Shitty DDoS Script With Python

This is a bad ddos tool script i made, there are tons of tools 100 times better but i’ll try to improve this and make it public here Just change Target Ip Port and choose the thread numbers Script 1 The first script just realizes the attack but there’s no way to know if it worked Script 2 This script realizes the attack and prints the amount of packets sent to the attacked Script 3 Script 2 but improved so […]

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CONFIDENT SEMANTIC RANKING LOSS FOR PART PARSING

If training from scratch, simply run. If not, customize the dir in /experiments/CSR config.py. @inproceedings{tan2021confident, title={Confident Semantic Ranking Loss for Part Parsing}, author={Tan, Xin and Xu, Jiachen and Ye, Zhou and Hao, Jinkun and Ma, Lizhuang}, booktitle={2021 IEEE International Conference on Multimedia and Expo (ICME)}, pages={1–6}, year={2021}, organization={IEEE} }    

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Aspect Sentiment Quad Prediction (ASQP)

We highly recommend you to install the specified version of the following packages to avoid unnecessary troubles: If the code is used in your research, please star our repo and cite our paper as follows: @inproceedings{zhang-etal-2021-aspect-sentiment, title = “Aspect Sentiment Quad Prediction as Paraphrase Generation”, author = “Zhang, Wenxuan and Deng, Yang and Li, Xin and Yuan, Yifei and Bing, Lidong and Lam, Wai”, booktitle =    

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Distributed Arcface Training in Pytorch

This is a deep learning library that makes face recognition efficient, and effective, which can train tens of millionsidentity on a single server. Requirements How to Training To train a model, run train.py with the path to the configs: 1. Single node, 8 GPUs: python -m torch.distributed.launch –nproc_per_node=8 –nnodes=1 –node_rank=0 –master_addr=”127.0.0.1″ –master_port=1234 train.py configs/ms1mv3_r50 2. Multiple nodes, each node 8 GPUs: Node 0: python -m torch.distributed.launch –nproc_per_node=8 –nnodes=2 –node_rank=0 –master_addr=

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Python Service for MISP Feed Management

Python Service for MISP Feed Management This set of scripts is designed to offer better reliability and more control over the fetching of feeds into MISP. For the moment, the schedule is broken up into multiple components, at the top of each plugin and in config.py: MISP_TIMES: An array of times (24hr format) when enabled MISP feeds will be fetched and cached. TEXT_TIMES: An array of times (24hr format) when enabled plaintext and CSV feeds will be fetched and cached. […]

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A Powerful HTML white space remover for Django

HTML Whitespace remover for Django Introduction : A powerful tool to optimize Django rendered templates Why use “django_stip_whitespace” ? Adds line break to InlineJS. It can automagically minify inline CSS, JS. Removes from HTML. It speeds up website by reducing the HTML size. Drop in replacement for django.gzip.GzipMiddleware. It compiles regex at runtime. So it’s blazing fast. Its mostly based on C ( gzip ) and Rust ( minify-html ) libraries. Significantly    

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Find out what commission you paid to the broker, how much money you earned with Ting

Сколько всего было внесено денег на счет Комиссию брокера Сумму денег на счету на данный момент Итоговый заработок Это скрипт для тех,кто столкнулся с проблемой подсчета уплаченой комиссии и подсчетом общей прибыли В личном кабинете Тинькофф банка получите токен Скачайте файл с кодом, замените YOUR TOKEN на ваш токен Запустите скрипт и получите данные GitHub View Github    

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Youtube Downloader by PyTube is a simple tool with a graphical interface and written in python

O que é o YouTube Downloader by PyTube? YouTube Downloader by PyTube é um software simples para baixar vídeos no YouTube com a qualidade máxima. YouTube Downloader by PyTube usa a bibliotecapytube, uma lib riquíssima cheia de recursos para baixar vídeos e áudio no YouTube. YouTube Downloader by PyTube não usa todos os recursos do pytube, apenas baixa vídeos no youtube com a qualidade máxima e também, caso o usuário tenha o wget, baixa a capa do vídeo…A interface gráfica […]

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A market neutral trading strategy enabling traders to profit from virtually any market conditions

A pairs trade relies on the fact that – if the correlation between two stocks is atleast 95% they follow a similar trend. But due to temporary market conditions like the announcement of results in a company or due to mishaps in another company, the stock direction of that company may deviate from the mean value. Given the striking similarities between the two banks used for this capstone, a change in the business environment of one bank, affects the paired […]

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