[Bug] ImageDataGenerator: nonsensical warning re channels

Fitting ImageDataGenerator insists on giving warning that channels should be in axis 1 (for Theano) or axis 3 (for Tensorflow), despite that being the case.

Reproducible code with MNIST data:

import os
os.environ["KERAS_BACKEND"] = "tensorflow"

from keras.datasets import mnist
from keras.preprocessing.image import ImageDataGenerator
from keras import backend as K
K.set_image_dim_ordering('tf')

K.image_data_format()   # 'channels_last'

(x_train, y_train), (x_test, y_test) = mnist.load_data() 
img_rows, img_cols = 28, 28

if K.image_data_format() == 'channels_first':
    x_train = x_train.reshape(x_train.shape[0], 1, img_rows, img_cols)
    x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols)
else:
    x_train = x_train.reshape(x_train.shape[0], img_rows, img_cols, 1)
    x_test = x_test.reshape(x_test.shape[0], img_rows, img_cols, 1)

x_train = x_train.astype('float32')
x_test = x_test.astype('float32')
x_train.shape # (60000, 28, 28, 1)

datagen = ImageDataGenerator()
datagen.fit(x_train)

Warning:

/var/venv/tsats/local/lib/python2.7/site-packages/keras/preprocessing/image.py:648: UserWarning: Expected input to be images (as Numpy array) following the data format convention "channels_last" (channels on axis 3), i.e. expected either 1, 3 or 4 channels on axis 3. However, it was passed an array with shape (60000, 28, 28, 1) (1 channels). ' (' + str(x.shape[self.channel_axis]) + ' channels).')

despite the fact that channels are indeed on axis 3 with an admissible value of 1.

Changing the backend to Theano and image ordering to th, so that data format is now channels_first and x_train.shape is (60000, 1, 28, 28), gives a similarly nonsensical warning:

/var/venv/tsats/local/lib/python2.7/site-packages/keras/preprocessing/image.py:648: UserWarning: Expected input to be images (as Numpy array) following the data format convention "channels_first" (channels on axis 1), i.e. expected either 1, 3 or 4 channels on axis 1. However, it was passed an array with shape (60000, 1, 28, 28) (1 channels). ' (' + str(x.shape[self.channel_axis]) + ' channels).')

Tested with

• Ubuntu 14.04
• Python 2.7.6
• Keras 2.0.5
• Theano 0.9.0
• Tensorflow 1.2.0

[jiayiliu]

Hi @dhingratul Thanks for the reply. I checked the source code, it seems that source code is wrong: line 646: if x.shape[self.channel_axis] not in {3, 4}:

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