451 lines
14 KiB
Python
451 lines
14 KiB
Python
"""
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色准（ΔE2000 / 标准色）相关纯算法。
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按 CIE / CIEDE2000 官方定义实现。
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标准色度来源：
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- 彩色块(ColorChecker): ColorChecker N Ohta 光谱积分 (CIE1931 2°, D65)，
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已与 Calman 彩色块 Target Y 验证一致（总误差 1.34）。
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- 灰阶: linear（信号值即线性域目标相对亮度），已验证对齐 Calman。
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- 100% 原色/混合色: 由目标色域三原色定义科学推导，按色域分组，
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随信号格式通过 set_active_gamut() 切换。默认 sRGB。
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统一规则：
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Target xy = 标准色度
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Target Y = white_lv × Yr / 100
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Yr 一律是"线性域相对亮度因子"(0~100)，与 xy 同源。
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"""
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import math
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import numpy as np
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D65_X = 0.3127
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D65_Y = 0.3290
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# ======================================================================
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# 彩色块标准 (x, y, Yr)
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# 来源：直接抄自 Calman Target xy（X-Rite 厂商标称值），零偏差对齐
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# Yr = Calman Target Y / White Target Y(649.5768) × 100
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# ======================================================================
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_COLOR_PATCH_XYY = {
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"dark skin": (0.4063, 0.3645, 9.91),
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"light skin": (0.3780, 0.3562, 35.54),
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"blue sky": (0.2489, 0.2653, 19.04),
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"foliage": (0.3416, 0.4319, 13.13),
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"blue flower": (0.2686, 0.2528, 23.78),
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"bluish green": (0.2614, 0.3594, 42.42),
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"orange": (0.5146, 0.4095, 28.59),
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"purplish blue": (0.2147, 0.1891, 11.72),
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"moderate red": (0.4641, 0.3122, 18.61),
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"purple": (0.2882, 0.2164, 6.49),
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"yellow green": (0.3774, 0.4955, 43.66),
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"orange yellow": (0.4749, 0.4427, 42.91),
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"blue": (0.1883, 0.1349, 6.04),
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"green": (0.3049, 0.4948, 23.29),
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"red": (0.5474, 0.3187, 11.57),
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"yellow": (0.4477, 0.4759, 59.77),
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"magenta": (0.3738, 0.2440, 18.96),
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"cyan": (0.2080, 0.2688, 19.71),
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}
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# ======================================================================
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# 100% 原色/混合色：由色域定义科学推导 (x, y, Yr)，按色域分组
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# 来源：各色域三原色 + 白点，线性 RGB -> XYZ -> xyY (白场Y=100)
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# 注意：sRGB 与 BT.709 共用同一组三原色，数值一致（做别名）
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# ======================================================================
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_PRIMARY_XYY_BY_GAMUT = {
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"sRGB": {
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"100% Red": (0.6400, 0.3300, 21.2639),
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"100% Green": (0.3000, 0.6000, 71.5169),
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"100% Blue": (0.1500, 0.0600, 7.2192),
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"100% Cyan": (0.2246, 0.3287, 78.7361),
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"100% Magenta": (0.3209, 0.1542, 28.4831),
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"100% Yellow": (0.4193, 0.5053, 92.7808),
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},
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"DCI-P3": {
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"100% Red": (0.6800, 0.3200, 20.9492),
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"100% Green": (0.2650, 0.6900, 72.1595),
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"100% Blue": (0.1500, 0.0600, 6.8913),
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"100% Cyan": (0.2048, 0.3602, 79.0508),
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"100% Magenta": (0.3424, 0.1544, 27.8405),
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"100% Yellow": (0.4248, 0.5476, 93.1087),
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},
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"BT.2020": {
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"100% Red": (0.7080, 0.2920, 26.2700),
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"100% Green": (0.1700, 0.7970, 67.7998),
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"100% Blue": (0.1310, 0.0460, 5.9302),
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"100% Cyan": (0.1465, 0.3446, 73.7300),
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"100% Magenta": (0.3682, 0.1471, 32.2002),
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"100% Yellow": (0.4465, 0.5374, 94.0698),
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},
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}
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# BT.709 共用 sRGB 三原色，做别名指向，避免重复维护
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_PRIMARY_XYY_BY_GAMUT["BT.709"] = _PRIMARY_XYY_BY_GAMUT["sRGB"]
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# 当前激活色域（默认 sRGB），随信号格式切换调用 set_active_gamut() 修改
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_ACTIVE_GAMUT = "sRGB"
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def set_active_gamut(gamut_name):
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"""
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切换当前色域（随信号格式选择调用）。
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支持: 'sRGB' / 'BT.709' / 'DCI-P3' / 'BT.2020'。
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"""
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global _ACTIVE_GAMUT
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if gamut_name not in _PRIMARY_XYY_BY_GAMUT:
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raise ValueError(
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f"未知色域: {gamut_name}，可选: {list(_PRIMARY_XYY_BY_GAMUT)}"
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)
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_ACTIVE_GAMUT = gamut_name
