CVNets: High Performance Library for Computer Vision

06/04/2022
by   Sachin Mehta, et al.
16

We introduce CVNets, a high-performance open-source library for training deep neural networks for visual recognition tasks, including classification, detection, and segmentation. CVNets supports image and video understanding tools, including data loading, data transformations, novel data sampling methods, and implementations of several standard networks with similar or better performance than previous studies. Our source code is available at: <https://github.com/apple/ml-cvnets>.

READ FULL TEXT

page 1

page 2

page 3

page 4

11/18/2021

PyTorchVideo: A Deep Learning Library for Video Understanding

We introduce PyTorchVideo, an open-source deep-learning library that pro...
03/19/2022

Volkit: A Performance-Portable Computer Vision Library for 3D Volumetric Data

We present volkit, an open source library with high performance implemen...
10/06/2021

Tribuo: Machine Learning with Provenance in Java

Machine Learning models are deployed across a wide range of industries, ...
05/04/2018

Manifold Geometry with Fast Automatic Derivatives and Coordinate Frame Semantics Checking in C++

Computer vision and robotics problems often require representation and e...
04/27/2020

GIMP-ML: Python Plugins for using Computer Vision Models in GIMP

This paper introduces GIMP-ML, a set of Python plugins for the widely po...
09/15/2020

A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation

This work studies the widely adopted ancestral sampling algorithms for a...
10/18/2021

SCENIC: A JAX Library for Computer Vision Research and Beyond

Scenic is an open-source JAX library with a focus on Transformer-based m...