def make_cinema_picture_on_sRGB():
"""
1000nits と 108nits の Output Transform を当てた画像を
sRGB のガンマに載せ替えて普通のモニターで見られるようにする。
"""
# 作成済みの TestPattern に OutputTransform を適用
src_img_name = "./src_img/src_bt2020_to_ap0.exr"
ctl_108 = [OUTPUT_TRANS_P3D65_108NITS_CTL]
ctl_1000 = [OUTPUT_TRANS_BT2020_1000NITS_CTL]
ot_108_img = get_after_ctl_image(src_img_name, ctl_108)[:, :, :3]
ot_1000_img = get_after_ctl_image(src_img_name, ctl_1000)[:, :, :3]
# Linear に戻す
ot_108_img = tf.eotf_to_luminance(ot_108_img, tf.ST2084) / 108
ot_1000_img = tf.eotf_to_luminance(ot_1000_img, tf.ST2084) / 1000
# clipping
ot_108_img = np.clip(ot_108_img, 0.0, 1.0)
ot_1000_img = np.clip(ot_1000_img, 0.0, 1.0)
# sRGB がガンマに載せ替える
ot_108_img = tf.oetf(ot_108_img, tf.SRGB)
ot_1000_img = tf.oetf(ot_1000_img, tf.SRGB)
# 保存
cv2.imwrite("./108_sRGB.png", np.uint8(np.round(ot_108_img * 0xFF))[:, :, ::-1])
cv2.imwrite("./1000_sRGB.png", np.uint8(np.round(ot_1000_img * 0xFF))[:, :, ::-1])
def make_primary_value_on_ap0(oetf=tf.GAMMA24):
"""
各種カラースペースの RGB Primary値が
AP0 ではどの値になるかを計算する。
"""
cs_name_list = [cs.BT709, cs.P3_D65, cs.BT2020, cs.ACES_AP1, cs.ACES_AP0]
dst_cs = RGB_COLOURSPACES[cs.ACES_AP0]
src_primaries = [[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]
src_primaries = np.array(src_primaries)
dst_primaries = {}
for src_cs_name in cs_name_list:
src_cs = RGB_COLOURSPACES[src_cs_name]
chromatic_acaptation = "XYZ Scaling"
temp = RGB_to_RGB(src_primaries, src_cs, dst_cs, chromatic_acaptation)
if src_cs_name == cs.ACES_AP0:
cs_name = "ACES_AP0"
elif src_cs_name == cs.ACES_AP1:
cs_name = "ACES_AP1"
else:
cs_name = src_cs_name
temp = np.clip(temp, 0.0, 1.0)
dst_primaries[cs_name] = tf.oetf(temp, oetf)
return dst_primaries
def plot_log_stops():
# oetf_list = [tf.LOGC, tf.SLOG3, tf.DLOG, tf.FLOG, tf.NLOG]
oetf_list = [tf.LOGC, tf.SLOG3_REF]
ax1 = pu.plot_1_graph(fontsize=20,
figsize=(16, 10),
graph_title="Characteristics of the camera log",
graph_title_size=None,
xlabel="Exposure [stops].",
ylabel="10bit code value",
axis_label_size=None,
legend_size=19,
xlim=[-8, 8],
ylim=[0, 1024],
xtick=[x for x in range(-8, 9)],
ytick=[x * 128 for x in range(9)],
xtick_size=None,
ytick_size=None,
linewidth=3)
# centerd_spins(ax1)
for oetf_name in oetf_list:
x_max = tf.MAX_VALUE[oetf_name]
x = get_log_scale_x(sample_num=64, x_max=x_max, stops=20)
x2 = x / 0.20 if oetf_name == tf.SLOG3 else x / 0.18
y = tf.oetf(x / x_max, oetf_name) * 1023
ax1.plot(np.log2(x2), y, '-o', label=oetf_name)
# Plot A-Log
alog = ALOG_DATA
x = get_log_scale_x(sample_num=64, x_max=ALOG_MAX, stops=20)
x2 = x / 0.18
ax1.plot(np.log2(x2), alog, '-o', label="Astrodesign A-Log??")
