A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

Related tags

Deep Learningrockpool
Overview

Rockpool

PyPI - Package Conda Documentation Status PyPI - Python Version Black - formatterDOI

Noodle

Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build networks, simulate, train and test them, deploy them either in simulation or on event-driven neuromorphic compute hardware. Rockpool provides layers with a number of simulation backends, including Brian2, NEST, Torch, JAX, Numba and raw numpy. Rockpool is designed to make machine learning based on SNNs easier. It is not designed for detailed simulation of biological networks.

Documentation and getting started

The best place to start with Rockpool is the documentation, which contains several tutorials and getting started guides.

The documentation is hosted online: https://rockpool.ai/

Installation instructions

Use pip to install Rockpool and required dependencies

$ pip install rockpool --user

The --user option installs the package only for the current user.

If you want to install all the extra dependencies required for Brian, PyTorch and Jax layers, use the command

$ pip install rockpool[all] --user

NEST-backed modules

The NEST simulator cannot be installed using pip. Please see the documentation for NEST at [https://nest-simulator.readthedocs.io/en/latest/] for instructions on how to get NEST running on your system.

License

Rockpool is released under a AGPL license. Commercial licenses are available on request.

Contributing

Fork the public repository at https://github.com/SynSense/rockpool, then clone your fork.

$ git clone https://github.com/your-fork-location/rockpool.git rockpool

Install the package in development mode using pip

$ cd rockpool
$ pip install -e . --user

or

$ pip install -e .[all] --user

The main branch is development. You should commit your modifications to a new feature branch.

$ git checkout -b feature/my-feature develop
...
$ git commit -m 'This is a verbose commit message.'

Then push your new branch to your repository

$ git push -u origin feature/my-feature

When you're finished with your modifications, make a merge request on github.com, from your branch in your fork to https://github.com/SynSense/rockpool.

Owner
SynSense
SynSense
The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier')

The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography

James 135 Dec 23, 2022
Dist2Dec: A Simplicial Neural Network for Homology Localization

Dist2Dec: A Simplicial Neural Network for Homology Localization

Alexandros Keros 6 Jun 12, 2022
Python Single Object Tracking Evaluation

pysot-toolkit The purpose of this repo is to provide evaluation API of Current Single Object Tracking Dataset, including VOT2016 VOT2018 VOT2018-LT OT

348 Dec 22, 2022
Code for "Localization with Sampling-Argmax", NeurIPS 2021

Localization with Sampling-Argmax [Paper] [arXiv] [Project Page] Localization with Sampling-Argmax Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-

JeffLi 71 Dec 17, 2022
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

Automatic, Readable, Reusable, Extendable Machin is a reinforcement library designed for pytorch. Build status Platform Status Linux Windows Supported

Iffi 348 Dec 24, 2022
Face recognition project by matching the features extracted using SIFT.

MV_FaceDetectionWithSIFT Face recognition project by matching the features extracted using SIFT. By : Aria Radmehr Professor : Ali Amiri Dependencies

Aria Radmehr 4 May 31, 2022
3D ResNets for Action Recognition (CVPR 2018)

3D ResNets for Action Recognition Update (2020/4/13) We published a paper on arXiv. Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara, and Yutaka Satoh,

Kensho Hara 3.5k Jan 06, 2023
Cognate Detection Repository

Cognate Detection Repository Details This repository contains the data for two publications: Challenge Dataset of Cognates and False Friend Pairs from

Diptesh Kanojia 1 Apr 26, 2022
Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21

CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different

Sunghwan Hong 120 Jan 04, 2023
Expressive Body Capture: 3D Hands, Face, and Body from a Single Image

Expressive Body Capture: 3D Hands, Face, and Body from a Single Image [Project Page] [Paper] [Supp. Mat.] Table of Contents License Description Fittin

Vassilis Choutas 1.3k Jan 07, 2023
The audio-video synchronization of MKV Container Format is exploited to achieve data hiding

The audio-video synchronization of MKV Container Format is exploited to achieve data hiding, where the hidden data can be utilized for various management purposes, including hyper-linking, annotation

Maxim Zaika 1 Nov 17, 2021
pytorch implementation for PointNet

PointNet.pytorch This repo is implementation for PointNet in pytorch. The model is in pointnet/model.py. It is teste

Fei Xia 1.7k Dec 30, 2022
Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering (NAACL 2021)

Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering Abstract In open-domain question answering (QA), retrieve-and-read mec

Clova AI Research 34 Apr 13, 2022
Official PyTorch implementation of "Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient".

Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient This repository is the official PyTorch implementation of "Edge Rewiring Go

Shanchao Yang 4 Dec 12, 2022
Code release of paper "Deep Multi-View Stereo gone wild"

Deep MVS gone wild Pytorch implementation of "Deep MVS gone wild" (Paper | website) This repository provides the code to reproduce the experiments of

François Darmon 53 Dec 24, 2022
Spiking Neural Network for Computer Vision using SpikingJelly framework and Pytorch-Lightning

Spiking Neural Network for Computer Vision using SpikingJelly framework and Pytorch-Lightning

Sami BARCHID 2 Oct 20, 2022
Run PowerShell command without invoking powershell.exe

PowerLessShell PowerLessShell rely on MSBuild.exe to remotely execute PowerShell scripts and commands without spawning powershell.exe. You can also ex

Mr.Un1k0d3r 1.2k Jan 03, 2023
A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano

yolov5-fire-smoke-detect-python A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano You can see

20 Dec 15, 2022
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

LexGLUE: A Benchmark Dataset for Legal Language Understanding in English ⚖️ 🏆 🧑‍🎓 👩‍⚖️ Dataset Summary Inspired by the recent widespread use of th

95 Dec 08, 2022
YolactEdge: Real-time Instance Segmentation on the Edge

YolactEdge, the first competitive instance segmentation approach that runs on small edge devices at real-time speeds. Specifically, YolactEdge runs at up to 30.8 FPS on a Jetson AGX Xavier (and 172.7

Haotian Liu 1.1k Jan 06, 2023