278 Repositories
Python performance-bottleneck Libraries
Training PSPNet in Tensorflow. Reproduce the performance from the paper.
Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support
A higher performance pytorch implementation of DeepLab V3 Plus(DeepLab v3+)
A Higher Performance Pytorch Implementation of DeepLab V3 Plus Introduction This repo is an (re-)implementation of Encoder-Decoder with Atrous Separab
A high-performance DNS stub resolver for bulk lookups and reconnaissance (subdomain enumeration)
MassDNS A high-performance DNS stub resolver MassDNS is a simple high-performance DNS stub resolver targeting those who seek to resolve a massive amou
Dashboard to monitor the performance of your Binance Futures account
futuresboard A python based scraper and dashboard to monitor the performance of your Binance Futures account. Note: A local sqlite3 database config/fu
Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks.
Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks. Generally, we intergrete different kind of functional
Predict the latency time of the deep learning models
Deep Neural Network Prediction Step 1. Genernate random parameters and Run them sequentially : $ python3 collect_data.py -gp -ep -pp -pl pooling -num
The project covers common metrics for super-resolution performance evaluation.
Super-Resolution Performance Evaluation Code The project covers common metrics for super-resolution performance evaluation. Metrics support The script
An alternative serializer implementation for REST framework written in cython built for speed.
drf-turbo An alternative serializer implementation for REST framework written in cython built for speed. Free software: MIT license Documentation: htt
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model
A System Metrics Monitoring Tool Built using Python3 , rabbitmq,Grafana and InfluxDB. Setup using docker compose. Use to monitor system performance with graphical interface of grafana , storage of influxdb and message queuing of rabbitmq
SystemMonitoringRabbitMQGrafanaInflux This repository has code to setup a system monitoring tool The tools used are the follows Python3.6 Docker Rabbi
When in Doubt: Improving Classification Performance with Alternating Normalization
When in Doubt: Improving Classification Performance with Alternating Normalization Findings of EMNLP 2021 Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoa
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just
A modular, research-friendly framework for high-performance and inference of sequence models at many scales
T5X T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of
An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance"
Lidar-Segementation An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from
Official PyTorch Implementation for InfoSwap: Information Bottleneck Disentanglement for Identity Swapping
InfoSwap: Information Bottleneck Disentanglement for Identity Swapping Code usage Please check out the user manual page. Paper Gege Gao, Huaibo Huang,
A command line tool for visualizing CSV/spreadsheet-like data
PerfPlotter Read data from CSV files using pandas and generate interactive plots using bokeh, which can then be embedded into HTML pages and served by
A Factor Model for Persistence in Investment Manager Performance
Factor-Model-Manager-Performance A Factor Model for Persistence in Investment Manager Performance I apply methods and processes similar to those used
Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.
stock-graph-python Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.
Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at
State-of-the-art language models can match human performance on many tasks
Status: Archive (code is provided as-is, no updates expected) Grade School Math [Blog Post] [Paper] State-of-the-art language models can match human p
OneFlow is a performance-centered and open-source deep learning framework.
OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
An interactive tool with which to explore the possible imaging performance of candidate ngEHT architectures.
ngEHTexplorer An interactive tool with which to explore the possible imaging performance of candidate ngEHT architectures. Welcome! ngEHTexplorer is a
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.
AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance
Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.
Implementation of several Bayesian multi-target tracking algorithms, including Poisson multi-Bernoulli mixture filters for sets of targets and sets of trajectories. The repository also includes the GOSPA metric and a metric for sets of trajectories to evaluate performance.
This repository contains the Matlab implementations for the following multi-target filtering/tracking algorithms: - Folder PMBM contains the implemen
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning.
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
a discord libary that use to make discord bot with low efficiency and bad performance because I don't know how to manage the project
Aircord 🛩️ a discord libary that use to make discord bot with low efficiency and bad performance because I don't know how to manage the project Examp
High-fidelity performance metrics for generative models in PyTorch
High-fidelity performance metrics for generative models in PyTorch
Comparing Database performance with Django ORM
Comparing Database performance with Django ORM Postgresql MySQL MariaDB SQLite Comparing database operation performance using django ORM. PostgreSQL v
API with high performance to create a simple blog and Auth using OAuth2 ⛏
DogeAPI API with high performance built with FastAPI & SQLAlchemy, help to improve connection with your Backend Side to create a simple blog and Cruds
Dynamic Bottleneck for Robust Self-Supervised Exploration
Dynamic Bottleneck Introduction This is a TensorFlow based implementation for our paper on "Dynamic Bottleneck for Robust Self-Supervised Exploration"
Compares various time-series feature sets on computational performance, within-set structure, and between-set relationships.
feature-set-comp Compares various time-series feature sets on computational performance, within-set structure, and between-set relationships. Reposito
Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.
stock-graph-python Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
Developed a website to analyze and generate report of students based on the curriculum that represents student’s academic performance.
