Torch, TF, Lasagne code for audio style transfer.
http://dmitryulyanov.github.io/audio-texture-synthesis-and-style-transfer/
#dl #audio #styletransfer #torch #tf #lasagne
http://dmitryulyanov.github.io/audio-texture-synthesis-and-style-transfer/
#dl #audio #styletransfer #torch #tf #lasagne
Dmitry Ulyanov
Audio texture synthesis and style transfer
by Dmitry Ulyanov and Vadim Lebedev We present an extension of texture synthesis and style transfer method of Leon Gatys et al. for audio. We have developed the same code for three frameworks (well, it is cold in Moscow), choose your favorite: Torch TensorFlow…
Image-to-Image Translation in Tensorflow
http://affinelayer.com/pix2pix/index.html
#deeplearning #tf #dl
http://affinelayer.com/pix2pix/index.html
#deeplearning #tf #dl
Tensorflow: The Confusing Parts (1)
The tutorial for beginners by Jacob, Google AI Resident. This can be nice intro for those, who wanted to get familiar with #TF
This is thorough introduction to the concepts underlying Tensorflow’s API; such as nodes, graphs and sessions.
https://jacobbuckman.com/post/tensorflow-the-confusing-parts-1/?utm_source=telegram&utm_medium=opendatascience
#tensorflow #tutorial #novice #beginner
The tutorial for beginners by Jacob, Google AI Resident. This can be nice intro for those, who wanted to get familiar with #TF
This is thorough introduction to the concepts underlying Tensorflow’s API; such as nodes, graphs and sessions.
https://jacobbuckman.com/post/tensorflow-the-confusing-parts-1/?utm_source=telegram&utm_medium=opendatascience
#tensorflow #tutorial #novice #beginner
Face recognition is now available as a JS-package with the help of face-api.js. It is built on top of #Tensorflow (js version).
https://itnext.io/face-api-js-javascript-api-for-face-recognition-in-the-browser-with-tensorflow-js-bcc2a6c4cf07?gi=a277ad002e2a
#cv #js #tf #dl #cnn
https://itnext.io/face-api-js-javascript-api-for-face-recognition-in-the-browser-with-tensorflow-js-bcc2a6c4cf07?gi=a277ad002e2a
#cv #js #tf #dl #cnn
Medium
face-api.js — JavaScript API for Face Recognition in the Browser with tensorflow.js
A JavaScript API for Face Detection, Face Recognition and Face Landmark Detection
Fast image-to-image translation in the browser. With 3 trained models introduced. Plus a processed dataset of 1000 images for edges2cats translation.
Demo: https://zaidalyafeai.github.io/pix2pix/cats.html
Code: https://github.com/zaidalyafeai/zaidalyafeai.github.io/tree/master/pix2pix
#tf #tensorflow #tfjs #pix2pix #cv
Demo: https://zaidalyafeai.github.io/pix2pix/cats.html
Code: https://github.com/zaidalyafeai/zaidalyafeai.github.io/tree/master/pix2pix
#tf #tensorflow #tfjs #pix2pix #cv
🔥 Tensorflow 2.0 release
Faster
TPU support
TensorFlow datasets
Change log: https://medium.com/tensorflow/tensorflow-2-0-is-now-available-57d706c2a9ab
#google #tensorflow #dl #tf
Faster
TPU support
TensorFlow datasets
Change log: https://medium.com/tensorflow/tensorflow-2-0-is-now-available-57d706c2a9ab
#google #tensorflow #dl #tf
Medium
TensorFlow 2.0 is now available!
Earlier this year, we announced TensorFlow 2.0 in alpha at the TensorFlow Dev Summit. Today, we’re delighted to announce that the final…
Separate voice from music
Spleeter is the Deezer source separation library with pretrained models written in Python and uses Tensorflow. It makes it easy to train source separation model (assuming you have a dataset of isolated sources), and provides already trained state of the art model for performing various flavor of separation:
* vocals (singing voice) / accompaniment separation (2 stems)
* vocals / drums / bass / other separation (4 stems)
* vocals / drums / bass / piano / other separation (5 stems)
Spleeter is also very fast as it can perform separation of audio files to 4 stems 100x faster than real-time when run on a GPU
blog: https://deezer.io/releasing-spleeter-deezer-r-d-source-separation-engine-2b88985e797e
paper: http://archives.ismir.net/ismir2019/latebreaking/000036.pdf
github: https://github.com/deezer/spleeter
#voice #music #tf
Spleeter is the Deezer source separation library with pretrained models written in Python and uses Tensorflow. It makes it easy to train source separation model (assuming you have a dataset of isolated sources), and provides already trained state of the art model for performing various flavor of separation:
* vocals (singing voice) / accompaniment separation (2 stems)
* vocals / drums / bass / other separation (4 stems)
* vocals / drums / bass / piano / other separation (5 stems)
Spleeter is also very fast as it can perform separation of audio files to 4 stems 100x faster than real-time when run on a GPU
blog: https://deezer.io/releasing-spleeter-deezer-r-d-source-separation-engine-2b88985e797e
paper: http://archives.ismir.net/ismir2019/latebreaking/000036.pdf
github: https://github.com/deezer/spleeter
#voice #music #tf
With new TensorBoard.dev you can share your DL/ML experiments result at tensorBoard
Link: https://blog.tensorflow.org/2019/12/introducing-tensorboarddev-new-way-to.html
#DL #ML #tensorflow #tf
Link: https://blog.tensorflow.org/2019/12/introducing-tensorboarddev-new-way-to.html
#DL #ML #tensorflow #tf
blog.tensorflow.org
Introducing TensorBoard.dev: a new way to share your ML experiment results
The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.