def lab2bgr(matrix):
"""convert numpy of lab colors to bgr colors"""
bgr_cols = []
for j in matrix:
bgr_col = []
for lab in j:
print(lab)
rgb = convert_color(lab, "LAB", "RGB", lab2rgb)
bgr = convert_color(rgb, "RGB", "BGR", rgb2bgr)
bgr_col.append(bgr)
bgr_cols.append(bgr_col)
return bgr_cols
def hsv_to_bgr(cols):
# convert numpy of hsv colors to bgr colors
bgr_cols = []
for j in cols:
bgr_col = []
for hsv in j:
h, s, v = hsv
rgb = convert_color((h,s*100,v*100), "HSV", "RGB", hsv2rgb)
bgr = convert_color(rgb, "RGB", "BGR", rgb2bgr)
bgr_col.append(bgr)
bgr_cols.append(bgr_col)
# len(bgr_cols[0]) 20 x 20
return bgr_cols
def get_bgr_lab_avg(data, label, col_rgb):
bgr_cols = []
lab_cols = []
for i in range(len(lst)):
avgcolcatrgb = np.mean(
[np.array(eval(n)) for n in data[col_rgb][data[label] == lst[i]]],
axis=0).tolist()
rgb = list(np.array(avgcolcatrgb).astype(int))
bgr = [
int(el / 255) for el in convert_color(rgb, "RGB", "BGR", rgb2bgr)
]
bgr_cols.append([np.round(l) for l in bgr])
lab = convert_color(np.array(avgcolcatrgb) / 255, "RGB", "LAB")
lab_cols.append([np.round(l) for l in list(lab)])
return bgr_cols, lab_cols
def get_rgb_hcl(lab):
lch_hue = []
lch = []
hcl = []
rgb = []
for el in lab:
lch_el = convert_color((el), "LAB", "LCH")
hcl.append(lch_el[::-1])
lch.append(lch_el)
lch_hue.append((lch_el[2]))
rgb_el = convert_color((el), "LAB", "RGB", lab2rgb)
r, g, b = rgb_el
rgb_el = r / 255, g / 255, b / 255
rgb.append(rgb_el)
return rgb, hcl
def plot_feature_label_color(data):
""" plot color name feature and basic color label
finding basic color's values by averaging
all color names belonging to that basic color"""
for color_id in range(len(data['srgb'])):
print(f'label: {color_id}')
plot_color(eval(data['srgb'].iloc[color_id]), 10)
basic_color = data['cat1'].iloc[color_id]
print(f'feature: {color_id}')
try:
plot_color(
eval(data['srgb'][data['name'] == basic_color].iloc[color_id]),
10)
except:
colsofcat = data['cielab'][data['cat1'] == basic_color]
len_colsofcat = len(colsofcat)
ls_ = []
as_ = []
bs_ = []
for i in range(len_colsofcat):
r = eval(colsofcat.iloc[i])[0]
ls_.append(r)
g = eval(colsofcat.iloc[i])[1]
as_.append(g)
b = eval(colsofcat.iloc[i])[2]
bs_.append(b)
la = int(mean(ls_))
aa = int(mean(as_))
ba = int(mean(bs_))
srgb = convert_color([la, aa, ba], "LAB", "RGB", lab2rgb)
plot_color(srgb, 10)
def print_hist_colors(lab, frequency):
labfreq = zip(lab, frequency)
labfreqslim = [el for el in list(labfreq) if el[-1] != 0]
for el in labfreqslim:
rgb_el = convert_color(el[0], "LAB", "RGB", lab2rgb)
square = np.full((10, 10, 3), rgb_el, dtype=np.uint8) / 255.0
plt.figure(figsize=(5, 2))
plt.imshow(square)
plt.axis('off')
plt.show()
def lch_to_bgr(cols):
# convert numpy of lch colors to bgr colors
bgr_cols = []
for j in cols:
bgr_col = []
for lch in j:
lab = lch2lab(lch)
bgr = convert_color(lab, "LAB", "BGR", lab2bgr)
bgr_col.append(bgr)
bgr_cols.append(bgr_col)
# len(bgr_cols[0]) 20 x 20
return bgr_cols
def make_rgb_hsv_colorwheel_colors():
""" Color Wheel 30°-steps in different color spaces """
# RGB-Colors
lst1 = [(255, 0, 0), (255, 128, 0), (255, 255, 0), (128, 255, 0),
(0, 255, 0), (0, 255, 128), (0, 255, 255), (0, 128, 255),
(0, 0, 255), (128, 0, 255), (255, 0, 255), (255, 0, 128)]
lst2 = []
lst3 = [
'red', 'orange', 'yellow', 'green-yellow', 'green', 'green-blue',
'cyan', 'blue-yellow', 'blue', 'purple', 'magenta', 'red-yellow'
]
# HSV-Colors
for i in range(len(lst1)):
lst2.append(convert_color(lst1[i], "RGB", "HSV", rgb2hsv))
df = pd.DataFrame()
df['RGB'] = lst1
df['HSV'] = lst2
df['name'] = lst3
return df
def get_palettecolvals(palette, depth, target_cs='hsv'):
""" convert palette's bgr colors into any color space values """
bgr_array = np.array(eval(palette.loc['bgr_colors'][depth]))
rgb_array = convert_array(bgr_array, origin='BGR', target='RGB')
lab_array = convert_array(np.array(rgb_array) / 255,
origin='RGB',
target='LAB')
if target_cs == 'rgb':
rgb_list = [list(i) for i in rgb_array]
return rgb_list
elif target_cs == 'hsv':
hsv_array = []
for i in rgb_array:
rgb = np.array(i)
rgbi = np.array([[rgb / 255]], dtype=np.float32)
hsv = cv2.cvtColor(rgbi, cv2.COLOR_RGB2HSV)
hsv = hsv[0, 0]
hsv_array.append(hsv)
hsv_list = [list(i) for i in hsv_array]
return hsv_list
elif target_cs == 'lab':
lab_array = []
for idn, rgb in enumerate(rgb_array):
rgb = np.array(rgb)
rgbi = np.array([[rgb / 255]], dtype=np.float32)
lab = cv2.cvtColor(rgbi, cv2.COLOR_RGB2LAB)
lab = lab[0, 0]
lab_array.append(lab)
lab_list = [i.tolist() for i in lab_array]
return lab_list
elif target_cs == 'lch':
lch_array = []
for idn, lab in enumerate(lab_array):
lch = convert_color(lab, "LAB", "LCH")
lch = np.array(lch)
lch_array.append(lch)
lch_list = [i.tolist() for i in lch_array]
return lch_list
def make_lab_lch_colorwheel_colors(lablch_twelve):
""" build pd frame with lab lch for 12 30°-step hues """
lst = []
lst2 = []
lst3 = []
lst4 = [
'fuchsia', 'red', 'terracotta', 'olive', 'kelly', 'leaf', 'teal',
'atoll', 'azure', 'blue', 'purple', 'lilac'
]
for i in lablch_twelve.items():
# {'LCH': i[0]}
lst.append(i[0])
lst2.append(i[1])
for i in range(len(lst2)):
lst3.append(convert_color(lst2[i], "RGB", "LAB", rgb2lab))
df = pd.DataFrame()
df['LCH'] = lst
df['Lab'] = lst2
df['RGB'] = lst3
df['name'] = lst4
return df
