Implements support for *ARRI* colorspaces conversions and transfer functions.
"""
+from __future__ import division
+
import array
import math
+import os
+
+import PyOpenColorIO as ocio
import aces_ocio.generate_lut as genlut
-from aces_ocio.utilities import ColorSpace, mat44_from_mat33
+from aces_ocio.utilities import ColorSpace, mat44_from_mat33, sanitize
__author__ = 'ACES Developers'
exposure_index,
name,
lut_directory,
- lut_resolution_1d):
+ lut_resolution_1d,
+ aliases):
"""
Object description.
Return value description.
"""
- name = "%s (EI%s) - %s" % (transfer_function, exposure_index, gamut)
- if transfer_function == "":
- name = "Linear - %s" % gamut
- if gamut == "":
- name = "%s (EI%s)" % (transfer_function, exposure_index)
+ name = '%s (EI%s) - %s' % (transfer_function, exposure_index, gamut)
+ if transfer_function == '':
+ name = 'Linear - ARRI %s' % gamut
+ if gamut == '':
+ name = '%s (EI%s)' % (transfer_function, exposure_index)
cs = ColorSpace(name)
cs.description = name
+ cs.aliases = aliases
cs.equality_group = ''
- cs.family = 'ARRI'
+ cs.family = 'Input/ARRI'
cs.is_data = False
- # Globals
- IDT_maker_version = "0.08"
+ # A linear space needs allocation variables
+ if transfer_function == '':
+ cs.allocation_type = ocio.Constants.ALLOCATION_LG2
+ cs.allocation_vars = [-8, 5, 0.00390625]
- nominal_EI = 400.0
+ # Globals.
+ IDT_maker_version = '0.08'
+
+ nominal_EI = 400
black_signal = 0.003907
mid_gray_signal = 0.01
encoding_gain = 0.256598
0.89 - 1) / 3 + 1) * encoding_gain
def log_c_inverse_parameters_for_EI(EI):
- cut = 1.0 / 9.0
- slope = 1.0 / (cut * math.log(10))
+ cut = 1 / 9
+ slope = 1 / (cut * math.log(10))
offset = math.log10(cut) - slope * cut
gain = EI / nominal_EI
gray = mid_gray_signal / gain
- # The higher the EI, the lower the gamma
+ # The higher the EI, the lower the gamma.
enc_gain = gain_for_EI(EI)
enc_offset = encoding_offset
for i in range(0, 3):
- nz = ((95.0 / 1023.0 - enc_offset) / enc_gain - offset) / slope
+ nz = ((95 / 1023 - enc_offset) / enc_gain - offset) / slope
enc_offset = encoding_offset - math.log10(1 + nz) * enc_gain
- # Calculate some intermediate values
- a = 1.0 / gray
+
+ a = 1 / gray
b = nz - black_signal / gray
e = slope * a * enc_gain
f = enc_gain * (slope * b + offset) + enc_offset
- # Manipulations so we can return relative exposure
+
+ # Ensuring we can return relative exposure.
s = 4 / (0.18 * EI)
t = black_signal
b += a * t
'e': e,
'f': f}
- def log_c_to_linear(code_value, exposure_index):
+ def normalized_log_c_to_linear(code_value, exposure_index):
p = log_c_inverse_parameters_for_EI(exposure_index)
breakpoint = p['e'] * p['cut'] + p['f']
- if (code_value > breakpoint):
- linear = ((pow(10, (code_value / 1023.0 - p['d']) / p['c']) -
+ if code_value > breakpoint:
+ linear = ((pow(10, (code_value - p['d']) / p['c']) -
p['b']) / p['a'])
else:
- linear = (code_value / 1023.0 - p['f']) / p['e']
-
- # print(codeValue, linear)
+ linear = (code_value - p['f']) / p['e']
return linear
-
cs.to_reference_transforms = []
- if transfer_function == "V3 LogC":
- data = array.array('f', "\0" * lut_resolution_1d * 4)
+ if transfer_function == 'V3 LogC':
+ data = array.array('f', '\0' * lut_resolution_1d * 4)
for c in range(lut_resolution_1d):
- data[c] = log_c_to_linear(1023.0 * c / (lut_resolution_1d - 1),
- int(exposure_index))
+ data[c] = normalized_log_c_to_linear(c / (lut_resolution_1d - 1),
+ int(exposure_index))
- lut = "%s_to_linear.spi1d" % (
- "%s_%s" % (transfer_function, exposure_index))
+ lut = '%s_to_linear.spi1d' % (
+ '%s_%s' % (transfer_function, exposure_index))
- # Remove spaces and parentheses
- lut = lut.replace(' ', '_').replace(')', '_').replace('(', '_')
+ lut = sanitize(lut)
- genlut.write_SPI_1d(lut_directory + "/" + lut,
- 0.0,
- 1.0,
- data,
- lut_resolution_1d,
- 1)
+ genlut.write_SPI_1d(
+ os.path.join(lut_directory, lut),
+ 0,
+ 1,
+ data,
+ lut_resolution_1d,
+ 1)
- # print("Writing %s" % lut)
cs.to_reference_transforms.append({
'type': 'lutFile',
'path': lut,
cs.to_reference_transforms.append({
'type': 'matrix',
'matrix': mat44_from_mat33([0.680206, 0.236137, 0.083658,
- 0.085415, 1.017471, -0.102886,
- 0.002057, -0.062563, 1.060506]),
+ 0.085415, 1.017471, -0.102886,
+ 0.002057, -0.062563, 1.060506]),
'direction': 'forward'
})
colorspaces = []
- transfer_function = "V3 LogC"
- gamut = "Wide Gamut"
+ transfer_function = 'V3 LogC'
+ gamut = 'Wide Gamut'
- # EIs = [160.0, 200.0, 250.0, 320.0, 400.0, 500.0, 640.0, 800.0,
- # 1000.0, 1280.0, 1600.0, 2000.0, 2560.0, 3200.0]
+ # EIs = [160, 200, 250, 320, 400, 500, 640, 800,
+ # 1000, 1280, 1600, 2000, 2560, 3200]
EIs = [160, 200, 250, 320, 400, 500, 640, 800,
1000, 1280, 1600, 2000, 2560, 3200]
default_EI = 800
- # Full conversion
+ # Full Conversion
for EI in EIs:
log_c_EI_full = create_log_c(
gamut,
transfer_function,
EI,
- "LogC",
+ 'LogC',
lut_directory,
- lut_resolution_1d)
+ lut_resolution_1d,
+ ["%sei%s_%s" % ("logc3", str(EI), "arriwide")])
colorspaces.append(log_c_EI_full)
- # Linearization only
+ # Linearization Only
for EI in [800]:
log_c_EI_linearization = create_log_c(
- "",
+ '',
transfer_function,
EI,
- "LogC",
+ 'LogC',
lut_directory,
- lut_resolution_1d)
+ lut_resolution_1d,
+ ["crv_%sei%s" % ("logc3", str(EI))])
colorspaces.append(log_c_EI_linearization)
- # Primaries
+ # Primaries Only
log_c_EI_primaries = create_log_c(
gamut,
- "",
+ '',
default_EI,
- "LogC",
+ 'LogC',
lut_directory,
- lut_resolution_1d)
+ lut_resolution_1d,
+ ["%s_%s" % ('lin', "arriwide")])
colorspaces.append(log_c_EI_primaries)
return colorspaces
projects / OpenColorIO-Configs.git / blobdiff