def Get_Batch_Chrominance():
''''Convert every image in the batch to LAB Colorspace and normalize each value of it between [0,1]
Return:
AbColores_values array [batch_size,2224,224,2] 0-> A value, 1-> B value color
'''
global AbColores_values
global ColorImages_Batch
AbColores_values = np.empty((Batch_size,224,224,2),"float32")
for indx in range(Batch_size):
lab = color.rgb2lab(ColorImages_Batch[indx])
Min_valueA = np.amin(lab[:,:,1])
Max_valueA = np.amax(lab[:,:,1])
Min_valueB = np.amin(lab[:,:,2])
Max_valueB = np.amax(lab[:,:,2])
AbColores_values[indx,:,:,0] = Normalize(lab[:,:,1],-128,127)
AbColores_values[indx,:,:,1] = Normalize(lab[:,:,2],-128,127)
single_File_For_ColorizationModel_For_Not_OOP_Fan.py 文件源码
python
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