Python Uncertainty-metrics Resources

fast_bss_eval Do you have a zillion BSS audio files to process and it is taking days ? Is your simulation never ending ? Fear no more! fast_bss_eval i

Evaluation of Latent Space Disentanglement in the Presence of Interdependent Attributes Supplementary materials for ISMIR 2021 LBD submission: K. N. W

DEAR (Deep Evidential Action Recognition) Project | Paper & Supp Wentao Bao, Qi Yu, Yu Kong International Conference on Computer Vision (ICCV Oral), 2

PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)

GUPNet This is the official implementation of "Geometry Uncertainty Projection Network for Monocular 3D Object Detection". citation If you find our wo

blockprint This is a repository for discussion and development of tools for Ethereum block fingerprinting. The primary aim is to measure beacon chain

Website, Tutorials, and Docs    Uncertainty Toolbox A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualizatio

TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

Image Quality Evaluation Metrics Implementation of some common full reference image quality metrics. The repo is built based on full reference image q

Sync2Gen Code for ICCV 2021 paper: Scene Synthesis via Uncertainty-Driven Attribute Synchronization 0. Environment Environment: python 3.6 and cuda 10

EOW-Softmax This code is for the paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration". Accepted by ICCV21. Usage Commnd exa

Reformulation-Aware-Metrics Introduction This codebase contains source-code of the Python-based implementation of our CIKM 2021 paper. Chen, Jia, et a

Simple tool/toolkit for evaluating NLG (Natural Language Generation) offering various automated metrics. Jury offers a smooth and easy-to-use interface. It uses datasets for underlying metric computation, and hence adding custom metric is easy as adopting datasets.Metric.

iometrics Monitor and log Network and Disks statistics in MegaBytes per second. Install pip install iometrics Usage Pytorch-lightning integration from

Map Metrics for Trajectory Quality Map metrics toolkit provides a set of metrics to quantitatively evaluate trajectory quality via estimating consiste

A suite of utilities for AWS Lambda Functions that makes tracing with AWS X-Ray, structured logging and creating custom metrics asynchronously easier

OpenMEVA Contributed by Jian Guan, Zhexin Zhang. Thank Jiaxin Wen for DeBugging. OpenMEVA is a benchmark for evaluating open-ended story generation me

Epistemic Neural Networks A library for uncertainty representation and training in neural networks. Introduction Many applications in deep learning re

Fast k-NN graph construction for slow metrics

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

MonoRUn MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagation. CVPR 2021. [paper] Hansheng Chen, Yuyao Huang, Wei Tian*

UACANet: Uncertainty Aware Context Attention for Polyp Segmentation Official pytorch implementation of UACANet: Uncertainty Aware Context Attention fo

chia-monitor A monitoring tool to collect all important metrics from your Chia farming node and connected harvesters. It can send you push notificatio

ProSelfLC: CVPR 2021 ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks For any specific discussion or potential fu

Timbre Dissimilarity Metrics A collection of metrics for evaluating timbre dissimilarity using the TorchMetrics API Installation pip install -e . Usag

Deep Deterministic Uncertainty This repository contains the code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic

Aerial Depth Completion This work is described in the letter "Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation", by Lucas

UQ360 The Uncertainty Quantification 360 (UQ360) toolkit is an open-source Python package that provides a diverse set of algorithms to quantify uncert

Push metrics from your periodic long-running jobs to existing Prometheus/VictoriaMetrics monitoring system.

UQ360 The Uncertainty Quantification 360 (UQ360) toolkit is an open-source Python package that provides a diverse set of algorithms to quantify uncert

wide-minima-density-hypothesis Details about the wide minima density hypothesis and metrics to compute width of a minima This repo presents the wide m

whm also known as wifi-heat-mapper is a Python library for benchmarking Wi-Fi networks and gather useful metrics that can be converted into meaningful easy-to-understand heatmaps.

SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving Abstract In this paper, we introduce SalsaNext f

Inferring Spatial Uncertainty in Object Detection A teaser version of the code for the paper Labels Are Not Perfect: Inferring Spatial Uncertainty in

Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this

Evaluating the Factual Consistency of Abstractive Text Summarization Authors: Wojciech Kryściński, Bryan McCann, Caiming Xiong, and Richard Socher Int

Assessing Dialogue Systems with Distribution Distances [arXiv][code] We propose to measure the performance of a dialogue system by computing the distr

RecSim NG, a probabilistic platform for multi-agent recommender systems simulation. RecSimNG is a scalable, modular, differentiable simulator implemented in Edward2 and TensorFlow. It offers: a powerful, general probabilistic programming language for agent-behavior specification;

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

OCTIS : Optimizing and Comparing Topic Models is Simple! OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and compa

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.

Pandana Pandana is a Python library for network analysis that uses contraction hierarchies to calculate super-fast travel accessibility metrics and sh

Sensitivity Analysis Library (SALib) Python implementations of commonly used sensitivity analysis methods. Useful in systems modeling to calculate the

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

empyrical Common financial risk metrics. Table of Contents Installation Usage Support Contributing Testing Installation pip install empyrical Usage S

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking Ning Wang, Wengang Zhou, Jie Wang, and Houqiang Li Accepted by CVPR

onemetric Installation Install onemetric from PyPI (recommended): pip install onemetric Install onemetric from the GitHub source: git clone https://gi

Machine learning metrics for distributed, scalable PyTorch applications.

Gelato Bayesian dessert for Lasagne Recent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the be

Hera Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser. Setting up Step 1. Plant the spy Install the package pip

Basic Utilities for PyTorch Natural Language Processing (NLP) PyTorch-NLP, or torchnlp for short, is a library of basic utilities for PyTorch NLP. tor

Starlette Prometheus Introduction Prometheus integration for Starlette. Requirements Python 3.6+ Starlette 0.9+ Installation $ pip install starlette-p

Prometheus FastAPI Instrumentator A configurable and modular Prometheus Instrumentator for your FastAPI. Install prometheus-fastapi-instrumentator fro

Basic Utilities for PyTorch Natural Language Processing (NLP) PyTorch-NLP, or torchnlp for short, is a library of basic utilities for PyTorch NLP. tor

TL;DR Ignite is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Click on the image to

Starlette Prometheus Introduction Prometheus integration for Starlette. Requirements Python 3.6+ Starlette 0.9+ Installation $ pip install starlette-p

Prometheus FastAPI Instrumentator A configurable and modular Prometheus Instrumentator for your FastAPI. Install prometheus-fastapi-instrumentator fro

Diamond Diamond is a python daemon that collects system metrics and publishes them to Graphite (and others). It is capable of collecting cpu, memory,

pytest-play pytest-play is a codeless, generic, pluggable and extensible automation tool, not necessarily test automation only, based on the fantastic

Radon Radon is a Python tool that computes various metrics from the source code. Radon can compute: McCabe's complexity, i.e. cyclomatic complexity ra

Prometheus Python Client The official Python 2 and 3 client for Prometheus. Three Step Demo One: Install the client: pip install prometheus-client Tw

Starlette Prometheus Introduction Prometheus integration for Starlette. Requirements Python 3.6+ Starlette 0.9+ Installation $ pip install starlette-p

timing-asgi This is a timing middleware for ASGI, useful for automatic instrumentation of ASGI endpoints. This was developed at GRID for use with our

Prometheus Flask exporter This library provides HTTP request metrics to export into Prometheus. It can also track method invocations using convenient

ngxtop - real-time metrics for nginx server (and others) ngxtop parses your nginx access log and outputs useful, top-like, metrics of your nginx serve

Prometheus Python Client The official Python 2 and 3 client for Prometheus. Three Step Demo One: Install the client: pip install prometheus-client Tw

Basic Utilities for PyTorch Natural Language Processing (NLP) PyTorch-NLP, or torchnlp for short, is a library of basic utilities for PyTorch NLP. tor

Note: the current releases of this toolbox are a beta release, to test working with Haskell's, Python's, and R's code repositories. Metrics provides i