Developed a website to analyze and generate report of students based on the curriculum that represents student’s academic performance. We have developed the system such that, it will automatically parse data onto the database from excel file, which will in return reduce time consumption of analysis of data.
ticktock is a minimalist library to view Python time performance of Python code.
ticktock is a minimalist library to view Python time performance of Python code.
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 using a CNN-based orientation classifier')
Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021
Detecting Beneficial Feature Interactions for Recommender Systems (L0-SIGN) This is our implementation for the paper: Su, Y., Zhang, R., Erfani, S., &
Propose a principled and practically effective framework for unsupervised accuracy estimation and error detection tasks with theoretical analysis and state-of-the-art performance.
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles This project is for the paper: Detecting Errors and Estimating
An easy-to-use high-performance asynchronous web framework.
中文 | English 一个易用的高性能异步 web 框架。 Index.py 文档 Index.py 实现了 ASGI3 接口,并使用 Radix Tree 进行路由查找。是最快的 Python web 框架之一。一切特性都服务于快速开发高性能的 Web 服务。 大量正确的类型注释 灵活且高效的
EasyBuild is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.
EasyBuild is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.
GraPE is a Rust/Python library for high-performance Graph Processing and Embedding.
GraPE GraPE (Graph Processing and Embedding) is a fast graph processing and embedding library, designed to scale with big graphs and to run on both of
Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track (SIGIR 2021 Full Paper).
Optimizing Dense Retrieval Model Training with Hard Negatives Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma 🔥 News 2021-10
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Companion code for "Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees"
Companion code for "Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees" Installa
A data analysis using python and pandas to showcase trends in school performance.
A data analysis using python and pandas to showcase trends in school performance. A data analysis to showcase trends in school performance using Panda
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
High performance Python GLMs with all the features!
High performance Python GLMs with all the features!
High Performance Blockchain Deserializer
bitcoin_explorer is an efficient library for reading bitcoin-core binary blockchain file as a database (utilising multi-threading).
Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
guapow is an on-demand and auto performance optimizer for Linux applications.
guapow is an on-demand and auto performance optimizer for Linux applications. This project's name is an abbreviation for Guarana powder (Guaraná is a fruit from the Amazon rainforest with a highly caffeinated seed).
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API.
a high-performance, lightweight and human friendly serving engine for scrapy
a high-performance, lightweight and human friendly serving engine for scrapy
PerfSpect is a system performance characterization tool based on linux perf targeting Intel microarchitectures
PerfSpect PerfSpect is a system performance characterization tool based on linux perf targeting Intel microarchitectures. The tool has two parts perf
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models tabular data.
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
A self-supervised 3D representation learning framework named viewpoint bottleneck.
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In
Sampling profiler for Python programs
py-spy: Sampling profiler for Python programs py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spe
S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.
S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.
Sampling profiler for Python programs
py-spy: Sampling profiler for Python programs py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spe
A self-supervised 3D representation learning framework named viewpoint bottleneck.
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In
Django package to log request values such as device, IP address, user CPU time, system CPU time, No of queries, SQL time, no of cache calls, missing, setting data cache calls for a particular URL with a basic UI.
django-web-profiler's documentation: Introduction: django-web-profiler is a django profiling tool which logs, stores debug toolbar statistics and also
Code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition"
SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec
No effort, no worry, maximum performance.
Django Cachalot Caches your Django ORM queries and automatically invalidates them. Documentation: http://django-cachalot.readthedocs.io Table of Conte
A faster collectstatic command.
Collectfast A faster collectstatic command. Features Efficiently decide what files to upload using cached checksums Parallel file uploads Supported St
Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch
Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch
Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection
Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection
Alternative StdLib for Nim for Python targets
Alternative StdLib for Nim for Python targets, hijacks Python StdLib for Nim
A custom prime algorithm, implementation, and performance code & review
Colander A custom prime algorithm, implementation, and performance code & review Pseudocode Algorithm 1. given a number of primes to find, the followi
X-modaler is a versatile and high-performance codebase for cross-modal analytics.
