def Load(cls, file_path, rescale_in_preprocessing=False):
training_data = numpy.load(file_path)
image_input = training_data['image_data']
if rescale_in_preprocessing:
for row in range(image_input.shape[0]):
image_input[row,
0, :, :] = ImagePreprocessor.RescaleImageInput(
image_input[row, 0, :, :])
else:
image_input = ImagePreprocessor.NormalizeImageInput(image_input)
ret = (image_input, training_data['chars'])
del training_data.f
training_data.close()
return ret
