#!/usr/bin/env python3
# Copyright © 2014 Mattias Andrée (maandree@member.fsf.org)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see .
# This module implements support for ICC profiles
import os
from subprocess import Popen, PIPE
from curve import *
LIBEXECDIR = 'bin'
'''
:str Path to executable libraries, '/usr/libexec' is standard
'''
def load_icc(pathname):
'''
Load ICC profile from a file
@param pathname:str The ICC profile file
@return :()→void Function to invoke, parameterless, to apply the ICC profile to the colour curves
'''
with open(pathname, 'rb') as file:
return parse_icc(file.read())
def get_current_icc(display = None):
'''
Get all currently applied ICC profiles as profile applying functions
@param display:str? The display to use, `None` for the current one
@return list<(screen:int, monitor:int, profile:()→void)> List of used profiles
'''
return [(screen, monitor, parse_icc(profile)) for screen, monitor, profile in get_current_icc_raw(display)]
def get_current_icc_raw(display = None):
'''
Get all currently applied ICC profiles as raw profile data
@param display:str? The display to use, `None` for the current one
@return list<(screen:int, monitor:int, profile:bytes())> List of used profiles
'''
# Generate command line arguments to execute
command = [LIBEXECDIR + os.sep + 'blueshift_iccprofile']
if display is not None:
command.append(display)
# Spawn the libexec blueshift_iccprofile
process = Popen(command, stdout = PIPE)
# Wait for the child process to exit and gather its output to stdout
lines = process.communicate()[0].decode('utf-8', 'error').split('\n')
# Ensure the tha process has exited
while process.returncode is None:
process.wait()
# Throw exception if the child process failed
if process.returncode != 0:
raise Exception('blueshift_iccprofile exited with value %i' % process.returncode)
rc = []
# Get the screen, output and profile for each monitor with an _ICC_PROFILE(_n) atom set
for s, m, p in [line.split(': ') for line in lines if not line == '']:
# Convert the program from hexadecminal encoding to raw octet encoding
p = bytes([int(p[i : i + 2], 16) for i in range(0, len(p), 2)])
# List the profile
rc.append((int(s), int(m), p))
return rc
def parse_icc(content):
'''
Parse ICC profile from raw data
@param content:bytes The ICC profile data
@return :()→void Function to invoke, parameterless, to apply the ICC profile to the colour curves
'''
# Magic number for dual-byte precision lookup table based profiles
MLUT_TAG = 0x6d4c5554
# Magic number for gamma–brightness–contrast based profiles
# and for variable precision lookup table profiles
VCGT_TAG = 0x76636774
def fcurve(R_curve, G_curve, B_curve):
'''
Apply an ICC profile mapping
@param R_curve:list Lookup table for the red channel
@param G_curve:list Lookup table for the green channel
@param B_curve:list Lookup table for the blue channel
'''
for curve, icc in curves(R_curve, G_curve, B_curve):
for i in range(i_size):
# Nearest neighbour
y = int(curve[i] * (len(icc) - 1) + 0.5)
# Trunction to actual neighbour
y = min(max(0, y), len(icc) - 1)
# Apply mapping
curve[i] = icc[y]
# Integers in ICC profiles are encoded with the most significant byte first
int_ = lambda bs : sum([v << (i * 8) for i, v in enumerate(reversed(bs))])
def read(n):
'''
Read a set of bytes for the encoded ICC profile
@param n:int The number of bytes to read
@return :list The next `n` bytes of the profile
'''
if len(content) < n:
raise Exception('Premature end of file: %s' % pathname)
rc, content[:] = content[:n], content[n:]
return rc
# Convert profile encoding format for bytes to integer list
content = list(content)
# Skip the first 128 bytes
read(128)
# Get the number of bytes
n_tags, ptr = int_(read(4)), 128 + 4
# Create array for the lookup tables to creat
R_curve, G_curve, B_curve = [], [], []
for i_tag in range(n_tags):
# Get profile encoding type, offset to the profile and the encoding size of its data
(tag_name, tag_offset, tag_size), ptr = [int_(read(4)) for _ in range(3)], ptr + 3 * 4
# XXX should I not jump to the data now instead of inside the if statements' bodies?
if tag_name == MLUT_TAG:
## The profile is encododed as an dual-byte precision lookup table
# Jump to the profile data
read(tag_offset - ptr)
# Get the lookup table for the red channel,
for _ in range(256): R_curve.append(int_(read(2)) / 65535)
# for the green channel
for _ in range(256): G_curve.append(int_(read(2)) / 65535)
