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
Official page of Struct-MDC (RA-L'22 with IROS'22 option); Depth completion from Visual-SLAM using point & line features

Struct-MDC (click the above buttons for redirection!) Official page of "Struct-MDC: Mesh-Refined Unsupervised Depth Completion Leveraging Structural R

Urban Robotics Lab. @ KAIST 37 Dec 22, 2022
A repository for benchmarking neural vocoders by their quality and speed.

License The majority of VocBench is licensed under CC-BY-NC, however portions of the project are available under separate license terms: Wavenet, Para

Meta Research 177 Dec 12, 2022
[ICML'21] Estimate the accuracy of the classifier in various environments through self-supervision

What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? [Paper] [ICML'21 Project] PyTorch Implementation T

24 Oct 26, 2022
Image Deblurring using Generative Adversarial Networks

DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo

Orest Kupyn 2.2k Jan 01, 2023
I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive constraining

I-SECRET This is the implementation of the MICCAI 2021 Paper "I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive con

13 Dec 02, 2022
Structural Constraints on Information Content in Human Brain States

Structural Constraints on Information Content in Human Brain States Code accompanying the paper "The information content of brain states is explained

Leon Weninger 3 Sep 07, 2022
Implementation of ToeplitzLDA for spatiotemporal stationary time series data.

Code for the ToeplitzLDA classifier proposed in here. The classifier conforms sklearn and can be used as a drop-in replacement for other LDA classifiers. For in-depth usage refer to the learning from

Jan Sosulski 5 Nov 07, 2022
YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931)

Introduction Yolov5-face is a real-time,high accuracy face detection. Performance Single Scale Inference on VGA resolution（max side is equal to 640 an

DeepCam Shenzhen 1.4k Jan 07, 2023
Age Progression/Regression by Conditional Adversarial Autoencoder

Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE) TensorFlow implementation of the algorithm in the paper Age Progression/Regre

Zhifei Zhang 603 Dec 22, 2022
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

Nils Thuerey 1.3k Jan 08, 2023
A highly efficient and modular implementation of Gaussian Processes in PyTorch

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

3k Jan 02, 2023
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters.

Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters. Overview This project is a Torch implementation for our CVPR 2016 paper

Jianwei Yang 278 Dec 25, 2022
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes

Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes [Paper] Method overview 4DMatch Benchmark 4DMatch is a benchmark for matc

103 Jan 06, 2023
Source code for Task-Aware Variational Adversarial Active Learning

Contrastive Coding for Active Learning under Class Distribution Mismatch Official PyTorch implementation of ["Contrastive Coding for Active Learning u

27 Nov 23, 2022
Computing Shapley values using VAEAC

Shapley values and the VAEAC method In this GitHub repository, we present the implementation of the VAEAC approach from our paper "Using Shapley Value

3 Nov 23, 2022
PyTorch implementation of Weak-shot Fine-grained Classification via Similarity Transfer

SimTrans-Weak-Shot-Classification This repository contains the official PyTorch implementation of the following paper: Weak-shot Fine-grained Classifi

BCMI 60 Dec 02, 2022
Temporal Knowledge Graph Reasoning Triggered by Memories

MTDM Temporal Knowledge Graph Reasoning Triggered by Memories To alleviate the time dependence, we propose a memory-triggered decision-making (MTDM) n

4 Sep 25, 2022
Best Practices on Recommendation Systems

Recommenders What's New (February 4, 2021) We have a new relase Recommenders 2021.2! It comes with lots of bug fixes, optimizations and 3 new algorith

Microsoft 14.8k Jan 03, 2023
Some methods for comparing network representations in deep learning and neuroscience.

Generalized Shape Metrics on Neural Representations In neuroscience and in deep learning, quantifying the (dis)similarity of neural representations ac

Alex Williams 45 Dec 27, 2022
Project page for our ICCV 2021 paper "The Way to my Heart is through Contrastive Learning"

The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video This is the official project page of our ICCV 2

36 Jan 06, 2023