You've got a deep learning model, but you're not sure how to dress it up. That's where we come in! In this exercise, we'll take a plain Jane model and give it a makeover, just like a fashionista would.
Take a style transfer model and use SqueezeNet to add some flair to a bland image. But be warned, it's not just about looking good – it's about looking great!
Squeeze It!Use SqueezeNet to extract the style features from a reference image, then use them to style your model. Don't forget to add some flair with a little bit of noise!
Example Code:
from SqueezeNet import SqueezeNet
# Create a style transfer model
model = SqueezeNet(input_shape=(256, 256, 3), num_classes=10)
# Load the style features from the reference image
reference_image = load_image('reference_image.jpg')
# Extract the style features
style_features = model.extract_style(reference_image)
# Use the style features to style your model
model.style = style_features
# Train the model on your own data
model.fit(your_data)