将Numpy 3D数组转换为3个R、G、B十六进制字符串

Question

我有一个包含图片RGB值的大列表。我使用numpy创建图案和/或枕头来加载图片，并将它们转换为3D numpy数组(int32(。现在，我想以一种奇怪的方式将数组重组为十六进制字符串：此结构中R、G、B的三个十六进制字符串："0000FFFF"，其中前4个字符必须始终为零，然后2个字符表示像素n+1，最后2个字符代表像素n。我已经用一个代码做到了这一点，这个代码对于较大的图像来说太长了，我需要一些改进。到目前为止我得到的：

import numpy
import numpy.matlib
#from matplotlib.colors import rgb2hex
import time
def pairwise(iterable):
"""Create a paired-list from a list."""
a = iter(iterable)
return zip(a, a)
def test(imgSize=[480,640], brightness=[255,255,255]):

#generate pattern
startPattern = time.time()
patternDescription = 'Stripe Test'
pattern = numpy.zeros((imgSize[0], imgSize[1], 3))
line = (numpy.r_[:imgSize[1]]%255)/255
colorChR = numpy.matlib.repmat(line, imgSize[0], 1)
colorChG = numpy.matlib.repmat(line, imgSize[0], 1)
colorChB = numpy.matlib.repmat(line, imgSize[0], 1)
colorChR[:, :] = 0
colorChR[:, 0:60] = 1
colorChG[:, :] = 0
colorChG[:, 0:60] = 1
colorChB[:, :] = 0
colorChB[:, 0:60] = 1
pattern[:, :, 0] = colorChR
pattern[:, :, 1] = colorChG
pattern[:, :, 2] = colorChB
stopPattern = time.time()
print('TIME: Pattern generation:  ' + str(round(stopPattern-startPattern,3)) + ' s. ')
# first reshape
startReshape = time.time()
pattern[:, :, 0] = pattern[:, :, 0]*brightness[0] # red brightness multiplicator
pattern[:, :, 1] = pattern[:, :, 1]*brightness[1] # green brightness multiplicator
pattern[:, :, 2] = pattern[:, :, 2]*brightness[2] # blue brightness multiplicator

img = pattern.astype(int)

# IDEALLY I WANT TO CHANGE THE CODE ONLY FROM HERE ON

# redValues = pattern[:,:,0].astype(int)
# greenValues = pattern[:,:,1].astype(int)
# blueValues = pattern[:,:,2].astype(int)


#     test = ("0000" + ("{:0>2X}" * len(redValues))).format(*tuple(redValues[::-1]))

#     numpy.set_printoptions(formatter={'int':hex})

#     #test = [ rgb2hex(img[i,:]) for i in range(img.shape[0]) ]
#     rgb2hex = lambda r,g,b: '%02X%02X%02X' %(r,g,b)
#     test = [ rgb2hex(*img[i,:]) for i in range(img.shape[0]) ]
# #    img = numpy.array2string(img, formatter = {'int':lambda img: hex(img)})
imgReshape = numpy.reshape(img, (1, imgSize[0]*imgSize[1]*3)) #necessary?
redValues = imgReshape[0][0::3] #red values (0, 3, 6, ..)
greenValues = imgReshape[0][1::3] #green values (1, 4, 7, ..)
blueValues = imgReshape[0][2::3] #blue values (2, 5, 8, ..)
stopReshape = time.time()
print('TIME: Reshape into colors: ' + str(round(stopReshape-startReshape,3)) + ' s. ')


redString = ''
greenString = ''
blueString = ''
outData = dict()
startString = time.time()
for i, j in pairwise(redValues):
tempRed = "0000%02X%02X" % (int(j), int(i))
redString += tempRed

for i, j in pairwise(greenValues):
tempGreen = "0000%02X%02X" % (int(j), int(i))
greenString += tempGreen

for i, j in pairwise(blueValues):
tempBlue = "0000%02X%02X" % (int(j), int(i))
blueString += tempBlue
outData['red'] = redString
outData['green'] = greenString
outData['blue'] = blueString
stopString = time.time()
print('TIME: String formatting:   ' + str(round(stopString-startString, 3)) + ' s')
print('DATATEST: First 200 red chars: ' + str(outData['red'][0:200]))
print('DATATEST: First 200 green chars: ' + str(outData['green'][0:200]))
print('DATATEST: First 200 blue chars: ' + str(outData['blue'][0:200]))
#return outData

Answer 1

尝试使用numpy数组：

redValues = np.random.randint(0, 255, (10, 2))
red = np.array(redValues).reshape(-1, 2)
red_channel = (red[:, 1] << 8) + red[:, 0]
redString = ''.join(map(lambda val: f'0000{val:04x}', red_channel))