Detectron2 for Document Layout Analysis

Detectron2 This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Detectron2 implementation.PubLayNet is a very large dataset for document layout analysis (document segmentation). It can be used to trained semantic segmentation/Object detection models. NOTE Models are trained on a portion of the dataset (train-0.zip, train-1.zip, train-2.zip, train-3.zip) Trained on total 191,832 images Models are evaluated on dev.zip (~11,000 images) Backbone pretrained on COCO dataset is used but trained from scratch on PubLayNet dataset Trained […]

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Tools to Design or Visualize Architecture of Neural Network

Net2Vis: Net2Vis automatically generates abstract visualizations for convolutional neural networks from Keras code. visualkeras : Visualkeras is a Python package to help visualize Keras (either standalone or included in tensorflow) neural network architectures. It allows easy styling to fit most needs. As of now it supports layered style architecture generation which is great for CNNs (Convolutional Neural Networks) and a grap style architecture. import visualkeras model = … visualkeras.layered_view(model).show() # display using your system viewer visualkeras.layered_view(model, to_file=’output.png’) # write to […]

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BErt-like Neurophysiological Data Representation

BENDR BErt-like Neurophysiological Data Representation. This repository contains the source code for reproducing, or extending the BERT-like self-supervision pre-training for EEG data from the article: BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data To run these scripts, you will need to use the DN3 project. We will try to keep this updated so that it works with the latest DN3 release. If you are just looking for the BENDR model, and […]

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Official implementation of Monocular Quasi-Dense 3D Object Tracking

qd-3dt Monocular Quasi-Dense 3D Object Tracking (QD-3DT) is an online framework detects and tracks objects in 3D using quasi-dense object proposals from 2D images. Monocular Quasi-Dense 3D Object Tracking,Hou-Ning Hu, Yung-Hsu Yang, Tobias Fischer, Trevor Darrell, Fisher Yu, Min Sun,arXiv technical report (arXiv 2103.07351)Project Website (QD-3DT) @article{Hu2021QD3DT, author = {Hu, Hou-Ning and Yang, Yung-Hsu and Fischer, Tobias and Yu, Fisher and Darrell, Trevor and Sun, Min}, title = {Monocular Quasi-Dense 3D Object Tracking}, journal = {ArXiv:2103.07351}, year = {2021} } […]

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A GitHub bot to automatically update and merge GitHub PRs

kodiak A GitHub bot to automatically update and merge GitHub PRs. install app | documentation | web dashboard Automate your GitHub Pull Requests Auto Update – Keep your PRs up to date with master automatically Auto Merge – Add the automerge label to auto merge once CI and Approvals pass. Bot Collaboration – Combine Kodiak with a dependency bot (dependabot, snyk, greenskeeper.io) to automate updating of dependencies Installation Kodiak is available through the GitHub Marketplace. If you’d rather run Kodiak […]

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Build GUIs from python functions using magic

magicgui Build GUIs from python functions using magic. Installation magicgui uses qtpy to support both pyside2 and pyqt5 backends. However, youmust have one of those installed for magicgui to work. install with pip pip install magicgui[pyqt5] # or pip install magicgui[pyside2] or with conda: conda install -c conda-forge magicgui pyqt # or pyside2 instead of pyqt :information_source: If you’d like to help us extend support to a different backend,please open an issue. Basic usage from magicgui import magicgui from enum […]

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A comparison of mesh generators

Mesh Generator Comparison This repository creates meshes of the same domains with multiple mesh generators and compares the results. The used mesh generators are For each domain and mesh generator (if applicable), the repostory shows the followingdata: the mesh generation time the average and minimum cell quality the nummber of CG iterations for the FEM-Poisson-problem on the mesh. If you’d like to see other mesh generators, domains, or quality measures: Let me know! Disk L-shape Rectangle with refinement Quarter annulus […]

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A comprehensive Reddit scraping command-line tool written in Python

URS Universal Reddit Scraper – A comprehensive Reddit scraping command-line tool written in Python. This is a comprehensive Reddit scraping tool that integrates multiple features: Scrape Reddit via PRAW (the official Python Reddit API Wrapper) Scrape Subreddits Scrape Redditors Scrape submission comments Analytical tools for scraped data Get frequencies for words that are found in submission titles, bodies, and/or comments Generate a wordcloud from scrape results Run pip install -r requirements.txt to get all project dependencies. You will need your […]

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A terminal interface for exploring and arranging tabular data

VisiData A terminal interface for exploring and arranging tabular data. VisiData supports tsv, csv, sqlite, json, xlsx (Excel), hdf5, and many other formats. Platform requirements Linux, OS/X, or Windows (with WSL) Python 3.6+ additional Python modules are required for certain formats and sources Install To install the latest release from PyPi: pip3 install visidata To install the cutting edge develop branch (no warranty expressed or implied): pip3 install git+https://github.com/saulpw/[email protected] See visidata.org/install for detailed instructions for all available platforms and package […]

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The next best thing after Bloomberg Terminal

GamestonkTerminal Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies. As a modern Python-based environment, GamestonkTerminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs). Getting Started Install This project was originally written and tested with Python 3.6.8. It should now support […]

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