edmontdants Goto Github PK

fabrik

:factory: Collaboratively build, visualize, and design neural nets in browser

face-aging-caae

Age Progression/Regression by Conditional Adversarial Autoencoder

face-annotation-tool

Help you manually label facial landmarks.

face-vid2vid

face_srgan

Face generation from a given extremely low resolution images using DC_GAN.

faceforensics

Github of the FaceForensics dataset

faceit_live3

This is an update to faceit_live using first order model

faceswap

Deepfakes Software For All

falcon

Chrome extension for full text history search!

famos

Adversarial Framework for (non-) Parametric Image Stylisation Mosaics

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_down:

fashion-mnist-classifier-pytorch

fast-neural-style

Feedforward style transfer

fast-neural-style-1

pytorch implementation of fast-neural-style

fast-pixel-cnn

Speed up PixelCNN++ image generation by up to a 183 times

fast-rcnn

Fast R-CNN

fast-style-transfer

TensorFlow CNN for fast style transfer ⚡🖥🎨🖼

fast_multi_style_transfer-tensorflow

Multi style transfer. You can make Gogh + Manet + Picasso style image

fastai

The fastai deep learning library

fastbook

The fastai book, published as Jupyter Notebooks

faster_rcnn

Faster R-CNN

faster_rcnn_for_open_images_dataset_keras

Faster R-CNN for Open Images Dataset by Keras

fastmri

A large-scale dataset of both raw MRI measurements and clinical MRI images

fastphotostyle

Style transfer, deep learning, feature transform

fastsparse

Fastai+PyTorch implementation of sparse model training methods (SET, SNFS, RigL) + customize-your-own.

fauxtograph

Tools for using a variational auto-encoder for latent image encoding and generation.

fb.resnet.torch

Torch implementation of ResNet from http://arxiv.org/abs/1512.03385 and training scripts

fbnn

Facebook's extensions to torch/nn.

fbtt-embedding

This is a Tensor Train based compression library to compress sparse embedding tables used in large-scale machine learning models such as recommendation and natural language processing. We showed this library can reduce the total model size by up to 100x in Facebook’s open sourced DLRM model while achieving same model quality. Our implementation is faster than the state-of-the-art implementations. Existing the state-of-the-art library also decompresses the whole embedding tables on the fly therefore they do not provide memory reduction during runtime of the training. Our library decompresses only the requested rows therefore can provide 10,000 times memory footprint reduction per embedding table. The library also includes a software cache to store a portion of the entries in the table in decompressed format for faster lookup and process.

feathers

A framework for real-time applications and REST APIs with JavaScript and TypeScript