X-modaler X-modaler is a versatile and high-performance codebase for cross-modal analytics. This codebase unifies comprehensive high-quality modules i
In this project we investigate the performance of the SetCon model on realistic video footage. Therefore, we implemented the model in PyTorch and tested the model on two example videos.
Contrastive Learning of Object Representations Supervisor: Prof. Dr. Gemma Roig Institutions: Goethe University CVAI - Computational Vision & Artifici
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
FedScale: Benchmarking Model and System Performance of Federated Learning
FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca
BoxInst: High-Performance Instance Segmentation with Box Annotations
Introduction This repository is the code that needs to be submitted for OpenMMLab Algorithm Ecological Challenge, the paper is BoxInst: High-Performan
LightSeq is a high performance training and inference library for sequence processing and generation implemented in CUDA
LightSeq: A High Performance Library for Sequence Processing and Generation
Full-text multi-table search application for Django. Easy to install and use, with good performance.
django-watson django-watson is a fast multi-model full-text search plugin for Django. It is easy to install and use, and provides high quality search
This is the pytorch implementation for the paper: *Learning Accurate Performance Predictors for Ultrafast Automated Model Compression*, which is in submission to TPAMI
SeerNet This is the pytorch implementation for the paper: Learning Accurate Performance Predictors for Ultrafast Automated Model Compression, which is
peace-performance (Rust) binding for python. To calculate star ratings and performance points for all osu! gamemodes
peace-performance-python Fast, To calculate star ratings and performance points for all osu! gamemodes peace-performance (Rust) binding for python bas
Use this script to track the gains of cryptocurrencies using historical data and display it on a super-imposed chart in order to find the highest performing cryptocurrencies historically
crypto-performance-tracker Use this script to track the gains of cryptocurrencies using historical data and display it on a super-imposed chart in ord
This is an online course where you can learn and master the skill of low-level performance analysis and tuning.
Performance Ninja Class This is an online course where you can learn to find and fix low-level performance issues, for example CPU cache misses and br
View your VALORANT performance in different areas of every map in the game!
Valorant-Zone-Stats Inspired by Leetify's awesome Map Zones Tool for CS:GO A simple desktop program to view your VALORANT performance in different are
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with ONNX, TensorRT, ncnn, and OpenVINO supported.
Introduction YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and ind
PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"
Transparency-by-Design networks (TbD-nets) This repository contains code for replicating the experiments and visualizations from the paper Transparenc
A high-performance anchor-free YOLO. Exceeding yolov3~v5 with ONNX, TensorRT, NCNN, and Openvino supported.
YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and industrial communities. For more details, please refer to our report on Arxiv.
Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
On the Bottleneck of Graph Neural Networks and its Practical Implications This is the official implementation of the paper: On the Bottleneck of Graph
Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track (SIGIR 2021 Full Paper).
Optimizing Dense Retrieval Model Training with Hard Negatives Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma This repo provi
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast
HyperPose is a library for building high-performance custom pose estimation applications.
HyperPose is a library for building high-performance custom pose estimation applications.
DFM: A Performance Baseline for Deep Feature Matching
DFM: A Performance Baseline for Deep Feature Matching Python (Pytorch) and Matlab (MatConvNet) implementations of our paper DFM: A Performance Baselin
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.
Flexible interface for high performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra. What is Lightning Tran
This is the antenna performance plotted from tinyGS reception data.
tinyGS-antenna-map This is the antenna performance plotted from tinyGS reception data. See their repository. The code produces a plot that provides Az
nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.
What is nnDetection? Simultaneous localisation and categorization of objects in medical images, also referred to as medical object detection, is of hi
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data
This repository is the official PyTorch implementation of Meta-Balance. Find the paper on arxiv MetaBalance: High-Performance Neural Networks for Clas
Performance data for WASM SIMD instructions.
WASM SIMD Data This repository contains code and data which can be used to generate a JSON file containing information about the WASM SIMD proposal. F
🔮 Execution time predictions for deep neural network training iterations across different GPUs.
Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's
SysInfo is an app developed in python which gives Basic System Info , and some detailed graphs of system performance .
SysInfo SysInfo is an app developed in python which gives Basic System Info , and some detailed graphs of system performance . Installation Download t
DownTime-Score is a Small project aimed to Monitor the performance and the availabillity of a variety of the Vital and Critical Moroccan Web Portals
DownTime-Score DownTime-Score is a Small project aimed to Monitor the performance and the availabillity of a variety of the Vital and Critical Morocca