Need to implement data augmentation technique about geotile HOT 1 CLOSED

import imgaug.augmenters as iaa
from imgaug.augmentables.segmaps import SegmentationMapsOnImage
import numpy as np

# Define augmentation pipeline
seq = iaa.Sequential([
    iaa.Fliplr(0.5),  # Horizontal flip
    iaa.Flipud(0.5),  # Vertical flip
    iaa.Affine(rotate=(-45, 45)),  # Random rotation between -45 and 45 degrees
    iaa.Affine(scale=(0.5, 1.5)),  # Random scaling between 0.5x and 1.5x
    iaa.Affine(translate_percent={"x": (-0.2, 0.2), "y": (-0.2, 0.2)}),  # Random translation
    # iaa.AdditiveGaussianNoise(scale=(0, 0.05*255)),  # Gaussian noise
    # iaa.ElasticTransformation(alpha=50, sigma=5)  # Elastic deformation
])

# Apply augmentation to images and masks
augmented_images, augmented_masks = seq(images=TRAIN_XX, segmentation_maps=TRAIN_YY)

augmented_images = []
augmented_masks = []

num_augmentations = 15 # total number of tiles will be: num_augmentations * number of features
# Apply augmentation to each original image and mask
for i in range(TRAIN_XX.shape[0]):
    image = TRAIN_XX[i]
    mask = TRAIN_YY[i]

    # Create a segmentation map object from the mask
    segmentation_map = SegmentationMapsOnImage(mask, shape=image.shape)

    # Apply augmentation num_augmentations times
    for _ in range(num_augmentations):
        # Apply the same augmentation to both image and mask
        augmented_image, augmented_segmentation_mask = seq.augment(image=image, segmentation_maps=segmentation_map)

        # Append the augmented image and mask to the lists
        augmented_images.append(augmented_image)
        augmented_masks.append(augmented_segmentation_mask.get_arr())

# Convert lists to numpy arrays
augmented_images = np.array(augmented_images)
augmented_masks = np.array(augmented_masks)

# append augmented images/masks with original images/masks
all_images = np.concatenate((TRAIN_XX, augmented_images), axis=0)
all_masks = np.concatenate((TRAIN_YY, augmented_masks), axis=0)