# and for the blue channel.
for _ in range(256): B_curve.append(int_(read(2)) / 65535)
return lambda : fcurve(R_curve, G_curve, B_curve)
elif tag_name == VCGT_TAG:
## The profile is encoded as with gamma, brightness and contrast values
# or as a variable precision lookup table profile
# Jump to the profile data
read(tag_offset - ptr)
# VCGT profiles starts where their magic number
tag_name = int_(read(4))
if not tag_name == VCGT_TAG:
break
# Skip four bytes
read(4)
# and get the actual encoding type
gamma_type = int_(read(4))
if gamma_type == 0:
## The profile is encoded as a variable precision lookup table
(n_channels, n_entries, entry_size) = [int_(read(2)) for _ in range(3)]
if tag_size == 1584:
(n_channels, n_entries, entry_size) = 3, 256, 2
if not n_channels == 3:
# Assuming sRGB, can only be an correct assumption if there are exactly three channels
break
# Calculate the divisor for mapping to [0, 1]
divisor = (256 ** entry_size) - 1
# Values are encoded in integer form with `entry_size` bytes
int__ = lambda : int_(read(entry_size)) / divisor
# Get the lookup table for the red channel,
for _ in range(n_entries): R_curve.append(int__())
# for the green channel
for _ in range(n_entries): G_curve.append(int__())
# and for the blue channel.
for _ in range(n_entries): B_curve.append(int__())
return lambda : fcurve(R_curve, G_curve, B_curve)
elif gamma_type == 1:
## The profile is encoded with gamma, brightness and contrast values
# Get the gamma, brightness and contrast for the red channel,
(r_gamma, r_min, r_max) = [int_(read(4)) / 65535 for _ in range(3)]
# green channel
(g_gamma, g_min, g_max) = [int_(read(4)) / 65535 for _ in range(3)]
# and blue channel.
(b_gamma, b_min, b_max) = [int_(read(4)) / 65535 for _ in range(3)]
def f():
'''
Apply the gamma, brightness and contrast
'''
# Apply gamma
gamma(r_gamma, g_gamma, b_gamma)
# before brightness and contrast
rgb_limits(r_min, r_max, g_min, g_max, b_min, b_max)
return f
break
# XXX should I not jump to (tag_offset + tag_size - ptr) here
# and not break the loops when unkown?
raise Exception('Unsupported ICC profile file')
def make_icc_interpolation(profiles):
'''
An interpolation function for ICC profiles
@param profiles:list<()→void> Profile applying functions
@return :(timepoint:float, alpha:float)→void() A function that applies an interpolation of the profiles,
it takes to arguments: the timepoint and the filter
alpha. The timepoint is normally a [0, 1] floating point
of the dayness level, this means that you only have two
ICC profiles, but you have multiple profiles, in such
case profile #⌊timepoint⌋ and profile #(⌊timepoint⌋ + 1)
(modulus the number of profiles) are interpolated with
(timepoint - ⌊timepoint⌋) weight to the second profile.
The filter alpha is a [0, 1] floating point of the degree
to which the profile should be applied.
'''
def f(t, a):
# Get floor and ceiling profiles and weight
(pro0, pro1), t = [profiles[(int(t) + 0) % len(profiles)] for i in range(2)], t % 1
if (pro0 is pro1) and (a == 1):
# If the floor and ceiling are the same profile,
# and the alpha is 1, than we can just simple apply
# one without any interpolation
pro0()
return
# But otherwise, we will need to save the current curves
r_, g_, b_ = r_curve[:], g_curve[:], b_curve[:]
# reset the curves
start_over()
# and apply on of the profiles
pro0()
# so that we can get the mapping of one of the profiles.
r0, g0, b0 = r_curve[:], g_curve[:], b_curve[:]
# After which we can get the last encoding value
n = len(r0) - 1
rgb = None
if pro0 is pro1:
# Now, if the floor and ceiling profiles are than same profile,
# then we can use just one of then interpolat between it and a clean adjustment.
rgb = [[v * a + i * (1 - a) / n for i, v in enumerate(c0)] for c0 in (r0, g0, b0)]
else:
# Otherwise we need to clear the curves from the floor profile's adjustments
start_over()
# and apply the ceiling profile
pro1()
# so that we can that profile's adjustments.
# Than we pair the floor and ceilings profile for each channel.
r01, g01, b01 = (r0, r_curve[:]), (g0, g_curve[:]), (b0, b_curve[:])
# Now that we have two profiles, when we interpolate between them and a clean
# state, we first interpolate the profiles and the interpolate between that
# interpolation and a clean adjustment.
interpol = lambda i, v0, v1 : (v0 * (1 - t) + v1 * t) * a + i * (1 - a) / n
rgb = [[interpol(i, v0, v1) for i, (v0, v1) in enumerate(zip(*c01))] for c01 in (r01, g01, b01)]
# Now that we have read the profiles, it is time to restore the curves to the
# state they were in,
r_curve[:], g_curve[:], b_curve[:] = r_, g_, b_
# and apply the interpolated profile adjustments on top of it.
for curve, icc in curves(*rgb):
for i in range(i_size):
# Nearest neighbour
y = int(curve[i] * (len(icc) - 1) + 0.5)
# Trunction to actual neighbour
y = min(max(0, y), len(icc) - 1)
# Apply mapping
curve[i] = icc[y]
return f