colour.characterisation.cameras.RGB_CameraSensitivities, illuminant: colour.colorimetry.spectrum.SpectralDistribution) Tuple[numpy.ndarray, numpy.ndarray] [source]¶
Convert given training data to RGB tristimulus values using given illuminant and given camera RGB spectral sensitivities.
- Parameters
training_data (colour.colorimetry.spectrum.MultiSpectralDistributions) – Training data multi-spectral distributions.
sensitivities (colour.characterisation.cameras.RGB_CameraSensitivities) – Camera RGB spectral sensitivities.
illuminant (colour.colorimetry.spectrum.SpectralDistribution) – Illuminant spectral distribution.
- Returns
Tuple of training data RGB tristimulus values and white balance multipliers.
- Return type
Examples
>>> path = os.path.join( ... RESOURCES_DIRECTORY_RAWTOACES, ... 'CANON_EOS_5DMark_II_RGB_Sensitivities.csv') >>> sensitivities = sds_and_msds_to_msds( ... read_sds_from_csv_file(path).values()) >>> illuminant = normalise_illuminant( ... SDS_ILLUMINANTS['D55'], sensitivities) >>> training_data = read_training_data_rawtoaces_v1() >>> RGB, RGB_w = training_data_sds_to_RGB( ... training_data, sensitivities, illuminant) >>> RGB[:5] array([[ 0.0207582..., 0.0196857..., 0.0213935...], [ 0.0895775..., 0.0891922..., 0.0891091...], [ 0.7810230..., 0.7801938..., 0.7764302...], [ 0.1995 ..., 0.1995 ..., 0.1995 ...], [ 0.5898478..., 0.5904015..., 0.5851076...]]) >>> RGB_w array([ 2.3414154..., 1. , 1.5163375...])