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ProGamerGov edited this page Nov 1, 2019 · 31 revisions

These are scripts which can be used to enhance neural-style-pt's capabilities.


neural_style_c.py

  • Implements -content_channels, -style_channels, -content_channel_mode, -style_channel_mode, and -specific_content_channels parameters. The content and style channel parameters let you pick how many channels you are going to strengthen or weaken. The channel model parameters let you choose between weakening channels, and strengthening channels. The specific content channels parameter lets you select specific content channels by their id, for strengthening or weakening.

  • Implements the features of neural_bestchannels.lua and more. More info on this script can be found here.


neural_style_labels.py

  • A modified version of neural_style.py that prints what it thinks the content image contains, and then what it thinks the image being stylized is.

  • Every time the loss values are printed to the terminal, what it thinks the current image being stylized is.

  • Label file is included in gist for default VGG-16, and VGG-19 models.


Multiscale-Resolution-Scripts

  • A set of multires/multiscale resolution scripts which can easily be used with neural-style-pt and neural-style.

Neural-Zoom

  • The successor to the original Neural-Zoom.

  • Neural-Zoom let's you create an "infinite zoom" effect with Neural-Style, and other style transfer projects.


pytorch-convis

  • A tool to visualize convolutional layer activations on an input image.

Neural-Tools

  • This project currently implements Scale Control, and Color Control (Luminance-Only style transfer, and color matching with histogram matching) in Neural-Style using external Python scripts. The external scripts allow for the features to be used on pretty much any other style transfer system.

  • The features come from the Controlling Perceptual Factors in Neural Style Transfer research paper.

  • The Neural-Tools wiki (includes extensive usage information and results for comparison with normal style transfer), can be found here.


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