anasghrab Goto Github PK

followers: 14.0 following: 121.0 repos: 32.0 gists: 0.0

Name: Anas

Type: User

Company: CMAM - ISMS

Location: Tunis

Blog: https://anas.ghrab.tn

Anas's Projects

awesome-deep-learning-music

List of articles related to deep learning applied to music

datatext

ATTENTION : cette version n'est plus à jour, il faut se référer à celle de Gitlab.com

denoising-historical-recordings

A two-stage U-Net for high-fidelity denoising of historical recordings

diastema

This section OUTDATED as diastema in now a part of Music22.

django-rdf-io

Simple RDF serialiser/deserialiser to support synching a django model with an external triple-store

django-tailordev-biblio

:books: Bibliography management for your django projects.

essentia

C++ library of algorithms to extract features from audio files, including Python bindings.

gitlabhq

GitLab is version control for your server | Please open issues in our issue tracker on GitLab.com

The International Image Interoperability Framework (IIIF) Audio/Visual (A/V) Technical Specification Group aims to extend to A/V the benefits of interoperability and the growing ecosystem of clients and servers that IIIF provides for images. This repository contains user stories and mockups for interoperable A/V content – contributions are welcome.

jetson-inference

Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

jupyterhub

Multi-user server for Jupyter notebooks

lodel

Science publishing CMS

music22

This repository is OUTDATED. Please follow the link...

ofsite

openFrameworks web site

ofxatk

C++ Audio Tool Kit designed for openFrameworks

ofxopencvdnnobjectdetection

OpenCV based DNN Object Detection Library for Openframeworks

opencollective

Organizing the Internet Generation

openmiir

a public domain dataset of EEG recordings for music imagery information retrieval

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)