genisplaja

genisplaja's Stars

• jlevy/the-art-of-command-line

  Master the command line, in one page

  154k2.8k25414.6k

• CMU-Perceptual-Computing-Lab/openpose

  OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

  Language:C++31.5k9242k7.9k

• lllyasviel/ControlNet

  Let us control diffusion models!

  Language:Python30.9k2195562.8k

• facebookresearch/audiocraft

  Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.

  Language:Python21.1k2103922.2k

• Olshansk/interview

  Everything you need to prepare for your technical interview

  17.8k782503.7k

• diff-usion/Awesome-Diffusion-Models

  A collection of resources and papers on Diffusion Models

  Language:HTML11.2k26848951

• lucidrains/musiclm-pytorch

  Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch

  Language:Python3.2k9853258

• haoheliu/AudioLDM

  AudioLDM: Generate speech, sound effects, music and beyond, with text.

  Language:Python2.5k42110225

• archinetai/audio-diffusion-pytorch

  Audio generation using diffusion models, in PyTorch.

  Language:Python2k4043168

• csteinmetz1/ai-audio-startups

  Community list of startups working with AI in audio and music technology

  1.6k695137

• marl/crepe

  CREPE: A Convolutional REpresentation for Pitch Estimation -- pre-trained model (ICASSP 2018)

  Language:Python1.1k3478160

• teticio/audio-diffusion

  Apply diffusion models using the new Hugging Face diffusers package to synthesize music instead of images.

  Language:Jupyter Notebook727174470

• lucidrains/BS-RoFormer

  Implementation of Band Split Roformer, SOTA Attention network for music source separation out of ByteDance AI Labs

  Language:Python443143016

• mir-dataset-loaders/mirdata

  Python library for working with Music Information Retrieval datasets

  Language:Python3661330959

• spotify/basic-pitch-ts

  A lightweight yet powerful audio-to-MIDI converter with pitch bend detection.

  Language:TypeScript24920923

• AakashKumarNain/diffusion_models

  All about the fundamentals and working of Diffusion Models

  Language:HTML153815

• gladia-research-group/multi-source-diffusion-models

  Language:Python151121112

• adobe-research/convmelspec

  Convmelspec: Convertible Melspectrograms via 1D Convolutions

  Language:Python13611510

• GuitarML/mldsp-papers

  Collection of papers related to neural nets/machine learning for audio DSP.

  130713

• archinetai/a-unet

  A toolbox that provides hackable building blocks for generic 1D/2D/3D UNets, in PyTorch.

  Language:Python84408

• caffeinism/FiLM-pytorch

  PyTorch implementation of FiLM: Visual Reasoning with a General Conditioning Layer

  Language:Python53218

• yoyololicon/spectrogram-inversion

  spectrogram inversion tools in PyTorch. Documentation: https://spectrogram-inversion.readthedocs.io

  Language:Python46227

• gusanthon/pywdf

  Wave digital filter elements and circuits in python

  Language:Python28243

• yoyololicon/duet-svs-diffusion

  Language:Python26110

• MTG/compIAM

  Common tools for the computational analysis of Indian Art Music

  Language:Jupyter Notebook217184

• leichtrhino/ChimeraNet

  Unofficial implementation of music separation model by Luo et.al.

  Language:Python13382

• magronp/spectrogram-inversion

  Spectrogram inversion algorithms for audio source separation, based on consistency, mixing, and magnitude constraints

  Language:Python11200

• MTG/IAM-tutorial-ismir22

  Webbook source code for ISMIR 2022 Tutorial: Computational Methods for Supporting Corpus-Based Research on Indian Art Music

  Language:Jupyter Notebook8521

• enricguso/UMX_loss_functions

  Open-Unmix - Music Source Separation for PyTorch

  Language:Python30

• thomasgnuttall/compIAM

  Centralized tools for the computational analysis of Indian Art Music

  Language:HTML2100