This project aims at visualize loss and other important metrics for analysis.

This project also implement an instance of neural-style, follows the idea of a keras example keras/examples/neural_style_transfer.py, but with a mostly different design.

Visualization is important and fun. It tells us what's going on.

• python 3
• keras
• tensorflow >= 0.9.0 / Theano
• h5py
• Pillow
• requests
• tornado

make sure you have the requirements above, or type this in your command line:

sudo pip install -r requirements.txt

if you want to use tensorflow as backend, follow the instruction to install tensorflow first

then

python neural_style.py

now you can see the neural style board in localhost:8000

For example, you may find an bad output

after comparing the loss, you will found negative correlation between style loss and content loss(against the assumption of neural-style):

so a very small picture may not be very suitable for neural-style task.

Here's a better result with nearly independent loss:

A very high learning rate:

You can stop your training at any time and continue at the last epoch.

You are free to adjust hyperparameter

Using TensorFlow as backend.

CPU: about 30 seconds/iter on Macbook Pro

GPU: about 0.3 s/iter on an K20