Acoustic mosquito detection code with Bayesian Neural Networks

Overview

HumBugDB

Acoustic mosquito detection with Bayesian Neural Networks.

General use instructions

This code is complementary to the paper: "HumBugDB: a large-scale acoustic mosquito dataset" and the dataset on Zenodo.

See documentation in the paper supplement for:

  • Section A: Licensing
  • Section B: Code use, feature and model engineering
  • Section C: Description and visualisations of metadata in data/metadata/*.csv

Additional documentation for:

Installation instructions

You may choose to use the Colab environment which is natively compatible with all of our code. Alternatively, see the instructions for manually configuring an environment to run the Jupyter notebooks.

Google Colab

  • Installation and use with Google Colab here.

Jupyter notebook

  • Installation instructions and requirements for PyTorch: InstallationLogPyTorch.txt.
  • Keras min. requirements: condarequirementsKeras.txt and piprequirementsKeras.txt. Compatible with Tensorflow 1.X and 2.X.

After installation of requirements:

  • git clone https://github.com/HumBug-Mosquito/HumBugDB.git
    
  • Extract audio from four-part-archive to Zenodo to /data/audio/.

Contact

Developed by Ivan Kiskin of MLRG University of Oxford. Contact [email protected] for enquiries or suggestions. Follow our Twitter on @OxHumBug and visit our HumBug website for updates on the overall HumBug project.

You might also like...
Bayesian Neural Networks in PyTorch

We present the new scheme to compute Monte Carlo estimator in Bayesian VI settings with almost no memory cost in GPU, regardles of the number of sampl

Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.
Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks

Complex-Valued Neural Networks (CVNN)Complex-Valued Neural Networks (CVNN)

Complex-Valued Neural Networks (CVNN) Done by @NEGU93 - J. Agustin Barrachina Using this library, the only difference with a Tensorflow code is that y

Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.

pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit

This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).

The Neural Process Family This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CN

Code for
Code for "Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks", CVPR 2021

Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks This repository contains the code that accompanies our CVPR 20

Supporting code for the paper
Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"

Dangers of Bayesian Model Averaging under Covariate Shift This repository contains the code to reproduce the experiments in the paper Dangers of Bayes

Companion code for the paper "An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence" (NeurIPS 2021)

ReLU-GP Residual (RGPR) This repository contains code for reproducing the following NeurIPS 2021 paper: @inproceedings{kristiadi2021infinite, title=

Code to go with the paper "Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo"

dblmahmc Code to go with the paper "Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo" Requirements: https://github.com

Releases(2.0)
Official repository for: Continuous Control With Ensemble DeepDeterministic Policy Gradients

Continuous Control With Ensemble Deep Deterministic Policy Gradients This repository is the official implementation of Continuous Control With Ensembl

4 Dec 06, 2021
Fight Recognition from Still Images in the Wild @ WACVW2022, Real-world Surveillance Workshop

Fight Detection from Still Images in the Wild Detecting fights from still images is an important task required to limit the distribution of social med

Şeymanur Aktı 10 Nov 09, 2022
iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis Andreas Bl

CompVis Heidelberg 36 Dec 25, 2022
Official implementation for TTT++: When Does Self-supervised Test-time Training Fail or Thrive

TTT++ This is an official implementation for TTT++: When Does Self-supervised Test-time Training Fail or Thrive? TL;DR: Online Feature Alignment + Str

VITA lab at EPFL 39 Dec 25, 2022
Pytorch implementation of VAEs for heterogeneous likelihoods.

Heterogeneous VAEs Beware: This repository is under construction 🛠️ Pytorch implementation of different VAE models to model heterogeneous data. Here,

Adrián Javaloy 35 Nov 29, 2022
IMBENS: class-imbalanced ensemble learning in Python.

IMBENS: class-imbalanced ensemble learning in Python. Links: [Documentation] [Gallery] [PyPI] [Changelog] [Source] [Download] [知乎/Zhihu] [中文README] [a

Zhining Liu 176 Jan 04, 2023
A Python wrapper for Google Tesseract

Python Tesseract Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and "read" the text embedded i

Matthias A Lee 4.6k Jan 05, 2023
A general, feasible, and extensible framework for classification tasks.

Pytorch Classification A general, feasible and extensible framework for 2D image classification. Features Easy to configure (model, hyperparameters) T

Eugene 26 Nov 22, 2022
SelfAugment extends MoCo to include automatic unsupervised augmentation selection.

SelfAugment extends MoCo to include automatic unsupervised augmentation selection. In addition, we've included the ability to pretrain on several new datasets and included a wandb integration.

Colorado Reed 24 Oct 26, 2022
Neural Cellular Automata + CLIP

🧠 Text-2-Cellular Automata Using Neural Cellular Automata + OpenAI CLIP (Work in progress) Examples Text Prompt: Cthulu is watching cthulu_is_watchin

Mainak Deb 21 Dec 19, 2022
This is our ARTS test set, an enriched test set to probe Aspect Robustness of ABSA.

This is the repository for our 2020 paper "Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis". Data We provide

35 Nov 16, 2022
IEEE Winter Conference on Applications of Computer Vision 2022 Accepted

SSKT(Accepted WACV2022) Concept map Dataset Image dataset CIFAR10 (torchvision) CIFAR100 (torchvision) STL10 (torchvision) Pascal VOC (torchvision) Im

1 Nov 17, 2022
Lenia - Mathematical Life Forms

For full version list, see Timeline in Lenia portal [2020-10-13] Update Python version with multi-kernel and multi-channel extensions (v3.4 LeniaNDK.p

Bert Chan 3.1k Dec 28, 2022
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021

AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Project Page | Video | Paper PyTorch implementation of automatic integration

Stanford Computational Imaging Lab 149 Dec 22, 2022
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).

NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti

Wonyong Jeong 15 Nov 21, 2022
Use evolutionary algorithms instead of gridsearch in scikit-learn

sklearn-deap Use evolutionary algorithms instead of gridsearch in scikit-learn. This allows you to reduce the time required to find the best parameter

rsteca 709 Jan 03, 2023
3D dataset of humans Manipulating Objects in-the-Wild (MOW)

MOW dataset [Website] This repository maintains our 3D dataset of humans Manipulating Objects in-the-Wild (MOW). The dataset contains 512 images in th

Zhe Cao 28 Nov 06, 2022
An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow implementation of SERank model. The code is developed based on TF-Ranking.

SERank An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow

Zhihu 44 Oct 20, 2022
Capture all information throughout your model's development in a reproducible way and tie results directly to the model code!

Rubicon Purpose Rubicon is a data science tool that captures and stores model training and execution information, like parameters and outcomes, in a r

Capital One 97 Jan 03, 2023
Simple tutorials on Pytorch DDP training

pytorch-distributed-training Distribute Dataparallel (DDP) Training on Pytorch Features Easy to study DDP training You can directly copy this code for

Ren Tianhe 188 Jan 06, 2023