This project implements "virtual speed" from heart rate monito

Related tags

Deep Learningvspeed
Overview

ANT+ Virtual Stride Based Speed and Distance Monitor

Overview

This project implements "virtual speed" from heart rate monitor. The calculated speed is broadcasted as such on ANT+ (using python-ant). Based on vpower by Darren Hague.

Even if the receiver app runs on the same computer, you will need two ANT+ sticks, because one device can't be used by two apps simultaneously.

Supported devices:

Warning: the Cycplus ANT Stick is not compatible, even though it uses the same Vendor ID and Product ID (0fcf:1008) as the ANTUSB2 Stick.

Running on Windows

  • Download the standalone executable
  • Install the libusb-win32 driver for the ANT+ device (if not already installed), it can be easily done using Zadig
    • Options - List All Devices
    • Select ANT+ stick
    • Select libusb-win32 driver and click Replace Driver
  • Run the downloaded executable

Running from source code (Windows, Linux, macOS)

  • Install Python 3 if not already installed
    • Check "Add Python to PATH" or use the full path in the commands below
  • Clone or download this repo
  • CD to the repo directory and run pip install -r requirements.txt
    • On Linux and macOS use pip3 instead of pip
  • [Optional] Run pip install pywin32 (Windows only, to stop the ANT node on terminal window close)
  • Run python vspeed.py (or double click vspeed.py if you installed the Python Launcher)
    • On Linux and macOS use python3 instead of python
You might also like...
AdamW optimizer and cosine learning rate annealing with restarts

AdamW optimizer and cosine learning rate annealing with restarts This repository contains an implementation of AdamW optimization algorithm and cosine

Maksym Pyrozhok 133 Dec 20, 2022
Jigsaw Rate Severity of Toxic Comments

Jigsaw Rate Severity of Toxic Comments

Guanshuo Xu 66 Nov 30, 2022
Model search is a framework that implements AutoML algorithms for model architecture search at scale
Model search is a framework that implements AutoML algorithms for model architecture search at scale

Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers speed up their exploration process for finding the right model architecture for their classification problems (i.e., DNNs with different types of layers).

Google 3.2k Dec 31, 2022
Implements Gradient Centralization and allows it to use as a Python package in TensorFlow
Implements Gradient Centralization and allows it to use as a Python package in TensorFlow

Gradient Centralization TensorFlow This Python package implements Gradient Centralization in TensorFlow, a simple and effective optimization technique

Rishit Dagli 101 Nov 1, 2022
Implements MLP-Mixer: An all-MLP Architecture for Vision.
Implements MLP-Mixer: An all-MLP Architecture for Vision.

MLP-Mixer-CIFAR10 This repository implements MLP-Mixer as proposed in MLP-Mixer: An all-MLP Architecture for Vision. The paper introduces an all MLP (

Sayak Paul 51 Jan 4, 2023
QueryFuzz implements a metamorphic testing approach to test Datalog engines.
QueryFuzz implements a metamorphic testing approach to test Datalog engines.

Datalog is a popular query language with applications in several domains. Like any complex piece of software, Datalog engines may contain bugs. The mo

null 34 Sep 10, 2022
This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of Coordinate Independent Convolutional Networks.
This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of Coordinate Independent Convolutional Networks.

Orientation independent Möbius CNNs This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of

Maurice Weiler 59 Dec 9, 2022
This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong Poisons
This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong Poisons

Adversarial poison generation and evaluation. This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong

null 31 Nov 1, 2022
Implements an infinite sum of poisson-weighted convolutions

An infinite sum of Poisson-weighted convolutions Kyle Cranmer, Aug 2018 If viewing on GitHub, this looks better with nbviewer: click here Consider a v

Kyle Cranmer 26 Dec 7, 2022
Owner
GitHub Repository
Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The original code is written in keras.

CasRel-pytorch-reimplement Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The o

longlongman 170 Dec 01, 2022
Boosting Adversarial Attacks with Enhanced Momentum (BMVC 2021)

EMI-FGSM This repository contains code to reproduce results from the paper: Boosting Adversarial Attacks with Enhanced Momentum (BMVC 2021) Xiaosen Wa

John Hopcroft Lab at HUST 10 Sep 26, 2022
NDE: Climate Modeling with Neural Diffusion Equation, ICDM'21

Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff

Jeehyun Hwang 5 Dec 18, 2022
[ICLR 2021] Is Attention Better Than Matrix Decomposition?

Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T

Gsunshine 271 Dec 29, 2022
Tool which allow you to detect and translate text.

Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr

Damian Panek 176 Nov 28, 2022
A library for uncertainty quantification based on PyTorch

Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation

TorchUQ 96 Dec 12, 2022
Code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction

Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,

stanley 152 Dec 16, 2022
Transformers are Graph Neural Networks!

🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article

Chaitanya Joshi 46 Jun 30, 2022
Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.

Population-Based Bandits (PB2) Code for the Population-Based Bandits (PB2) Algorithm, from the paper Provably Efficient Online Hyperparameter Optimiza

Jack Parker-Holder 22 Nov 16, 2022
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

AlphaZero-Gomoku This is an implementation of the AlphaZero algorithm for playing the simple board game Gomoku (also called Gobang or Five in a Row) f

Junxiao Song 2.8k Dec 26, 2022
Restricted Boltzmann Machines in Python.

How to Use First, initialize an RBM with the desired number of visible and hidden units. rbm = RBM(num_visible = 6, num_hidden = 2) Next, train the m

Edwin Chen 928 Dec 30, 2022
Machine learning library for fast and efficient Gaussian mixture models

This repository contains code which implements the Stochastic Gaussian Mixture Model (S-GMM) for event-based datasets Dependencies CMake Premake4 Blaz

Omar Oubari 1 Dec 19, 2022
Resources related to our paper "CLIN-X: pre-trained language models and a study on cross-task transfer for concept extraction in the clinical domain"

CLIN-X (CLIN-X-ES) & (CLIN-X-EN) This repository holds the companion code for the system reported in the paper: "CLIN-X: pre-trained language models a

Bosch Research 4 Dec 05, 2022
CVPR2021 Content-Aware GAN Compression

Content-Aware GAN Compression [ArXiv] Paper accepted to CVPR2021. @inproceedings{liu2021content, title = {Content-Aware GAN Compression}, auth

52 Nov 06, 2022
Multiband spectro-radiometric satellite image analysis with K-means cluster algorithm

Multi-band Spectro Radiomertric Image Analysis with K-means Cluster Algorithm Overview Multi-band Spectro Radiomertric images are images comprising of

Chibueze Henry 6 Mar 16, 2022
Global Filter Networks for Image Classification

Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch

Yongming Rao 273 Dec 26, 2022
Hierarchical Uniform Manifold Approximation and Projection

HUMAP Hierarchical Manifold Approximation and Projection (HUMAP) is a technique based on UMAP for hierarchical non-linear dimensionality reduction. HU

Wilson Estécio Marcílio Júnior 160 Jan 06, 2023
PECOS - Prediction for Enormous and Correlated Spaces

PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i

Amazon 387 Jan 04, 2023
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning

SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning This repository is the official implementation of "SHRIMP: Sparser Random Featur

Bobby Shi 0 Dec 16, 2021
EsViT: Efficient self-supervised Vision Transformers

Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect

Microsoft 352 Dec 25, 2022