Iran Open Source Hackathon

Overview

logo

Iran Open Source Hackathon is an open-source hackathon (duh) with the aim of encouraging participation in open-source contribution amongst Iranian developers. There is a curated list of repositories whose maintainers volunteered to be part of the hackathon. Contribute to any of these repositories during the hackathon, and at the end top contributors will be acknowledged here (so yes in the end its just about bragging rights).

👉 If you are a maintainer and want to enter some of your repositories in the hackathon so our participants will contribute to them, check this section.


A Note on Terminology

In these documents, keywords MUST, MUST NOT, REQUIRED, SHALL, SHALL NOT, SHOULD, SHOULD NOT, RECOMMENDED, MAY, and OPTIONAL, when appearing in caps lock and in bold, are to be interpreted as described in RFC 2119. This is not a software spec document, but still the extra clarity helps avoiding confusion.


⚠️ ⚠️ WORK IN PROGRESS NOTICE

This is work in progress. As long as this notice is up here, any rule, date, information, etc is subject to sudden change without any prior notice.

If a piece of information is followed by ⚠️, then there is a good chance we will change it in near future and current information is mostly a placeholder.



How Can I Participate?

Contribute to one of these repositories during the time of the hackathon:

  • Make a pull request, include #iosh ⚠️ in its title ⚠️ .
  • The pull request MUST be accepted to the repository before the end of the hackathon.
  • Each pull request will count towards your total score (depends on how many lines of code it is ⚠️ ).
  • At the end, top 5 ⚠️ contributors (highest scores ⚠️ ) will be acknowledged here. We might update the list during the hackathon as well.

👉 If you are unfamiliar with open-source contribution, git or github, take a look at these resources.

NOTE: Please carefully read our code of conduct before you start contributing.


Why Should I Participate?

  • You will help improve software that people like you use (apes together strong).
  • You will learn a lot (like seriously, a TON).
  • You will earn street-cred (which also helps with employability).

I Am A Maintainer. Can I Add My Repos To This Hackathon?

Of course! You need to:

  1. Fork this repository.
  2. For each repository like https://github.com/jafar/my-repo, add a yaml file to first/repos
    (i.e. first/repos/jafar/my-repo.yaml):
# first/repos/jafar/my-repo.yaml

name: My Cool Repository
description: I am particularly cool here
languages:
  - JavaScript
  - Hashemi
  - ...
  1. Make a pull request.

👉 You can see examples in the repos directory.

👉 You can add a list of maintainers (with whom hackathon participants can be in contact) as well:

# first/repos/jafar/my-repo.yaml

name: My Cool Repository
description: I am particularly cool here
languages:
  - JavaScript
  - Hashemi
#
# 👉 for user `https://github.com/asghar`, add `asghar` to this list
# 👉 also don't forget the repo owner if they are going to be a maintainer as well
#
maintainers:
  - jafar
  - asghar
  - nooshin
  - maliheh

👉 If your repo belongs to a company or organization, you MUST specify maintainers independently.

NOTE: Please carefully read our code of conduct before you submit your repositories.


Repositories

Name Description Owner Maintainer(s) Languages
FL Chart A powerful Flutter chart library, currently supporting Line Chart, Bar Chart, Pie Chart, Scatter Chart and Radar Chart. imaNNeoFighT imaNNeoFighT dart
Letiner An intelligent Leitner to memorize information, especially words, without needing to maintain boxes manually. It can be synced with Dropbox. justmisam justmisam Javascript, HTML, CSS
Lightweight Message Queue (LMQ) A lightweight message queue to work with short messages or content references as messages. justmisam justmisam Go
PyLMQ Python Library for LMQ justmisam justmisam Python
BarnameKon Telegram bot which create "Add to Google Calendar" link for your events. anvaari anvaari python
TyFON Typed Functions Over Network loreanvictor loreanvictor typescript, javascript
Callbag JSX callbags + JSX: fast and tiny interactive web apps loreanvictor loreanvictor typescript
Peanar A background job scheduler for Node.js based on RabbitMQ martianboy martianboy typescript
divar-starter-kit React.js SSR-ready boilerplate using Razzle. divar-ir iMohammadReza javascript
gRPC Go Contracts Verify the communication of your microservices by writing contracts for your RPCs shayanh shayanh go
thatcher-effect-dataset-generator Using OpenCV to apply Thatcher effect on a set of face images erfaniaa erfaniaa Python
text-to-commit-history Write a large text on your Github profile, with your commits history (contribution graph). erfaniaa erfaniaa Python
Keepalived Exporter Prometheus exporter for Keepalived metrics. cafebazaar mehdy go
Anbar A basic S3 compatible storage server in Rust. mehdy mehdy rust
Pyeez A simple framework to create console applications (like htop). mehdy mehdy python
paperify Backup files on paper using QRCodes. alisinabh alisinabh shell
Zarb project Zarb blockchain zarbchain b00f Go, Rust, Javascript
Laravel Toman Elegant Zarinpal and IDPay payment gateways for Laravel evryn AmirrezaNasiri PHP

