Python Deep Learning Projects

Plotting the training – part 2

Let's define another function that plots the images generated during each epoch. To reflect the difference, we will also include the original and the masked/noised images in the plot.

The top row contains the original images, the middle row contains the masked images, and the bottom row contains the generated images.

The plot has 12 rows with the sequence, row 1 - original, row 2 - masked, row3 - generated, row 4 - original, row5 - masked,..., row 12 - generated.

Let's take a look at the code for the same:

def plot_generated_images_combined(original, noised_data, generator):    rows, cols = 4, 12    num = rows * cols    image_size = 28    generated_images = generator.predict(noised_data[0:num])     imgs = np.concatenate([original[0:num], ...