ASCII Art

A 3D engine powered by ASCII art

asciimare A 3D engine powered by ASCII art. asciimare uses ASCII characters to display 3D graphics directly in the terminal. It is powered by python curses, and renders by raycasting on voxels. asciimare utilizes the combination of 95 printable ASCII characters 8 ANSI colors in the terminal to emulate a variety of hues and brightness. It first analyzes a given font and generate a continous and uniform range of shades, e.g. Menlo.ttc ““““““““““““””””””’……——- -,,,,,______::::::::^^^^^!!~~~””””””;;;;;;rrrrr++++||()==>> >>lllll???iiiccv[]ttzzjj7*ff{{}ssYYTJJJ111unnnnyyyyIIFFFFFFF oooooowe22h3Zaa44XXX%%%555PPPP$$$mmGGAAUUUUbbbppKKK96O##H&&D [email protected]@@@@@@@@@@@@NNNNNNNNNNNN and then plays […]

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Transaction

Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions

In short, dataset makes reading and writing data in databases as simple as reading and writing JSON files. Read the docs To install dataset, fetch it with pip: Note: as of version 1.0, dataset is split into two packages, with the data export features now extracted into a stand-alone package, datafreeze. See the relevant repository here. GitHub https://github.com/pudo/dataset    

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Facebook NLP Research
NLP

Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN

Abstract Despite their failure to solve the compositional SCAN dataset, seq2seq architectures still achieve astonishing success on more practical tasks. This observation pushes us to question the usefulness of SCAN-style compositional generalization in realistic NLP tasks. In this work, we study the benefit that such compositionality brings about to several machine translation tasks. We present several focused modifications of Transformer that greatly improve generalization capabilities on SCAN and select one that remains on par with a vanilla Transformer on a […]

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Deep Learning

Deep learning models for remote sensing applications

Setting up a python environment Follow the instruction in https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.html for downloading and installing Miniconda Open a terminal in the code directory Create an environment using the .yml file: conda env create -f deepsatmodels_env.yml Activate the environment: source activate deepsatmodels Install required version of torch: conda install pytorch torchvision torchaudio cudatoolkit=10.1 -c pytorch-nightly Datasets MTLCC dataset (Germany) Download the dataset (.tfrecords) The data for Germany can be downloaded from: https://github.com/TUM-LMF/MTLCC clone the repository in a separate directory: git clone https://github.com/TUM-LMF/MTLCC […]

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Discord

Discord Token Finder with python

Find half of your target’s token with just their ID. Install 🔧 pip install -r requeriments.txt Usage 💻 Go to Discord Settings Advanced Enable Developer Mode When you right click on an user, the final option is “Copy ID”, click it and input it into Ttawi Notes 📝 If you see a bug, please open an issue. ☕    

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Scripts

Repositório contendo scripts Python que realizam a consulta de CPF e CNPJ diretamente no site da Receita Federal

Repositório contendo scripts Python que realizam a consulta de CPF e CNPJ diretamente no site da Receita Federal. Requerimentos Python 3.x instalado; Driver do navegador que será utilizado. Clique aqui para mais informações; Caminho do driver baixado adicionado ao PATH. Instalação Na pasta do repositório, execute o comando: pip install -r requirements.txt Alterações necessárias Para a execução, é necessário adaptar o código para o navegador que será utilizado. Por padrão o código utiliza o navegador Microsoft Edge. Modificar se necessário: […]

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Guide

Developer guide for Hivecoin project

Developer guide for Hivecoin project. Install Content are writen in reStructuredText (RST) and rendered with Sphinx. Much of the content displayed on the is converted from Markdown toreStructuredText (RST) and renderedwith Sphinx. Render the documentation locally To render the documentation locally you first need to install Sphinx and therequired theme modules, e.g. by running pip install -r requirements.txt This should be done from the root of this repo. Then you can execute Sphinx by calling This will generate HTML from […]

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PyTorch

SSD-based Object Detection in PyTorch

서강대학교 현대모비스 SW 프로그램에서 진행한 인공지능 프로젝트입니다. Jetson nano를 이용해 pre-trained network를 fine tuning시켜 차량 및 신호등 인식을 구현하였습니다. https://www.youtube.com/watch?v=jYsIBuAgdao This repo implements SSD (Single Shot MultiBox Detector) in PyTorch for object detection, using MobileNet backbones. It also has out-of-box support for retraining on Google Open Images dataset. For documentation, please refer to Object Detection portion of the Hello AI World tutorial:Re-training SSD-Mobilenet Thanks to @qfgaohao for the upstream implementation from: https://github.com/qfgaohao/pytorch-ssd GitHub View Github    

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