preds.py

fig,axes = plt.subplots(5,5) 
fig.subplots_adjust(0,0,3,3)
for i in range(0,5,1):
    for j in range(0,5,1):
        num = random.randint(0,len(test_X)-1)
        display_image = test_X[num].squeeze(0)
        image = test_X[num]
        predicted_prob = model.predict(image)
        predicted_class = np.argmax(predicted_prob)
        ground_truth =classes[y_test.iloc[num]]
        axes[i,j].imshow(display_image)
        axes[i,j].imshow(display_image)
        if(classes[predicted_class] != classes[y_test.iloc[num]]):
            t = 'PREDICTED {} \n GROUND TRUTH[{}]'.format(classes[predicted_class], classes[y_test.iloc[num]])
            axes[i,j].set_title(t, fontdict={'color': 'darkred'})
        else:
            t = '[CORRECT] {}'.format(classes[predicted_class]) 
            axes[i,j].set_title(t)
        axes[i,j].axis('off')