PyTorch implementation of neural style transfer algorithm

Pytorch implementation from scratch of [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Huang+, ICCV2017]]

Pytorch implementation of Noisy Student Training for Automatic Speech Recognition and Automatic Pronunciation Error Detection problem

JavaMod Player

A simple and minimalistic implementation of the fast neural style transfer method presented in "Perceptual Losses for Real-Time Style Transfer and Super-Resolution" by Johnson et. al. (2016) 🏞

Neural Style Transfer (NST) refers to a class of software algorithms that manipulate digital images, or videos, in order to adopt the appearance or visual style of another image. NST algorithms are characterized by their use of deep neural networks for the sake of image transformation.

A bot for Telegram that can transfer style from one image to another

NST algorithm that manages images or videos, to transfer the visual style of another image.

This repository has AMX Mod X plugin for add new customizable weapons to Counter-Strike 1.6 game.

A simple and minimalistic PyTorch implementation of "A Neural Algorithm of Artistic Style" by Gatys et. al (2015) 🏞

Telegram Bot @stylizer_bot providing image style transfer using NST & CycleGAN

🎨 Implementation of Fast Neural Style Transfer proposed by Justin Johnson et al. in the paper Perceptual Losses for Real-Time Style Transfer and Super-Resolution

Algorithm practice exercises using OpenCV

SmartThings open-source DeviceTypeHandlers and SmartApps code

One of the curious outcome of data science revolution is neural style transfer where nst algorithm merge two images, content and style, creating a artistic image of content image. Here TensorFlow is used to process images and lastly used nst algorithm.

neural_style_transfer

Configuration tree for the Modderation modpack series

NST World of Color (Minecraft 1.12)

Artistic Image Generation Using Neural Style Transfer BE Project

Implement the neural style transfer algorithm to generate novel artistic images using foundational layers of CNNs (pooling, convolutions) and to stack them properly in a deep network to solve multi-class image classification problems. Creating digital art using Neural Network based Style Transfer.