```python
import numpy as np
from paz import processors as pr
from paz.abstract import SequentialProcessor
from paz.processors import ResizeImage, DrawBoxes2D
from paz.backend.image import show_image

class PreprocessBoxes(SequentialProcessor):
    def __init__(self):
        super(PreprocessBoxes, self).__init__()
        self.add(pr.MatchBoxes())
        self.add(pr.EncodeBoxes())
        self.add(pr.ConvertClassToOneHot())

class PreprocessImage(SequentialProcessor):
    def __init__(self, size=(128, 128), mean=None, normalization=True):
        super(PreprocessImage, self).__init__()
        self.add(ResizeImage(size))
        if mean is not None:
            self.add(pr.SubtractMeanImage(mean))
        if normalization:
            self.add(pr.NormalizeImage())

class AugmentImage(SequentialProcessor):
    def __init__(self, size=(128, 128)):
        super(AugmentImage, self).__init__()
        self.add(ResizeImage(size))
        self.add(pr.RandomImageCrop())
        self.add(pr.RandomBrightness())
        self.add(pr.RandomContrast())
        self.add(pr.RandomSaturation())
        self.add(pr.RandomHue())

class AugmentBoxes(SequentialProcessor):
    def __init__(self):
        super(AugmentBoxes, self).__init__()
        self.add(pr.ToImageBoxCoordinates())
        self.add(pr.ExpandBoxes())
        self.add(pr.RandomSampleCrop())
        self.add(pr.RandomFlipBoxes())

class DrawBoxData2D(SequentialProcessor):
    def __init__(self):
        super(DrawBoxData2D, self).__init__()
        self.add(DrawBoxes2D())

class ShowBoxes(SequentialProcessor):
    def __init__(self, size=(128, 128)):
        super(ShowBoxes, self).__init__()
        self.add(ResizeImage(size))
        self.add(pr.DecodeBoxes())
        self.add(pr.DenormalizeBoxes())
        self.add(DrawBoxes2D())

class AugmentDetection(SequentialProcessor):
    def __init__(self, image_size=(128, 128), training=True):
        super(AugmentDetection, self).__init__()
        if training:
            self.add(AugmentImage(image_size))
            self.add(AugmentBoxes())
        self.add(PreprocessImage(image_size))
        self.add(PreprocessBoxes())

# Main section
if __name__ == "__main__":
    # Setup GPU memory growth (specific to TensorFlow)
    import tensorflow as tf
    gpus = tf.config.experimental.list_physical_devices('GPU')
    for gpu in gpus:
        tf.config.experimental.set_memory_growth(gpu, True)

    # Load model and data
    # model = load_model()  # Assuming a function to load a pre-trained model
    # data = load_data()  # Assuming a function to load data

    # Apply AugmentDetection and ShowBoxes processors to each sample in the dataset
    augment_detection = AugmentDetection()
    show_boxes = ShowBoxes()

    # for image, boxes in data:
    #     augmented_image, augmented_boxes = augment_detection(image, boxes)
    #     show_boxes(augmented_image, augmented_boxes)
```