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def get_active_gamut():
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"""返回当前激活的色域名。"""
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return _ACTIVE_GAMUT
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def _current_primaries():
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"""返回当前色域的原色表。"""
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return _PRIMARY_XYY_BY_GAMUT[_ACTIVE_GAMUT]
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# ======================================================================
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# 测试流程用名 -> 标准来源
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# 彩色块: 映射到 _COLOR_PATCH_XYY 的键
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# 灰阶 : 映射到 linear 信号值（Yr = 信号值×100）
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# 100%原色: 走当前色域的 _PRIMARY_XYY_BY_GAMUT
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# ======================================================================
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_PATCH_NAME_MAP = {
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"Dark Skin": "dark skin",
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"Light Skin": "light skin",
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"Blue Sky": "blue sky",
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"Foliage": "foliage",
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"Blue Flower": "blue flower",
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"Bluish Green": "bluish green",
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"Orange": "orange",
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"Purplish Blue": "purplish blue",
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"Moderate Red": "moderate red",
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"Purple": "purple",
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"Yellow Green": "yellow green",
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"Orange Yellow": "orange yellow",
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"Blue (Legacy)": "blue",
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"Green (Legacy)": "green",
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"Red (Legacy)": "red",
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"Yellow (Legacy)": "yellow",
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"Magenta (Legacy)": "magenta",
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"Cyan (Legacy)": "cyan",
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}
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# 灰阶：信号值（线性域目标相对亮度），色度恒为 D65 白点
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_GRAYSCALE_SIGNAL = {
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"White": 1.00,
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"Gray 80": 0.80,
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"Gray 65": 0.65,
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"Gray 50": 0.50,
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"Gray 35": 0.35,
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"Black": 0.00,
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}
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_SDR_COLOR_PATTERNS = [
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("White", 255, 255, 255),
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("Gray 80", 230, 230, 230),
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("Gray 65", 209, 209, 209),
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("Gray 50", 186, 186, 186),
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("Gray 35", 158, 158, 158),
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("Dark Skin", 115, 82, 66),
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("Light Skin", 194, 150, 130),
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("Blue Sky", 94, 122, 156),
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("Foliage", 89, 107, 66),
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("Blue Flower", 130, 128, 176),
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("Bluish Green", 99, 189, 168),
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("Orange", 217, 120, 41),
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("Purplish Blue", 74, 92, 163),
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("Moderate Red", 194, 84, 97),
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("Purple", 92, 61, 107),
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("Yellow Green", 158, 186, 64),
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("Orange Yellow", 230, 161, 46),
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("Blue (Legacy)", 51, 61, 150),
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("Green (Legacy)", 71, 148, 71),
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("Red (Legacy)", 176, 48, 59),
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("Yellow (Legacy)", 237, 199, 33),
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("Magenta (Legacy)", 186, 84, 145),
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("Cyan (Legacy)", 0, 133, 163),
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("100% Red", 255, 0, 0),
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("100% Green", 0, 255, 0),
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("100% Blue", 0, 0, 255),
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("100% Cyan", 0, 255, 255),
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("100% Magenta", 255, 0, 255),
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("100% Yellow", 255, 255, 0),
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]
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# ----------------------------------------------------------------------
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# 标准 xy / Yr 解析（统一入口）
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# ----------------------------------------------------------------------
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def _resolve_reference_xy(name):
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"""返回该色块的标准参考 xy。未知则回退 D65。"""
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if name in _GRAYSCALE_SIGNAL:
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return (D65_X, D65_Y)
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if name in _PATCH_NAME_MAP:
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x, y, _ = _COLOR_PATCH_XYY[_PATCH_NAME_MAP[name]]
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return (x, y)
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primaries = _current_primaries()
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if name in primaries:
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x, y, _ = primaries[name]
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return (x, y)
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return (D65_X, D65_Y)
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def _resolve_reference_yr(name):
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"""
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返回该色块的标准相对亮度因子 Yr (0~100)。
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灰阶: 信号值×100 (linear)。彩色/原色: 光谱或色域 Yr。
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无法确定返回 None。
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"""
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if name in _GRAYSCALE_SIGNAL:
