5 import generateLUT as genlut
11 def createLogC(gamut, transferFunction, exposureIndex, name, lutDir, lutResolution1d):
12 name = "%s (EI%s) - %s" % (transferFunction, exposureIndex, gamut)
13 if transferFunction == "":
14 name = "Linear - %s" % gamut
16 name = "%s (EI%s)" % (transferFunction, exposureIndex)
25 IDT_maker_version = "0.08"
28 blackSignal = 0.003907
30 encodingGain = 0.256598
31 encodingOffset = 0.391007
34 return (math.log(EI/nominalEI)/math.log(2) * (0.89 - 1) / 3 + 1) * encodingGain
36 def LogCInverseParametersForEI(EI) :
38 slope = 1.0 / (cut * math.log(10))
39 offset = math.log10(cut) - slope * cut
41 gray = midGraySignal / gain
42 # The higher the EI, the lower the gamma
43 encGain = gainForEI(EI)
44 encOffset = encodingOffset
46 nz = ((95.0 / 1023.0 - encOffset) / encGain - offset) / slope
47 encOffset = encodingOffset - math.log10(1 + nz) * encGain
48 # Calculate some intermediate values
50 b = nz - blackSignal / gray
51 e = slope * a * encGain
52 f = encGain * (slope * b + offset) + encOffset
53 # Manipulations so we can return relative exposure
62 'cut' : (cut - b) / a,
68 def logCtoLinear(codeValue, exposureIndex):
69 p = LogCInverseParametersForEI(exposureIndex)
70 breakpoint = p['e'] * p['cut'] + p['f']
71 if (codeValue > breakpoint):
72 linear = (pow(10,(codeValue/1023.0 - p['d']) / p['c']) - p['b']) / p['a']
74 linear = (codeValue/1023.0 - p['f']) / p['e']
76 #print( codeValue, linear )
80 cs.toReferenceTransforms = []
82 if transferFunction == "V3 LogC":
83 data = array.array('f', "\0" * lutResolution1d * 4)
84 for c in range(lutResolution1d):
85 data[c] = logCtoLinear(1023.0*c/(lutResolution1d-1), int(exposureIndex))
87 lut = "%s_to_linear.spi1d" % ("%s_%s" % (transferFunction, exposureIndex))
89 # Remove spaces and parentheses
90 lut = lut.replace(' ', '_').replace(')', '_').replace('(', '_')
92 genlut.writeSPI1D(lutDir + "/" + lut, 0.0, 1.0, data, lutResolution1d, 1)
94 #print( "Writing %s" % lut)
95 cs.toReferenceTransforms.append( {
98 'interpolation':'linear',
102 if gamut == 'Wide Gamut':
103 cs.toReferenceTransforms.append( {
105 'matrix':mat44FromMat33([0.680206, 0.236137, 0.083658,
106 0.085415, 1.017471, -0.102886,
107 0.002057, -0.062563, 1.060506]),
108 'direction':'forward'
111 cs.fromReferenceTransforms = []
114 def createColorSpaces(lutDir, lutResolution1d):
117 transferFunction = "V3 LogC"
119 #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]
120 EIs = [160, 200, 250, 320, 400, 500, 640, 800, 1000, 1280, 1600, 2000, 2560, 3200]
125 LogCEIfull = createLogC(gamut, transferFunction, EI, "LogC", lutDir, lutResolution1d)
126 colorspaces.append(LogCEIfull)
130 LogCEIlinearization = createLogC("", transferFunction, EI, "LogC", lutDir, lutResolution1d)
131 colorspaces.append(LogCEIlinearization)
134 LogCEIprimaries = createLogC(gamut, "", defaultEI, "LogC", lutDir, lutResolution1d)
135 colorspaces.append(LogCEIprimaries)