plt.legend(loc='upper left')
plt.savefig('camera_logs.png', bbox_inches='tight', pad_inches=0.1)
plt.show()
def plot_from_white_to_primary_rgb_value(primary_color='green', step=5,
name=cs.BT709, oetf_name=tf.GAMMA24):
xy = calc_xy_from_white_to_primary_n_step(name=name, step=step,
color=primary_color)
linear_rgb = get_normalize_rgb_value_from_small_xy(xy, cs.ACES_AP1)
rgb = tf.oetf(linear_rgb, oetf_name)
plot_chromaticity_diagram(rate=480/755.0*2,
xmin=-0.1, xmax=0.8, ymin=-0.1, ymax=1.05,
test_scatter=(xy, rgb),
white_point=D65_WHITE)
def make_color_chekcer_value(cmfs_name=cm.CIE1931,
temperature=6500,
color_space=SRGB_CS,
oetf_name=tf.SRGB):
"""
color checker を OETF でエンコードしたRGB値を作る。
"""
linear_rgb = make_color_chekcer_linear_value(cmfs_name=cmfs_name,
temperature=temperature,
color_space=color_space)
encoded_rgb = tf.oetf(linear_rgb, oetf_name)
return encoded_rgb
def get_from_white_to_primary_rgb_value(primary_color='green', step=5,
name=cs.BT709, oetf_name=tf.GAMMA24):
"""
>>> get_from_white_to_primary_rgb_value(
>>> 'green', step=5, name=cs.BT709, oetf_name=tf.GAMMA24)
[[1023 1023 1023]
[ 792 1023 792]
[ 603 1023 603]
[ 416 1023 416]
[ 0 1023 0]]
"""
xy = calc_xy_from_white_to_primary_n_step(name=name, step=step,
color=primary_color)
linear_rgb = get_normalize_rgb_value_from_small_xy(xy)
rgb = np.int16(np.round(tf.oetf(linear_rgb, oetf_name) * 1023))
return rgb
def temperature_convert_test(cmfs_name=cm.CIE1931,
temperature=6500,
color_space=SRGB_CS,
oetf_name=tf.SRGB):
full_spectrum_rgb = make_color_chekcer_value(cmfs_name=cmfs_name,
temperature=temperature,
color_space=color_space,
oetf_name=oetf_name)
base_d65_rgb_linear = make_color_chekcer_linear_value(
cmfs_name=cmfs_name, temperature=6500, color_space=color_space)
temp_conv_rgb_linear = cm.temperature_convert(base_d65_rgb_linear,
6500,
temperature,
chromatic_adaptation='CAT02',
color_space=color_space)
temp_conv_rgb = tf.oetf(temp_conv_rgb_linear, oetf_name)
full_spectrum_rgb = np.uint8(np.round(full_spectrum_rgb * 0xFF))
temp_conv_rgb = np.uint8(np.round(temp_conv_rgb * 0xFF))
tpg.plot_color_checker_image(full_spectrum_rgb, temp_conv_rgb)
def get_color_checker_rgb_value(self):
"""
24パターンの Color Checker の RGB値を得る
"""
colour_checker_param = colour.COLOURCHECKERS.get('ColorChecker 2005')
# 今回の処理では必要ないデータもあるので xyY と whitepoint だけ抽出
# -------------------------------------------------------------
_name, data, whitepoint = colour_checker_param
temp_xyY = []
for key in data.keys():
temp_xyY.append(data[key])
temp_xyY = np.array(temp_xyY)
large_xyz = colour.models.xyY_to_XYZ(temp_xyY)
rgb_white_point\
= colour.colorimetry.ILLUMINANTS['cie_2_1931'][self.white_point]
illuminant_XYZ = whitepoint # ColorCheckerのオリジナルデータの白色点
illuminant_RGB = rgb_white_point # RGBの白色点を設定
chromatic_adaptation_transform = 'CAT02'
large_xyz_to_rgb_matrix\
= tpg.get_xyz_to_rgb_matrix(self.color_space.name)
# large_xyz_to_rgb_matrix = self.color_space.XYZ_to_RGB_matrix
rgb = colour.models.XYZ_to_RGB(large_xyz, illuminant_XYZ,
illuminant_RGB, large_xyz_to_rgb_matrix,
chromatic_adaptation_transform)
# overflow, underflow check
# -----------------------------
rgb[rgb < 0.0] = 0.0
rgb[rgb > 1.0] = 1.0
point_100nits = 100 / tf.PEAK_LUMINANCE[self.transfer_function]
rgb = tf.oetf(rgb * point_100nits, self.transfer_function)
rgb = np.uint16(np.round(rgb * self.img_max))
return rgb