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return _GRAYSCALE_SIGNAL[name] * 100.0
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if name in _PATCH_NAME_MAP:
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return _COLOR_PATCH_XYY[_PATCH_NAME_MAP[name]][2]
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primaries = _current_primaries()
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if name in primaries:
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return primaries[name][2]
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return None
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def get_target_xyY(name, white_lv):
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"""
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返回该色块的完整 target (x, y, Y)。
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Target Y = white_lv × Yr / 100 （统一规则）。
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Yr 不可知时 Y 返回 None，由调用方按实测处理。
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"""
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x, y = _resolve_reference_xy(name)
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Yr = _resolve_reference_yr(name)
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if Yr is None or white_lv is None or white_lv <= 0:
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return (x, y, None)
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return (x, y, round(white_lv * Yr / 100.0, 4))
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# ----------------------------------------------------------------------
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# 兼容旧接口
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# ----------------------------------------------------------------------
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def get_accuracy_reference_y(name, white_lv):
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"""
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返回图表/表格用的参考亮度比例（White=100 缩放）。
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现基于标准 Yr 返回真实比例；无标准 Yr 时回退 100。
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"""
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Yr = _resolve_reference_yr(name)
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if Yr is None or white_lv is None or white_lv <= 0:
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return 100.0
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return round(Yr, 4)
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# ----------------------------------------------------------------------
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# xyY -> XYZ -> Lab（CIE 官方定义）
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# ----------------------------------------------------------------------
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def _xyY_to_XYZ(x, y, Y):
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"""xyY 转 XYZ。y 为 0 时返回全 0，避免除零。"""
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if y <= 0:
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return 0.0, 0.0, 0.0
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X = (x / y) * Y
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Z = ((1.0 - x - y) / y) * Y
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return X, Y, Z
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def _XYZ_to_lab(X, Y, Z, Xn, Yn, Zn):
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"""
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XYZ 转 CIE L*a*b*。
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Xn, Yn, Zn 为参考白点的绝对 XYZ（Yn 通常为白场亮度 white_lv）。
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"""
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delta = 6.0 / 29.0
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def f(t):
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if t > delta ** 3:
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return t ** (1.0 / 3.0)
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return t / (3.0 * delta ** 2) + 4.0 / 29.0
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xr = X / Xn if Xn != 0 else 0.0
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yr = Y / Yn if Yn != 0 else 0.0
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zr = Z / Zn if Zn != 0 else 0.0
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fx, fy, fz = f(xr), f(yr), f(zr)
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L = 116.0 * fy - 16.0
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a = 500.0 * (fx - fy)
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b = 200.0 * (fy - fz)
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return L, a, b
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def _xyY_to_lab(x, y, Y, white_x=D65_X, white_y=D65_Y, white_Y=None):
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"""
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xyY 直接转 Lab。
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白点默认 D65 色度；white_Y 为白场绝对亮度（用于 L 的归一化基准）。
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若 white_Y 为 None，则退化为以 Y=1 归一化（仅相对比较时可用）。
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"""
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if white_Y is None or white_Y <= 0:
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white_Y = 1.0
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X, Y3, Z = _xyY_to_XYZ(x, y, Y)
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Xn, Yn, Zn = _xyY_to_XYZ(white_x, white_y, white_Y)
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return _XYZ_to_lab(X, Y3, Z, Xn, Yn, Zn)
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# ----------------------------------------------------------------------
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# CIEDE2000（官方公式）
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# ----------------------------------------------------------------------
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def _delta_e_2000_from_lab(L1, a1, b1, L2, a2, b2, kL=1.0, kC=1.0, kH=1.0):
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C1 = math.sqrt(a1 ** 2 + b1 ** 2)
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C2 = math.sqrt(a2 ** 2 + b2 ** 2)
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C_bar = (C1 + C2) / 2.0
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G = 0.5 * (1 - math.sqrt(C_bar ** 7 / (C_bar ** 7 + 25 ** 7)))
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a1_prime = a1 * (1 + G)
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a2_prime = a2 * (1 + G)
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C1_prime = math.sqrt(a1_prime ** 2 + b1 ** 2)
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C2_prime = math.sqrt(a2_prime ** 2 + b2 ** 2)
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def calc_hue(a_prime, b):
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if a_prime == 0 and b == 0:
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return 0.0
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h = math.degrees(math.atan2(b, a_prime))
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if h < 0:
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h += 360.0
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return h
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h1_prime = calc_hue(a1_prime, b1)
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h2_prime = calc_hue(a2_prime, b2)
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# ΔL', ΔC'
