Beginner-friendly repository for Hacktober Fest 2021. Start your contribution to open source through baby steps. πŸ’œ

Overview

Hacktober Fest 2021

πŸŽ‰ Open source is changing the world – one contribution at a time! πŸŽ‰


This repository is made for beginners who are unfamiliar with open source and GitHub. So what is holding you back?! Make your first contribution to the open source and take home swags. πŸ‘• πŸ“¦

What is Hacktober Fest?

Hacktoberfest is a month-long open source contribution program hosted by DigitalOcean in the month of October for supporting open source development. Hacktoberfest encourages participation in the open source community, which grows bigger every year. Whether you are a pro in programming or a newbie, Hacktoberfest welcomes each one of the contributors for providing their valuable contribution to the open source community. Completing the challenge earns you a limited edition swags and other exiciting goodies.

How to receive swags?

  • Register yourself at the Hacktober Fest Website
  • Create 4 pull-requests from repositories participating in the challenge (repositories having hacktoberfest topic)
  • Successfully merged PRs will be validated further for 14 days.
  • After that, the PR is accepted
  • Remember! All PRs must be done between October 1 to October 31 to be eligible for swags.
  • This year the first 55,000 participants will be eligible for the prize.

How to contribute?

Read RULES.md before creating a pull request

PRs violating the rules will be closed and reported Spam! ❌

If you're not comfortable with command line, here are tutorials using GUI tools. If you don't have git on your machine, install it.

1. Fork the repository.

fork this repository

2. Clone your forked copy of the project.

git clone  https://github.com/abhilashmnair/HacktoberFest2021.git

3. Navigate to the project directory πŸ“ .

cd HacktoberFest2021

4. Add a reference(remote) to the original repository.

git remote add upstream https://github.com/abhilashmnair/HacktoberFest2021.git

5. Check the remotes for this repository.

git remote -v

6. Always take a pull from the upstream repository to your master branch to keep it at par with the main project(updated repository).

git pull upstream main

7. Create a new branch.

git checkout -b <your_branch_name>

8. Perform your desired changes to the code base.

9. Track your changes βœ”οΈ .

git add *

10. Commit your changes .

git commit -m "Message"

11. Push the committed changes in your feature branch to your remote repo.

git push -u origin <your_branch_name>

12. To create a pull request, click on compare and pull requests. Please ensure you compare your feature branch to the desired branch of the repository you are supposed to make a PR to.

Not a developer or programmer? Don't worry! Add useful documentation and fix grammatical errors in the README file. Every single contribution of yours will benefit your open source venture.

License

This repository and the contained files are licensed under MIT License. See LICENSE for full text.


πŸ’œ Thank You for your participation! πŸ’œ

Owner
Abhilash M Nair
Abhilash M Nair
Code for "Diffusion is All You Need for Learning on Surfaces"

Source code for "Diffusion is All You Need for Learning on Surfaces", by Nicholas Sharp Souhaib Attaiki Keenan Crane Maks Ovsjanikov NOTE: the linked

Nick Sharp 247 Dec 28, 2022
Seg-Torch for Image Segmentation with Torch

Seg-Torch for Image Segmentation with Torch This work was sparked by my personal research on simple segmentation methods based on deep learning. It is

Eren GΓΆlge 37 Dec 12, 2022
ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

Zongdai 107 Dec 20, 2022
Official Implementation for the "An Empirical Investigation of 3D Anomaly Detection and Segmentation" paper.

An Empirical Investigation of 3D Anomaly Detection and Segmentation Project | Paper Official PyTorch Implementation for the "An Empirical Investigatio

Eliahu Horwitz 55 Dec 14, 2022
Layered Neural Atlases for Consistent Video Editing

Layered Neural Atlases for Consistent Video Editing Project Page | Paper This repository contains an implementation for the SIGGRAPH Asia 2021 paper L

Yoni Kasten 353 Dec 27, 2022
[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning | ζ–—εœ°δΈ»AI

[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning DouZero is a reinforcement learning framework for DouDizhu (ζ–—εœ°δΈ»), t

Kwai Inc. 3.1k Jan 04, 2023
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks)

A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks) This repository contains a PyTorch implementation for the paper: Deep Pyra

Greg Dongyoon Han 262 Jan 03, 2023
Image processing in Python

scikit-image: Image processing in Python Website (including documentation): https://scikit-image.org/ Mailing list: https://mail.python.org/mailman3/l

Image Processing Toolbox for SciPy 5.2k Dec 31, 2022
*ObjDetApp* deploys a pytorch model for object detection

*ObjDetApp* deploys a pytorch model for object detection

Will Chao 1 Dec 26, 2021
Transformer Tracking (CVPR2021)

TransT - Transformer Tracking [CVPR2021] Official implementation of the TransT (CVPR2021) , including training code and trained models. We are revisin

chenxin 465 Jan 06, 2023
A Distributional Approach To Controlled Text Generation

A Distributional Approach To Controlled Text Generation This is the repository code for the ICLR 2021 paper "A Distributional Approach to Controlled T

NAVER 102 Jan 07, 2023
PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis

WaveGrad2 - PyTorch Implementation PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis. Status (202

Keon Lee 59 Dec 06, 2022
A PyTorch implementation of the paper "Semantic Image Synthesis via Adversarial Learning" in ICCV 2017

Semantic Image Synthesis via Adversarial Learning This is a PyTorch implementation of the paper Semantic Image Synthesis via Adversarial Learning. Req

Seonghyeon Nam 146 Nov 25, 2022
It's like Shape Editor in Maya but works with skeletons (transforms).

Skeleposer What is Skeleposer? Briefly, it's like Shape Editor in Maya, but works with transforms and joints. It can be used to make complex facial ri

Alexander Zagoruyko 1 Nov 11, 2022
Face recognize system

FRS Face_recognize_system This project contains my work that target on solving some problems of FRS: Face detection: Retinaface Face anti-spoofing: Fo

Tran Anh Tuan 4 Nov 18, 2021
PyMatting: A Python Library for Alpha Matting

Given an input image and a hand-drawn trimap (top row), alpha matting estimates the alpha channel of a foreground object which can then be composed onto a different background (bottom row).

PyMatting 1.4k Dec 30, 2022
This is an official implementation for "Self-Supervised Learning with Swin Transformers".

Self-Supervised Learning with Vision Transformers By Zhenda Xie*, Yutong Lin*, Zhuliang Yao, Zheng Zhang, Qi Dai, Yue Cao and Han Hu This repo is the

Swin Transformer 529 Jan 02, 2023
LIMEcraft: Handcrafted superpixel selectionand inspection for Visual eXplanations

LIMEcraft LIMEcraft: Handcrafted superpixel selectionand inspection for Visual eXplanations The LIMEcraft algorithm is an explanatory method based on

MI^2 DataLab 4 Aug 01, 2022
Official PyTorch implementation of the paper Image-Based CLIP-Guided Essence Transfer.

TargetCLIP- official pytorch implementation of the paper Image-Based CLIP-Guided Essence Transfer This repository finds a global direction in StyleGAN

Hila Chefer 221 Dec 13, 2022
Implementation of Google Brain's WaveGrad high-fidelity vocoder

WaveGrad Implementation (PyTorch) of Google Brain's high-fidelity WaveGrad vocoder (paper). First implementation on GitHub with high-quality generatio

Ivan Vovk 363 Dec 27, 2022