flower.py

categories = np.sort(os.listdir(folder_dir))
fig, ax = plt.subplots(6,6, figsize=(25, 40))

for i in range(6):
    for j in range(6):
        k = int(np.random.random_sample() * len(X_test))
        if(categories[np.argmax(y_test[k])] == categories[np.argmax(model.predict(X_test)[k])]):
            ax[i,j].set_title("TRUE: " + categories[np.argmax(y_test[k])], color='green')
            ax[i,j].set_xlabel("PREDICTED: " + categories[np.argmax(model.predict(X_test)[k])], color='green')
            ax[i,j].imshow(np.array(X_test)[k].reshape(SIZE, SIZE, 3), cmap='gray')
        else:
            ax[i,j].set_title("TRUE: " + categories[np.argmax(y_test[k])], color='red')
            ax[i,j].set_xlabel("PREDICTED: " + categories[np.argmax(model.predict(X_test)[k])], color='red')
            ax[i,j].imshow(np.array(X_test)[k].reshape(SIZE, SIZE, 3), cmap='gray')