Displaying 1 to 20 from 51 results

neuralconvo - Neural conversational model in Torch

  •    Lua

This is an attempt at implementing Sequence to Sequence Learning with Neural Networks (seq2seq) and reproducing the results in A Neural Conversational Model (aka the Google chatbot). Human: What is the purpose of living? Machine: To live forever.

DIGITS - Deep Learning GPU Training System

  •    HTML

DIGITS (the Deep Learning GPU Training System) is a webapp for training deep learning models. The currently supported frameworks are: Caffe, Torch, and Tensorflow. Once you have installed DIGITS, visit docs/GettingStarted.md for an introductory walkthrough.

waifu2x - Image Super-Resolution for Anime-Style Art

  •    Lua

Image Super-Resolution for Anime-style art using Deep Convolutional Neural Networks. And it supports photo. The demo application can be found at http://waifu2x.udp.jp/ .

deep-learning-model-convertor - The convertor/conversion of deep learning models for different deep learning frameworks/softwares

  •    

Note: This is not one convertor for all frameworks, but a collection of different converters. Because github is an open source platform, I hope we can help each other here, gather everyone's strength. The sheet below is a overview of all convertors in github (not only contain official provided and more are user-self implementations). I just make a little work to collect these convertors. Also, hope everyone can support this project to help more people who're also crazy because of various frameworks.




AlphaPose - Multi-Person Pose Estimation System

  •    Jupyter

Alpha Pose is an accurate multi-person pose estimator, which is the first open-source system that achieves 70+ mAP (72.3 mAP) on COCO dataset and 80+ mAP (82.1 mAP) on MPII dataset. To match poses that correspond to the same person across frames, we also provide an efficient online pose tracker called Pose Flow. It is the first open-source online pose tracker that achieves both 60+ mAP (66.5 mAP) and 50+ MOTA (58.3 MOTA) on PoseTrack Challenge dataset. Note: Please read PoseFlow/README.md for details.

CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more

  •    Lua

This package includes CycleGAN, pix2pix, as well as other methods like BiGAN/ALI and Apple's paper S+U learning. The code was written by Jun-Yan Zhu and Taesung Park. Note: Please check out PyTorch implementation for CycleGAN and pix2pix. The PyTorch version is under active development and can produce results comparable or better than this Torch version.

OpenNMT - Open Source Neural Machine Translation in Torch

  •    Lua

OpenNMT is a full-featured, open-source (MIT) neural machine translation system utilizing the Torch mathematical toolkit. OpenNMT only requires a Torch installation with few dependencies.

hydrogen - :atom: Run code interactively, inspect data, and plot

  •    Javascript

Hydrogen is an interactive coding environment that supports Python, R, JavaScript and other Jupyter kernels. Checkout our Documentation and Medium blog post to see what you can do with Hydrogen.


texture_nets - Code for "Texture Networks: Feed-forward Synthesis of Textures and Stylized Images" paper

  •    Lua

In the paper Texture Networks: Feed-forward Synthesis of Textures and Stylized Images we describe a faster way to generate textures and stylize images. It requires learning a feedforward generator with a loss function proposed by Gatys et al.. When the model is trained, a texture sample or stylized image of any size can be generated instantly. Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis presents a better architectural design for the generator network. By switching batch_norm to Instance Norm we facilitate the learning process resulting in much better quality.

deepo - A series of Docker images (and their generator) that allows you to quickly set up your deep learning research environment

  •    Python

If you want to share your data and configurations between the host (your machine or VM) and the container in which you are using Deepo, use the -v option, e.g. This will make /host/data from the host visible as /data in the container, and /host/config as /config. Such isolation reduces the chances of your containerized experiments overwriting or using wrong data.

TorchCraft - Connecting Torch to StarCraft

  •    C++

A bridge between Torch and StarCraft. Synnaeve, G., Nardelli, N., Auvolat, A., Chintala, S., Lacroix, T., Lin, Z., Richoux, F. and Usunier, N., 2016. TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games - arXiv:1611.00625.

neural-vqa - :grey_question: Visual Question Answering in Torch

  •    Lua

This is an experimental Torch implementation of the VIS + LSTM visual question answering model from the paper Exploring Models and Data for Image Question Answering by Mengye Ren, Ryan Kiros & Richard Zemel. Download the MSCOCO train+val images and VQA data using sh data/download_data.sh. Extract all the downloaded zip files inside the data folder.

awesome-torch - A curated list of awesome Torch tutorials, projects and communities

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A curated list of awesome Torch tutorials, projects and communities. Codes and related articles. (#) means authors of code and paper are different.

DenseNet-Caffe - DenseNet Caffe Models, converted from https://github.com/liuzhuang13/DenseNet

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We manually converted the original torch models into caffe format from https://github.com/liuzhuang13/DenseNet. Update (July 27, 2017): for your convenience, we also provide a link to these models on Baidu Disk.

Activity-Recognition-with-CNN-and-RNN - Temporal Segments LSTM and Temporal-Inception for Activity Recognition

  •    Lua

In this work, we demonstrate a strong baseline two-stream ConvNet using ResNet-101. We use this baseline to thoroughly examine the use of both RNNs and Temporal-ConvNets for extracting spatiotemporal information. Building upon our experimental results, we then propose and investigate two different networks to further integrate spatiotemporal information: 1) temporal segment RNN and 2) Inception-style Temporal-ConvNet. Our analysis identifies specific limitations for each method that could form the basis of future work. Our experimental results on UCF101 and HMDB51 datasets achieve state-of-the-art performances, 94.1% and 69.0%, respectively, without requiring extensive temporal augmentation.

torch2coreml - Torch7 -> CoreML

  •    Python

This tool helps convert Torch7 models into Apple CoreML format which can then be run on Apple devices. If you want to run tests, you need MacOS High Sierra 10.13 installed.

fast-neural-doodle - Faster neural doodle

  •    Lua

This is my try on drawing with neural networks, which is faster than Alex J. Champandard's version, and similar in quality. This approach is based on neural artistic style method (L. Gatys), whereas Alex's version uses CNN+MRF approach of Chuan Li. It takes several minutes to redraw Renoir example using GPU and it will easily fit in 4GB GPUs. If you were able to work with Justin Johnson's code for artistic style then this code should work for you too.

react-native-torch - Torch (flashlight) plugin for React Native (Android/iOS)

  •    Java

A simple React Native plugin to switch a flashlight on/off.Currently supports both iOS (>= 8.0) and Android (all versions).

sketch_simplification - Models and code related to sketch simplification of rough sketches.

  •    Shell

Example result of a sketch simplification. Image copyrighted by Eisaku Kubonouchi (@EISAKUSAKU) and only non-commercial research usage is allowed. See our project page for more detailed information.