Google Developer Student Club I2IT/Clippin n grafting Backend

Presenting you, 🎉 Clippin’ n Grafting 🎉, your very own ecommerce website displaying all your artsy-craftsy stuff. Not only the exposure, but we aim to provide budding artists, budding entrepreneurs and just art enthusiasts a platform to sell, buy and just cruise through the amazing range of artistry that people desire to showcase! This repo focuses on the Django backend part of our Clippin’ n Grafting project Frontend –                     Backend –    

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Network automation Inventory manager

Welcome to Worktory’s documentation! Worktory is a python library created with the single purpose of simplifying the inventory management of network automation scripts. As the network automation ecosystem grows, several connection plugins and parsers are available, and several times choosing a library or a connection plugin restricts all the devices to the same connection method. Worktory tries to solve that problem giving the developer total flexibility for choosing the connector plugin and parsers for each device, at the same time […]

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Convert lecture videos to slides in one line

About Convert lecture videos to slides in one line. Takes an input of a directory containing your lecture videos and outputs a directory containing .PDF files containing the slides of each lecture. (You can download the videos from Google Drive even if you only have View-Only permissions. Google it) The utility only captures slides when it detects that a slide has changed and does not capture every frame. Thus your pdf will be very close to the actual slides used. […]

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AniFormer: Data-driven 3D Animation with Transformer

This is the PyTorch implementation of our BMVC 2021 paper AniFormer: Data-driven 3D Animation with Transformer.Haoyu Chen, Hao Tang, Nicu Sebe, Guoying Zhao. Citation If you use our code or paper, please consider citing: @inproceedings{chen2021AniFormer, title={AniFormer: Data-driven 3D Animation withTransformer}, author={Chen, Haoyu and Tang, Hao and Sebe, Nicu and Zhao, Guoying}, booktitle={BMVC}, year={2021} } Dependencies Requirements: python3.6 numpy pytorch==1.1.0 and above trimesh Dataset preparation Please download DFAUST dataset    

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MEND: Fast Model Editing at Scale

Setup Environment This codebase uses Python 3.7.9. Other versions may work as well. Create a virtualenv (pyenv can help with this)and install the dependencies: $ python -m venv env $ source env/bin/activate (env) $ pip install -r requirements.txt Data You can download the data needed for this project fromthis Google Drive link.Unzip each sub-directory into mend/data and you should be good to go. Running the code Run MEND training/evaluation for distilGPT-2 on the wikitext editing problem with:

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A python program will display all SSID usernames and SSID passwords you once connected to your laptop

Windows-Wifi-password-extractor This python program will display all SSID usernames and SSID passwords you once connected to your laptop How to run the program Run the following command python windows_wifi_passwd_extractor.py Requirements Python 3.X beautifultable should be installled on your system Note for the program to run successfully open the CMD/Terminal and type the following command pip install -r requirements.txt Build with Author License    

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Lighter and Faster YOLO is used to detect defect of X-ray weld image

This project is based on ultralytics/yolov3. LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image. Download $ git clone https://github.com/lmomoy/LF-YOLO Train We provide multiple versions of LF-YOLO with different depths. $ python train.py –data coco.yaml –cfg LF-YOLO.yaml –weights ” –batch-size 1 LF-YOLO-1.25.yaml 1 LF-YOLO-0.75.yaml 1 LF-YOLO-0.5.yaml 1 Results We test our model on public dataset MS COCO, and it also achieves competitive results. Model size(pixels) mAPval0.5:0.95 mAPtest0.5:0.95    

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Repository for the Bias Benchmark for QA dataset

Repository for the Bias Benchmark for QA dataset. Authors: Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Thompson, Phu Mon Htut, and Samuel R. Bowman. About BBQ It is well documented that NLP models learnsocial biases present in the world, but littlework has been done to show how these biasesmanifest in actual model outputs for appliedtasks like question answering (QA). We introduce the Bias Benchmark for QA (BBQ), adataset consisting of question-sets constructedby the authors that highlightattestedsocialbiases […]

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Python port of Google’s libphonenumber

This is a Python port of Google’s libphonenumber library It supports Python 2.5-2.7 and Python 3.x (in the same codebase, with no 2to3 conversion needed). Original Java code is Copyright (C) 2009-2015 The Libphonenumber Authors. Release HISTORY, derived from upstream release notes. Installation Install using pip with: pip install phonenumbers Example Usage The main object that the library deals with is a PhoneNumber object. You can create this from a string representing a phone number using the parse function, but […]

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