To be completed


Duration

Beginning تیر ۱۵ 06 July
Ending شهریور ۱۵ 06 September

۱۴۰۰ / 2021


👉 For Participants

Your pull requests MUST be submitted after beginning of the hackathon period and be merged before the end of the hackathon.


👉 For Maintainers

Ideally, submit your repositories before the start of the hackathon, though you can ( ⚠️ ) submit it during the duration of the hackathon as well.


Top Contributors

To be determined


Owner
OSS Hackathon
OSS Hackathon
Flappy bird automation using Neuroevolution of Augmenting Topologies (NEAT) in Python

FlappyAI Flappy bird automation using Neuroevolution of Augmenting Topologies (NEAT) in Python Everything Used Genetic Algorithm especially NEAT conce

Eryawan Presma Y. 2 Mar 24, 2022
Code for MarioNette: Self-Supervised Sprite Learning, in NeurIPS 2021

MarioNette | Webpage | Paper | Video MarioNette: Self-Supervised Sprite Learning Dmitriy Smirnov, Michaël Gharbi, Matthew Fisher, Vitor Guizilini, Ale

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Revealing and Protecting Labels in Distributed Training

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This is an official implementation of our CVPR 2021 paper "Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression" (https://arxiv.org/abs/2104.02300)

Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression Introduction In this paper, we are interested in the bottom-up paradigm of estima

HRNet 367 Dec 27, 2022
A Kitti Road Segmentation model implemented in tensorflow.

KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark

Marvin Teichmann 890 Jan 04, 2023
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search

CLIP-GLaSS Repository for the paper Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search An in-browser demo is

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Tutel MoE: An Optimized Mixture-of-Experts Implementation

Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho

Microsoft 344 Dec 29, 2022
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Deep Learning for image classification pip install -r http://webia.lip6.fr/~baskiotisn/requirements-amal.txt Train an autoencoder python3 train_auto

Hector Kohler 0 Mar 30, 2022
Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory

Approximate Outer Product Gradient Descent with Memory Code for the numerical experiment of the paper Speeding-Up Back-Propagation in DNN: Approximate

2 Mar 02, 2022
Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad to your characters in Modo.

Applicator Kit for Modo Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad with a TrueDepth camera to

Andrew Buttigieg 3 Aug 24, 2021
SwinTrack: A Simple and Strong Baseline for Transformer Tracking

SwinTrack This is the official repo for SwinTrack. A Simple and Strong Baseline Prerequisites Environment conda (recommended) conda create -y -n SwinT

LitingLin 196 Jan 04, 2023
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Jorma Laaksonen 3 Jan 27, 2022
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
Official code for "Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021".

Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021. Introduction We proposed a novel model training paradi

Lucas 103 Dec 14, 2022
This respository includes implementations on Manifoldron: Direct Space Partition via Manifold Discovery

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dayang_wang 4 Apr 28, 2022
On Evaluation Metrics for Graph Generative Models

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Pytorch implementation of paper: "NeurMiPs: Neural Mixture of Planar Experts for View Synthesis"

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James Lin 101 Dec 13, 2022
Easily Process a Batch of Cox Models

ezcox: Easily Process a Batch of Cox Models The goal of ezcox is to operate a batch of univariate or multivariate Cox models and return tidy result. ⏬

Shixiang Wang 15 May 23, 2022
Code for "Learning Graph Cellular Automata"

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Daniele Grattarola 37 Oct 26, 2022
A tutorial on training a DarkNet YOLOv4 model for the CrowdHuman dataset

YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Table of c

JK Jung 118 Nov 10, 2022