```python
import numpy as np
import tensorflow as tf
from paz import processors as pr
from paz.abstract import SequentialProcessor
from paz.backend.image import draw_box, resize_image
from paz.backend.camera import denormalize_box
from paz.processors import LoadImage, DecodeBoxes2D, DenormalizeBoxes2D

class PreprocessBoxes(SequentialProcessor):
    def __init__(self):
        super(PreprocessBoxes, self).__init__()
        self.add(pr.MatchBoxes())
        self.add(pr.EncodeBoxes())
        self.add(pr.ConvertClassToOneHotVector(num_classes=20))

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

class AugmentImage(SequentialProcessor):
    def __init__(self, size=(128, 128)):
        super(AugmentImage, self).__init__()
        self.add(pr.ResizeImage(size))
        self.add(pr.RandomBrightness(0.2))
        self.add(pr.RandomContrast(0.2, 0.5))
        self.add(pr.RandomSaturation(0.2, 0.5))
        self.add(pr.RandomHue(0.05))
        self.add(pr.BlendRandomCroppedBackground(0.3))

class AugmentBoxes(SequentialProcessor):
    def __init__(self):
        super(AugmentBoxes, self).__init__()
        self.add(pr.ConvertBoxesToImageBoxes())
        self.add(pr.ExpandBoxes(1.2))
        self.add(pr.RandomSampleCrop())
        self.add(pr.RandomFlipBoxes())

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

class ShowBoxes(SequentialProcessor):
    def __init__(self, size=(128, 128)):
        super(ShowBoxes, self).__init__()
        self.add(LoadImage())
        self.add(pr.ResizeImage(size))
        self.add(DecodeBoxes2D())
        self.add(DenormalizeBoxes2D())
        self.add(DrawBoxData2D())

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

def setup_gpu_memory_growth():
    gpus = tf.config.experimental.list_physical_devices('GPU')
    for gpu in gpus:
        tf.config.experimental.set_memory_growth(gpu, True)

def main():
    setup_gpu_memory_growth()
    model = ...  # Load your model here
    dataset = ...  # Load your dataset here

    augment_detection = AugmentDetection(training=True)
    show_boxes = ShowBoxes()

    for sample in dataset:
        augmented_sample = augment_detection(sample)
        show_boxes(augmented_sample)

if __name__ == '__main__':
    main()
```