2 # -*- coding: utf-8 -*-
5 Implements support for *ARRI* colorspaces conversions and transfer functions.
12 import aces_ocio.generate_lut as genlut
13 from aces_ocio.utilities import ColorSpace, mat44_from_mat33, sanitize_path
16 __author__ = 'ACES Developers'
17 __copyright__ = 'Copyright (C) 2014 - 2015 - ACES Developers'
19 __maintainer__ = 'ACES Developers'
20 __email__ = 'aces@oscars.org'
21 __status__ = 'Production'
23 __all__ = ['create_log_c',
27 def create_log_c(gamut,
41 Parameter description.
46 Return value description.
49 name = '%s (EI%s) - %s' % (transfer_function, exposure_index, gamut)
50 if transfer_function == '':
51 name = 'Linear - %s' % gamut
53 name = '%s (EI%s)' % (transfer_function, exposure_index)
57 cs.equality_group = ''
62 IDT_maker_version = '0.08'
65 black_signal = 0.003907
66 mid_gray_signal = 0.01
67 encoding_gain = 0.256598
68 encoding_offset = 0.391007
71 return (math.log(EI / nominal_EI) / math.log(2) * (
72 0.89 - 1) / 3 + 1) * encoding_gain
74 def log_c_inverse_parameters_for_EI(EI):
76 slope = 1.0 / (cut * math.log(10))
77 offset = math.log10(cut) - slope * cut
78 gain = EI / nominal_EI
79 gray = mid_gray_signal / gain
80 # The higher the EI, the lower the gamma.
81 enc_gain = gain_for_EI(EI)
82 enc_offset = encoding_offset
84 nz = ((95.0 / 1023.0 - enc_offset) / enc_gain - offset) / slope
85 enc_offset = encoding_offset - math.log10(1 + nz) * enc_gain
88 b = nz - black_signal / gray
89 e = slope * a * enc_gain
90 f = enc_gain * (slope * b + offset) + enc_offset
92 # Ensuring we can return relative exposure.
102 'cut': (cut - b) / a,
108 def log_c_to_linear(code_value, exposure_index):
109 p = log_c_inverse_parameters_for_EI(exposure_index)
110 breakpoint = p['e'] * p['cut'] + p['f']
111 if code_value > breakpoint:
112 linear = ((pow(10, (code_value / 1023.0 - p['d']) / p['c']) -
115 linear = (code_value / 1023.0 - p['f']) / p['e']
118 cs.to_reference_transforms = []
120 if transfer_function == 'V3 LogC':
121 data = array.array('f', '\0' * lut_resolution_1d * 4)
122 for c in range(lut_resolution_1d):
123 data[c] = log_c_to_linear(1023.0 * c / (lut_resolution_1d - 1),
126 lut = '%s_to_linear.spi1d' % (
127 '%s_%s' % (transfer_function, exposure_index))
129 lut = sanitize_path(lut)
132 os.path.join(lut_directory, lut),
139 cs.to_reference_transforms.append({
142 'interpolation': 'linear',
143 'direction': 'forward'
146 if gamut == 'Wide Gamut':
147 cs.to_reference_transforms.append({
149 'matrix': mat44_from_mat33([0.680206, 0.236137, 0.083658,
150 0.085415, 1.017471, -0.102886,
151 0.002057, -0.062563, 1.060506]),
152 'direction': 'forward'
155 cs.from_reference_transforms = []
159 def create_colorspaces(lut_directory, lut_resolution_1d):
161 Generates the colorspace conversions.
166 Parameter description.
171 Return value description.
176 transfer_function = 'V3 LogC'
179 # EIs = [160.0, 200.0, 250.0, 320.0, 400.0, 500.0, 640.0, 800.0,
180 # 1000.0, 1280.0, 1600.0, 2000.0, 2560.0, 3200.0]
181 EIs = [160, 200, 250, 320, 400, 500, 640, 800,
182 1000, 1280, 1600, 2000, 2560, 3200]
187 log_c_EI_full = create_log_c(
194 colorspaces.append(log_c_EI_full)
198 log_c_EI_linearization = create_log_c(
205 colorspaces.append(log_c_EI_linearization)
208 log_c_EI_primaries = create_log_c(
215 colorspaces.append(log_c_EI_primaries)