Dev tools · alternatives · 2026
24 alternatives to Fast Style Transfer in TensorFlow
TensorFlow CNN for fast style transfer ⚡🖥🎨🖼. Contribute to lengstrom/fast-style-transfer development by creating an account on GitHub.
Fast Style Transfer in TensorFlow is a tool that applies artistic styles to images and videos using neural networks. Developed as open-source software, it enables users to transform photos with the visual… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Fast Style Transfer in TensorFlow launched in 2016; newer entries below may have overtaken it.
- 1

Demo of in-browser Fast Neural Style Transfer with deeplearn.js library - reiinakano/fast-style-transfer-deeplearnjs
2017 · github.com · its alternatives →
- 2

Arbitrary style transfer using TensorFlow.js. Contribute to reiinakano/arbitrary-image-stylization-tfjs development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 3

- 4
TensorFlow 1.0▲823Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
- 5NN
Free to use online neural network photo to painting generator.
2015 · instapainting.com · its alternatives →
- 6

The best image-to-image style transfer
2024 · dzine.ai · its alternatives →
- 7

Contribute to matthew-sochor/transfer development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 8

- 9

First AI with high-quality images in user-uploaded style
2024 · its alternatives →
- 10

High-performance TensorFlow library for quantitative finance. - google/tf-quant-finance
2021 · github.com · its alternatives →
- 11

:satellite: Simple and ready-to-use tutorials for TensorFlow - GitHub - instillai/TensorFlow-Course: :satellite: Simple and ready-to-use tutorials for TensorFlow
2018 · github.com · its alternatives →
- 12

Neural Network to colorize grayscale images. Contribute to pavelgonchar/colornet development by creating an account on GitHub.
2016 · github.com · its alternatives →
- 13

CNN image style transfer 🎨. Contribute to gsurma/style_transfer development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 14

- 15II
2017 · affinelayer.com · its alternatives →
- 16

Simple and comprehensive tutorials in TensorFlow. Contribute to easy-tensorflow/easy-tensorflow development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 17

Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
- 18
Weights & Biases▲110Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
- 19AL
Hi HN - this is a little side project I threw together. Some implementation details: image processing is all done with headless GIMP (running inside a Docker container) through its built-in Python API. It's _very_ slow (about 50 seconds/image), and currently it processes exactly one image at a time. The website is built with NextJS; payments are processed by Stripe. I've had the best results with pictures of houses, although certain photos of people or nature can look neat, too. (For example: https://brushify.art/s/ruYmQWk, original photo from…
2022 · brushify.art · its alternatives →
- 20ID
2016 · jakebian.github.io · its alternatives →
- 21

2016 · github.com · its alternatives →
- 22

TensorFlow implementation for audio neural style. Contribute to DmitryUlyanov/neural-style-audio-tf development by creating an account on GitHub.
2016 · github.com · its alternatives →
- 23

- 24

Paint artistic patterns using random neural network
2016 · github.com · its alternatives →
Also compare
- Paint yourself in the style of classic art, in your browser alternatives
- Paint any photo in the style of any painting, directly in your browser alternatives
- Deep Style alternatives
- TensorFlow 1.0 alternatives
- Neural network turns photos into a specific style of painting alternatives
- AI Photo Filter by Stylar alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →