Keras: Visualize ImageDataGenerator Output

Question

I would like to see what my ImageDataGenerator yields to my network.

Edit:
removed the channel_shift_range, accidently left it in the code

Generator

genNorm = ImageDataGenerator(rotation_range=10, width_shift_range=0.1, 
       height_shift_range=0.1, zoom_range=0.1, horizontal_flip=True)

Get Batches

batches = genNorm.flow_from_directory(path+'train', target_size=(224,224),
      class_mode='categorical', batch_size=64)

x_batch, y_batch = next(batches)

Plot Images

for i in range (0,32):
    image = x_batch[i]
    plt.imshow(image.transpose(2,1,0))
    plt.show()

Result

Generator Output

Is this normal or am I doing something wrong here?

Answer 1

The strange colors result from your channel shift. Do you really need that to augment your samples? Is a value of 10 (=very high) really what you want?

In addition to that: Another and likely more efficient way of checking what your generator yields is to set a directory with save_to_dir (parameter of flow/flow from directory function). In that you´ll find all the images that have been transformed and been delivered to your fit/flow function.

Edit:

You still somehow seem to invert your images during processing or while displaying them. I assume the original images look more like this:

Save the results of your ImageDataGenerator to a directory and compare these with the results that you see with plt.show.

Answer 2

Try this; change the generator as follow:

import numpy as np

def my_preprocessing_func(img):
    image = np.array(img)
    return image / 255

genNorm = ImageDataGenerator(rotation_range=10, width_shift_range=0.1, 
       height_shift_range=0.1, zoom_range=0.1, horizontal_flip=True, 
       preprocessing_function=my_preprocessing_func)

That worked for me,

Bruno