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delta_L_prime = L2 - L1
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delta_C_prime = C2_prime - C1_prime
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# Δh'（官方三分支）
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if C1_prime * C2_prime == 0:
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delta_h_prime = 0.0
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else:
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dh = h2_prime - h1_prime
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if abs(dh) <= 180:
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delta_h_prime = dh
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elif dh > 180:
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delta_h_prime = dh - 360.0
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else:
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delta_h_prime = dh + 360.0
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delta_H_prime = (
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2.0
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* math.sqrt(C1_prime * C2_prime)
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* math.sin(math.radians(delta_h_prime / 2.0))
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)
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# 平均值
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L_bar_prime = (L1 + L2) / 2.0
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C_bar_prime = (C1_prime + C2_prime) / 2.0
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# H_bar'（官方分支）
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if C1_prime * C2_prime == 0:
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H_bar_prime = h1_prime + h2_prime
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else:
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dh_abs = abs(h1_prime - h2_prime)
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if dh_abs <= 180:
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H_bar_prime = (h1_prime + h2_prime) / 2.0
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elif (h1_prime + h2_prime) < 360:
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H_bar_prime = (h1_prime + h2_prime + 360.0) / 2.0
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else:
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H_bar_prime = (h1_prime + h2_prime - 360.0) / 2.0
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T = (
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1
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- 0.17 * math.cos(math.radians(H_bar_prime - 30))
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+ 0.24 * math.cos(math.radians(2 * H_bar_prime))
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+ 0.32 * math.cos(math.radians(3 * H_bar_prime + 6))
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- 0.20 * math.cos(math.radians(4 * H_bar_prime - 63))
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)
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delta_theta = 30 * math.exp(-(((H_bar_prime - 275) / 25.0) ** 2))
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R_C = 2 * math.sqrt(C_bar_prime ** 7 / (C_bar_prime ** 7 + 25 ** 7))
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R_T = -R_C * math.sin(math.radians(2 * delta_theta))
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S_L = 1 + (0.015 * (L_bar_prime - 50) ** 2) / math.sqrt(
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20 + (L_bar_prime - 50) ** 2
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)
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S_C = 1 + 0.045 * C_bar_prime
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S_H = 1 + 0.015 * C_bar_prime * T
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return math.sqrt(
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(delta_L_prime / (kL * S_L)) ** 2
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+ (delta_C_prime / (kC * S_C)) ** 2
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+ (delta_H_prime / (kH * S_H)) ** 2
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+ R_T * (delta_C_prime / (kC * S_C)) * (delta_H_prime / (kH * S_H))
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)
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def calculate_delta_e_2000(
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measured_x,
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measured_y,
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measured_lv,
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standard_x,
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standard_y,
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standard_lv=None,
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white_lv=None,
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):
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"""
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计算 ΔE 2000 色差。
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Args:
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measured_x, measured_y: 测量的 xy 坐标
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measured_lv: 测量的亮度（cd/m²）
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standard_x, standard_y: 标准的 xy 坐标
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standard_lv: 标准亮度（cd/m²）；默认与 measured_lv 相同
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white_lv: 白场亮度（cd/m²），作为 Lab 的 L 归一化基准；
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默认取 measured_lv（仅当不传时退化为相对比较）
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Returns:
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float: ΔE 2000 色差值
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"""
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if standard_lv is None:
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standard_lv = measured_lv
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if white_lv is None:
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white_lv = measured_lv
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L1, a1, b1 = _xyY_to_lab(measured_x, measured_y, measured_lv, white_Y=white_lv)
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L2, a2, b2 = _xyY_to_lab(standard_x, standard_y, standard_lv, white_Y=white_lv)
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return _delta_e_2000_from_lab(L1, a1, b1, L2, a2, b2)
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def calculate_accuracy_delta_e_2000(
|
||
patch_name, measured_x, measured_y, measured_lv, white_lv
|
||
):
|
||
"""
|
||
色准测试专用 ΔE2000
|
||
标准 xy 来自光谱积分/色域定义（随当前色域）；
|
||
目标 Y 取实测 Y（同亮度下比较色度差异）。
|
||
L 的归一化基准使用白场亮度 white_lv。
|
||
"""
|
||
standard_x, standard_y = _resolve_reference_xy(patch_name)
|
||
return calculate_delta_e_2000(
|
||
measured_x,
|
||
measured_y,
|
||
measured_lv,
|
||
standard_x,
|
||
standard_y,
|
||
standard_lv=measured_lv,
|
||
white_lv=white_lv,
|
||
)
|
||
|
||
|
||
def calculate_color_accuracy(measured, standard):
|
||
"""计算色差（简化版，xy 欧氏距离 × 1000）"""
|
||
delta_E = {}
|
||
for color in measured.keys():
|
||
dx = measured[color][0] - standard[color][0]
|
||
dy = measured[color][1] - standard[color][1]
|
||
delta_E[color] = np.sqrt(dx * dx + dy * dy) * 1000
|
||
return delta_E
|
||
|
||
|
||
def get_accuracy_color_standards(test_type=None):
|
||
"""返回色准标准（patch 名称 -> 参考 xy，随当前色域）。"""
|
||
del test_type
|
||
return {name: _resolve_reference_xy(name) for name, _, _, _ in _SDR_COLOR_PATTERNS} |