Author: Deep Learner

Testing

A Python framework for creating automated browser tests

LuluTest LuluTest is an open source browser automation framework using Python and Selenium. It is relatively lightweight in that it mostly provides wrappers for 3rd party library methods that make browser automation and testing more intuitive. The ultimate goal of LuluTest is to get people writing robust automated browser scripts quickly by abstracting out the inherent complexities and peculiarities Basic Usage LuluTest is designed to support both white and black box testing. The functionsprovided will work as long as the […]

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Web Crawling & Web Scraping

A california coronavirus scrapers are written using Python

california-coronavirus-scrapers An experiment in open-sourcing the web scrapers that feed the Los Angeles Times’ California coronavirus tracker. The scrapers are written using Python and Jupyter notebooks, scheduled and run via GitHub Actions and then archived using git. Installation Clone the repository and install the Python dependencies. pipenv install Run all of the scraper commands. make Run one of the scraper commands. make -f vaccine-doses-on-hand/Makefile GitHub https://github.com/datadesk/california-coronavirus-scrapers    

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Data Visualization

A Python library that allows for effortless profiling with high-quality visualizations

QuickPotato A library for the Python programming language that allows for effortless profiling with high-quality visualizations and empowers you to produce a performance angle to test-driven development. QuickPotato is a Python library that aims to make it easier to rapidly profile your software and produce powerful code visualizations that enables you to quickly investigate where potential performance bottlenecks are hidden. Also, QuickPotato is trying to provide you with a path to add an automated performance testing angle to your regular […]

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Framework

A Python library for building Conceptual Distributed Model

Hapi Hapi is an open-source Python Framework for building raster-based conceptual distributed hydrological models using HBV96 lumped model & Muskingum routing method at a catchment scale, Hapi gives a high degree of flexibility to all components of the model (spatial discretization – cell size, temporal resolution, parameterization approaches and calibration). Main Features Modified version of HBV96 hydrological model (Bergström, 1992) with 15 parameters in case of consideringsnow processes, and 10 parameters without snow, in addition to 2 parameters of Muskingum […]

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Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 75: Outbound Translation

This week, I will comment on a paper by my good old friends from Charles University in collaboration with the University of Edinburgh, the University of Sheffield, and the University of Tartu within the Bergamot project. The main goal of the project is to develop a high-quality machine translation that runs locally in an internet browser and unlike services such as Google Translate or Microsoft Translator does not send any (potentially sensitive) data to any server. This is a very […]

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Machine Learning

Spatial Intention Maps for Multi-Agent Mobile Manipulation

spatial-intention-maps Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser IEEE International Conference on Robotics and Automation (ICRA), 2021 Abstract: The ability to communicate intention enables decentralized multi-agent robots to collaborate while performing physical tasks. In this work, we present spatial intention maps, a new intention representation for multi-agent vision-based deep reinforcement learning that improves coordination between decentralized mobile manipulators. In this representation, each agent’s intention is provided to other agents, and rendered into an overhead 2D […]

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GUI

A youtube-dl GUI written in PyQt

youtube-dl-GUI This repository contains code for a youtube-dl GUI written in PyQt. It is based on youtube-dl which is a Video downloading script maintained by various contributers and released in Public Domain. This GUI code is currently written for Python v3.x. Please note that this GUI code is released under the MIT License and not Public Domain. Requirements: Requirement for build Binaries/Executables Features: This application has the following features: supports downloading videos from 200+ websites allows to download multiple videos […]

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NLP

MixKD: Towards Efficient Distillation of Large-Scale Language Models

March 17, 2021 By: Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin Abstract Large-scale language models have recently demonstrated impressive empirical performance. Nevertheless, the improved results are attained at the price of bigger models, more power consumption, and slower inference, which hinder their applicability to low-resource (both memory and computation) platforms. Knowledge distillation (KD) has been demonstrated as an effective framework for compressing such big models. However, large-scale neural network systems are prone […]

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Data Visualization

An interactive chemical viewer for 2D structures of small molecules

mols2grid mols2grid is an interactive chemical viewer for 2D structures of small molecules, based on RDKit. 🐍 Installation mols2grid was developped for Python 3.6+ and requires rdkit (>=2019.09.1), pandas and jinja2 as dependencies. To install mols2grid from a clean conda environment: conda install -c conda-forge ‘rdkit>=2019.09.1’ pip install mols2grid It is compatible with Jupyter Notebook and Google Colab (Visual Studio notebooks and Jupyterlab are not supported) and can run on Streamlit. 📜 Usage import mols2grid mols2grid.display(“path/to/molecules.sdf”, # RDKit’s MolDrawOptions parameters […]

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Machine Learning

A simple python library for fast image generation of people who do not exist

Random Face A simple python library for fast image generation of people who do not exist. Requirements Linux, Windows, MacOS Python 3.8+ CPU compatible with OpenVINO. Install package pip install random_face Install the latest version git clone https://github.com/bes-dev/random_face.git cd random_face pip install -r requirements.txt python download_model.py pip install . Demo python -m random_face.demo Example import cv2 import random_face engine = random_face.get_engine() face = engine.get_random_face() cv2.imshow(“face”, face) cv2.waitKey() Citation @misc{belousov2021mobilestylegan, title={MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis}, author={Sergei […]

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