How can I perform advanced preprocessing in TensorFlow?

How can I perform advanced preprocessing in TensorFlow?

You can use the tf.data API for efficient data loading and preprocessing. What specific preprocessing techniques are you interested in?

I'm looking to implement data augmentation and normalization.

For data augmentation, you can use the tf.image module. For normalization, you can scale your images to a range of [0, 1] or standardize them. Would you like code examples?

Yes, please provide code examples for both.

Sure! Here's a simple example for data augmentation using tf.image:

import tensorflow as tf

# Load your dataset
image = tf.io.read_file('image.jpg')
image = tf.image.decode_jpeg(image)

# Data augmentation
image = tf.image.random_flip_left_right(image)
image = tf.image.random_brightness(image, max_delta=0.1)

And for normalization:

image = tf.cast(image, tf.float32) / 255.0  # Scale to [0, 1]

Let me know if you need more help!