Tgbox-bench - Simple TGBOX upload speed benchmark

Related tags

Deep Learningtgbox-bench
Overview

TGBOX Benchmark

This script will benchmark upload speed to TGBOX storage.

Build

If you're on Linux

git clone https://github.com/NotStatilko/tgbox-bench
cd tgbox-bench & python3 -m pip install -r requirements.txt
./bench.py # Run benchmark, close all network apps before this

If you're on Windows

Simplest way is download executable from TGBOX Telegram channel, but you can build by yourself, see Linux guide.

Report

Please, send your results to me, they are anonymized, thank you.

You might also like...
Wind Speed Prediction using LSTMs in PyTorch
Wind Speed Prediction using LSTMs in PyTorch

Implementation of Deep-Forecast using PyTorch Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting Adapted from original implementation Setu

Onur Kaplan 151 Dec 14, 2022
Learning High-Speed Flight in the Wild
Learning High-Speed Flight in the Wild

Learning High-Speed Flight in the Wild This repo contains the code associated to the paper Learning Agile Flight in the Wild. For more information, pl

Robotics and Perception Group 391 Dec 29, 2022
Vehicle speed detection with python

Vehicle-speed-detection In the project simulate the tracker.py first then simulate the SpeedDetector.py. Finally, a new window pops up and the output

null 3 Dec 15, 2022
Examples of using f2py to get high-speed Fortran integrated with Python easily

f2py Examples Simple examples of using f2py to get high-speed Fortran integrated with Python easily. These examples are also useful to troubleshoot pr

Michael 35 Aug 21, 2022
The modify PyTorch version of Siam-trackers which are speed-up by TensorRT.

SiamTracker-with-TensorRT The modify PyTorch version of Siam-trackers which are speed-up by TensorRT or ONNX. [Updating...] Examples demonstrating how

null 9 Dec 13, 2022
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.

This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.

null 4 Aug 2, 2022
A complete, self-contained example for training ImageNet at state-of-the-art speed with FFCV

ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur

FFCV 92 Dec 31, 2022
This project implements "virtual speed" from heart rate monito

ANT+ Virtual Stride Based Speed and Distance Monitor Overview This project imple

null 2 May 20, 2022
SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging.
SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging.

SweiNet SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging. SweiNet takes as in

Felix Jin 3 Mar 31, 2022
Releases(v0.4)
Owner
Non
Non
GitHub Repository
[CVPR'21] Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration

Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration This repository contains the implementation of our paper Locally Aware Pi

sfwang 70 Dec 19, 2022
Implementation of CVPR 2021 paper "Spatially-invariant Style-codes Controlled Makeup Transfer"

SCGAN Implementation of CVPR 2021 paper "Spatially-invariant Style-codes Controlled Makeup Transfer" Prepare The pre-trained model is avaiable at http

118 Dec 12, 2022
The Agriculture Domain of ERPNext comes with features to record crops and land

Agriculture The Agriculture Domain of ERPNext comes with features to record crops and land, track plant, soil, water, weather analytics, and even trac

Frappe 21 Jan 02, 2023
Easy genetic ancestry predictions in Python

ezancestry Easily visualize your direct-to-consumer genetics next to 2500+ samples from the 1000 genomes project. Evaluate the performance of a custom

Kevin Arvai 38 Jan 02, 2023
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

943 Jan 07, 2023
This is the code repository for the paper "Identification of the Generalized Condorcet Winner in Multi-dueling Bandits" (NeurIPS 2021).

Code Repository for the Paper "Identification of the Generalized Condorcet Winner in Multi-dueling Bandits" (To appear in: Proceedings of NeurIPS20

1 Oct 03, 2022
[CVPR 2021] Scan2Cap: Context-aware Dense Captioning in RGB-D Scans

Scan2Cap: Context-aware Dense Captioning in RGB-D Scans Introduction We introduce the task of dense captioning in 3D scans from commodity RGB-D sensor

Dave Z. Chen 79 Nov 07, 2022
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19)

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19) Tianyu Wang*, Xin Yang*, Ke Xu, Shaozhe Chen, Qiang Zhang, Ry

Steve Wong 177 Dec 01, 2022
TResNet: High Performance GPU-Dedicated Architecture

TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I

426 Dec 28, 2022
Neural network chess engine trained on Gary Kasparov's games.

Neural Chess It's not the best chess engine, but it is a chess engine. Proof of concept neural network chess engine (feed-forward multi-layer perceptr

3 Jun 22, 2022
CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.

CausalNLP CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable. Install pip install -U

Arun S. Maiya 95 Jan 03, 2023
WeakVRD-Captioning - Implementation of paper Improving Image Captioning with Better Use of Caption

WeakVRD-Captioning - Implementation of paper Improving Image Captioning with Better Use of Caption

30 Oct 28, 2022
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Intelligent Robotics and Machine Vision Lab 4 Jul 19, 2022
A new test set for ImageNet

ImageNetV2 The ImageNetV2 dataset contains new test data for the ImageNet benchmark. This repository provides associated code for assembling and worki

186 Dec 18, 2022
PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE).

GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv

Big Data and Multi-modal Computing Group, CRIPAC 186 Dec 27, 2022
Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019)

Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019) Introduction Official implementation of Dynamic Multi-scale Filters for Semant

23 Oct 21, 2022
Code for "Learning Graph Cellular Automata"

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Daniele Grattarola 37 Oct 26, 2022
[CVPR 2022 Oral] MixFormer: End-to-End Tracking with Iterative Mixed Attention

MixFormer The official implementation of the CVPR 2022 paper MixFormer: End-to-End Tracking with Iterative Mixed Attention [Models and Raw results] (G

Multimedia Computing Group, Nanjing University 235 Jan 03, 2023
Leveraging Two Types of Global Graph for Sequential Fashion Recommendation, ICMR 2021

This is the repo for the paper: Leveraging Two Types of Global Graph for Sequential Fashion Recommendation Requirements OS: Ubuntu 16.04 or higher ver

Yujuan Ding 10 Oct 10, 2022
Differentiable rasterization applied to 3D model simplification tasks

nvdiffmodeling Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Automatic 3D Model

NVIDIA Research Projects 336 Dec 30, 2022