diff options
| -rw-r--r-- | data/aces2065_1.coeff | bin | 0 -> 9437448 bytes | |||
| -rw-r--r-- | data/prophotorgb.coeff | bin | 0 -> 9437448 bytes | |||
| -rw-r--r-- | data/rec2020.coeff | bin | 0 -> 9437448 bytes | |||
| -rw-r--r-- | data/srgb.coeff | bin | 0 -> 9437448 bytes | |||
| -rw-r--r-- | jakob_hanika.py | 5 | ||||
| -rw-r--r-- | test_coeff.py | 59 |
6 files changed, 62 insertions, 2 deletions
diff --git a/data/aces2065_1.coeff b/data/aces2065_1.coeff Binary files differnew file mode 100644 index 0000000..25614e7 --- /dev/null +++ b/data/aces2065_1.coeff diff --git a/data/prophotorgb.coeff b/data/prophotorgb.coeff Binary files differnew file mode 100644 index 0000000..2c15813 --- /dev/null +++ b/data/prophotorgb.coeff diff --git a/data/rec2020.coeff b/data/rec2020.coeff Binary files differnew file mode 100644 index 0000000..7ce1269 --- /dev/null +++ b/data/rec2020.coeff diff --git a/data/srgb.coeff b/data/srgb.coeff Binary files differnew file mode 100644 index 0000000..a0b2ba2 --- /dev/null +++ b/data/srgb.coeff diff --git a/jakob_hanika.py b/jakob_hanika.py index af55c94..22b87fc 100644 --- a/jakob_hanika.py +++ b/jakob_hanika.py @@ -15,10 +15,11 @@ def model(wvlp, ccp): return 1 / 2 + yy / (2 * np.sqrt(1 + yy ** 2)) # Create a SpectralDistribution using given coefficients -def model_sd(ccp): +def model_sd(ccp, primed=True): # FIXME: don't hardcode the wavelength grid; there should be a way # of creating a SpectralDistribution from the function alone - return SpectralDistribution(model(wvlp, ccp), wvl, name="Model") + grid = wvlp if primed else wvl + return SpectralDistribution(model(grid, ccp), wvl, name="Model") # The goal is to minimize the color difference between a given distrbution # and the one computed from the model above. diff --git a/test_coeff.py b/test_coeff.py new file mode 100644 index 0000000..e53c6f1 --- /dev/null +++ b/test_coeff.py @@ -0,0 +1,59 @@ +import numpy as np, struct +from scipy.interpolate import RegularGridInterpolator +from colour import * +from colour.plotting import * +from colour.models import eotf_inverse_sRGB +from jakob_hanika import jakob_hanika, model_sd +from test_colorchecker import plot_comparison + + + +illuminant = "D65" +ill_xy = ILLUMINANTS["CIE 1931 2 Degree Standard Observer"][illuminant] +ill_sd = SpectralDistribution(ILLUMINANTS_SDS[illuminant]) + + + +class JakobHanikaInterpolator: + def __init__(self): + pass + + def read_file(self, path): + with open(path, "rb") as fd: + if fd.read(4).decode("ISO-8859-1") != "SPEC": + raise ValueError("bad magic number") + + self.res = struct.unpack("i", fd.read(4))[0] + self.scale = np.fromfile(fd, count=self.res, dtype=np.float32) # FIXME: default dtype + coeffs = np.fromfile(fd, count=3*self.res**3*3, dtype=np.float32) # FIXME: default dtype + coeffs = coeffs.reshape(3, self.res, self.res, self.res, 3) + + t = np.linspace(0, 1, self.res) + axes = [self.scale, t, t] + self.cubes = [RegularGridInterpolator(axes, coeffs[j, :, :, :, :], bounds_error=False) for j in range(3)] + + def __call__(self, RGB): + RGB = np.asarray(RGB, dtype=np.float) # FIXME: default dtype + vmax = RGB.max() + imax = RGB.argmax() + cube = self.cubes[imax] + chroma = RGB / (vmax + 1e-10) + chroma = np.array([ + vmax, + chroma[..., (imax + 2) % 3], + chroma[..., (imax + 1) % 3] + ]) + return cube(chroma).squeeze() + + + +if __name__ == "__main__": + jh = JakobHanikaInterpolator() + jh.read_file("data/srgb.coeff") + + linear_RGB = np.array([1, 0, 0]) # A random test color + RGB = eotf_inverse_sRGB(linear_RGB) + XYZ = sRGB_to_XYZ(RGB) + cc = jh(linear_RGB) + + plot_comparison(XYZ, model_sd(cc, primed=False), "Model", 123, ill_sd) |