ML-Utils

utils.py

import math
import matplotlib.pyplot as plt

def plot_grid_images(images, labels, columns=5, image_size=None, figsize=(8, 8), cmap='gray', title=None, file_name=None):
    fig = plt.figure(figsize=figsize)
    fig.tight_layout(h_pad=3)
    rows = math.ceil(len(images)/columns)
    for image, label, position in zip(images, labels, range(1, len(labels)+1)):
        fig.add_subplot(rows, columns, position)
        if image_size is not None:
            image = image.reshape(image_size)

        plt.imshow(image, cmap=cmap, interpolation='nearest')
        plt.axis('off')
        plt.title(label)
    if title is not None:
        fig.suptitle(title, fontsize=14)

    if file_name is not None:
        plt.savefig(file_name)
    plt.show()
    return file_name


def show_examples(generator, no_labels=False, title=None, class_indices_exist=True, no_images_to_show=9, columns=3):
    images_to_show = []
    images_labels = []
    images_shape = None
    
    if no_labels:
        for images in generator:
            images_shape = images.shape[1:]
            images_to_show.extend(images)
            if len(images_to_show) >= no_images_to_show:
                break
        images_labels = [None for _ in range(no_images_to_show)]
    else:
        if class_indices_exist:
            class_indices = {index: label for label, index in generator.class_indices.items()}
        
        for images, labels in generator:
            images_shape = images.shape[1:]
            images_to_show.extend(images)
            if not class_indices_exist:
                images_labels.extend(labels)
            else:
                images_labels.extend([class_indices[index] for index in labels])
            if len(images_to_show) >= no_images_to_show:
                break
    
    print('IMAGE SHAPE: ', images_shape)
    plot_grid_images(images_to_show[:no_images_to_show], images_labels[:no_images_to_show], title=title, columns=columns)