Search Results for "separation"

Librosa is a powerful Python library for analyzing and processing audio and music signals. Built on top of NumPy, SciPy, and matplotlib, it provides a wide range of tools for feature extraction, time-series manipulation, audio display, and music information retrieval. Whether you're building machine learning models for audio classification or visualizing spectrograms, Librosa is a go-to library for researchers and developers working in audio signal processing.

Sherloq is a research-oriented toolkit designed for digital image forensics, providing an integrated environment to experiment with algorithms for image analysis and tampering detection. Rather than functioning as an automated decision-making system, it serves as a companion tool for researchers, enthusiasts, and students who want to explore forensic techniques from scientific literature and workshops. The project emphasizes transparency and community collaboration, contrasting with...

The PyTorch-based audio source separation toolkit for researchers. Pytorch-based audio source separation toolkit that enables fast experimentation on common datasets. It comes with a source code thats supports a large range of datasets and architectures, and a set of recipes to reproduce some important papers. Building blocks are thought and designed to be seamlessly plugged together.

Spleeter is the Deezer source separation library with pretrained models written in Python and using Tensorflow. It makes it easy to train music source separation models (assuming you have a dataset of isolated sources), and provides already trained state of the art models for performing various flavours of separation. 2 stems and 4 stems models have state of the art performances on the musdb dataset.