 ```python
import paz
from paz import ProcessorA, GetHeatmapsAndTags, ToImageBoxCoordinates, box_coordinates, RandomFlipBoxesLeftRight
import numpy as np

# Image augmentation pipeline
image_transform_A = paz.ProcessorA()
image_transform_A.add_module(paz.RandomContrast())
image_transform_A.add_module(paz.RandomBrightness())
image_transform_A.add_module(paz.RandomSaturation())
image_transform_A.add_module(paz.RandomHue())

# Box augmentation pipeline
box_transform_A = paz.ProcessorA()
box_transform_A.add_module(ToImageBoxCoordinates())
box_transform_A.add_module(paz.ExpandBoxes())
box_transform_A.add_module(RandomFlipBoxesLeftRight())
box_transform_A.add_module(paz.RandomCropBoxes())

# Pipeline for drawing boxes
draw_boxes_processor = paz.ProcessorA()
draw_boxes_processor.add_module(paz.DrawBoxes())

# Pipeline for preprocessing boxes
preprocess_boxes_processor = paz.ProcessorA()
preprocess_boxes_processor.add_module(paz.MatchBoxesToDefaultBoxes())
preprocess_boxes_processor.add_module(paz.EncodeBoxes())
preprocess_boxes_processor.add_module(paz.ExpandClassLabel())

# Combine image and box augmentation pipelines
transform_A = paz.ProcessorA()
transform_A.add_module(image_transform_A)
transform_A.add_module(box_transform_A)

# Processor to put everything together
processor = paz.ProcessorA()
processor.add_module(transform_A)
processor.add_module(preprocess_boxes_processor)
processor.add_module(draw_boxes_processor)

# Generate sequence for processing batches of data
sequence = paz.Sequence()
sequence.add_module(processor)

# Download an image and perform augmentations
image = paz.data.download_image('https://example.com/image.jpg')
boxes = np.array([[10, 10, 100, 100, 1.0, 'class_label']])

# Perform augmentations
result = sequence.run(image, boxes)

# Display the augmented image and boxes
image_with_boxes = result['image_with_boxes']
heatmaps, tags = GetHeatmapsAndTags(image_with_boxes, result['boxes'])

# Display the image with boxes and heatmaps
# ...
```