Arabic Car License Recognition. A solution to the kaggle competition Machathon 3.0.

Overview

Transformers

Arabic licence plate recognition 🚗

  • Solution to the kaggle competition Machathon 3.0.
  • Ranked in the top 6️⃣ at the final evaluation phase.
  • Check our solution now on collab!
  • Check the solution presentation

Preprocessing Pipeline

The schematic of the processor

Approach

Step1: Preprocessing Enhancments on the image.

  • Most images had bad illumination and noise
    • Morphological operations to Maximize Contrast.
    • Gaussian Blur to remove Noise.
  • Thresholding on both Value and Saturation channels.

Step2: Extracting white plate using countours.

  • Get countours and sort based on Area.
  • Polygon Approximation For noisy countours.
  • Convex hull for Concave polygons.
  • 4-Point transformation For difficult camera angles.

Now have numbers in a countor and letters in another.

Step3: Separating characters from white plate using sliding windows.

Can't use countours to get symbols in white plate since Arabic Letter may consist of multiple charachters e.g ت this may consist of 2/3 countours.

Solution

  • Tuned 2 sliding windows, one for letters' white plate, the other for numbers.
    • Variable window width
    • Window height is the white plate height, since arabic characters may consist multiple parts
  • Selecting which window
    • Must have no black pixels on the sides
    • Must have a specific range of black pixels inside
    • For each group of windows the one with max black pixels is selected

Step4: Character Recognition.

  • Training 2 model since Arabic letters and numbers are similar e.g (أ,1) (5, ه)
    • one for classifing only arabic letters.
    • one for classifying arabic numbers.

Project Organization

Scripts applied on images

./Macathon/code/
├── extract_bbx_xml.ipynb                       : Takes directory of images and their bbx data stored in an xml files, and crop the bbxs from the images.
|                                                 The xml file contains licence label(name), xmin, ymin, xmax, ymax of the bbxs in an image.    
├── extract_bbx_txt.ipynb                       : Takes directory of images and their bbx data stored in a txt files, and crop the bbxs from the images.
|                                                 The txt file corresponding to one image may consist of multiple bbxs, each corresponds to a row of xmin,ymin,xmax,ymax for that bbx.
└── crop_right_noise.ipynb                      : Crops an image with some percentage and replace with the cropped image. 

Model versions

./Macathon/code/
└── model.ipynb                      : - The preprocessing and modeling stage, Contains:
                                          - Preprocessing Functions
                                          - Training both classifers
                                          - Prediction and generating the output csv file

Data Folder

./Macathon/data/
├── challenging_images.rar                      : Contains most challenging images collected from the train data. 
├── cropped_letters.zip                         : 28 Subfolders corresponding to the 28 letter in Arabic alphabet.
|                                                 Each subfolder holds images for the letter it's named after, cropped from the train data distribution.
├── cropped_numbers.zip                         : 10 Subfolders for the 10 numbers.
|                                                 Each subfolder holds images for the number it's named after, cropped from the train data distribution.
├── machathon-3.zip                             : The uploaded data found with the kaggle competition.
└── testLetters.zip                             : 200 images labeled from the test data distribution.
                                                  Each image has a corresponding xml file holding the bbxs locations in it.

Contributors

This masterpiece was designed, and implemented by

Hossam
Hossam Saeed
Mostafa wael
Mostafa Wael
Nada Elmasry
Nada Elmasry
Noran Hany
Noran Hany
Owner
Noran Hany
Noran Hany
Using Python to Play Cyberpunk 2077

CyberPython 2077 Using Python to Play Cyberpunk 2077 This repo will contain code from the Cyberpython 2077 video series on Youtube (youtube.

Harrison 118 Oct 18, 2022
Cognate Detection Repository

Cognate Detection Repository Details This repository contains the data for two publications: Challenge Dataset of Cognates and False Friend Pairs from

Diptesh Kanojia 1 Apr 26, 2022
Repository for the paper "Online Domain Adaptation for Occupancy Mapping", RSS 2020

RSS 2020 - Online Domain Adaptation for Occupancy Mapping Repository for the paper "Online Domain Adaptation for Occupancy Mapping", Robotics: Science

Anthony 26 Sep 22, 2022
Mmrotate - OpenMMLab Rotated Object Detection Benchmark

OpenMMLab website HOT OpenMMLab platform TRY IT OUT 📘 Documentation | 🛠️ Insta

OpenMMLab 1.2k Jan 04, 2023
This is a vision-based 3d model manipulation and control UI

Manipulation of 3D Models Using Hand Gesture This program allows user to manipulation 3D models (.obj format) with their hands. The project support bo

Cortic Technology Corp. 43 Oct 23, 2022
Code for the paper Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations (AKBC 2021).

Relation Prediction as an Auxiliary Training Objective for Knowledge Base Completion This repo provides the code for the paper Relation Prediction as

Facebook Research 85 Jan 02, 2023
Heart Arrhythmia Classification

This program takes and input of an ECG in European Data Format (EDF) and outputs the classification for heartbeats into normal vs different types of arrhythmia . It uses a deep learning model for cla

4 Nov 02, 2022
Anomaly Detection Based on Hierarchical Clustering of Mobile Robot Data

We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for

Zekeriyya Demirci 1 Jan 09, 2022
Covid19-Forecasting - An interactive website that tracks, models and predicts COVID-19 Cases

Covid-Tracker This is an interactive website that tracks, models and predicts CO

Adam Lahmadi 1 Feb 01, 2022
Dados coletados e programas desenvolvidos no processo de iniciação científica

Iniciacao_cientifica_FAPESP_2020-14845-6 Dados coletados e programas desenvolvidos no processo de iniciação científica Os arquivos .py são os programa

1 Jan 10, 2022
Python Fanduel API (2021) - Lineup Automation

Southpaw is a python package that provides access to the Fanduel API. Optimize your DFS experience by programmatically updating your lineups, analyzin

Brandin Canfield 13 Jan 04, 2023
Code in conjunction with the publication 'Contrastive Representation Learning for Hand Shape Estimation'

HanCo Dataset & Contrastive Representation Learning for Hand Shape Estimation Code in conjunction with the publication: Contrastive Representation Lea

Computer Vision Group, Albert-Ludwigs-Universität Freiburg 38 Dec 13, 2022
Official PyTorch implementation of SyntaSpeech (IJCAI 2022)

SyntaSpeech: Syntax-Aware Generative Adversarial Text-to-Speech | | | | 中文文档 This repository is the official PyTorch implementation of our IJCAI-2022

Zhenhui YE 116 Nov 24, 2022
Largest list of models for Core ML (for iOS 11+)

Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation We'v

Kedan Li 5.6k Jan 08, 2023
All of the figures and notebooks for my deep learning book, for free!

"Deep Learning - A Visual Approach" by Andrew Glassner This is the official repo for my book from No Starch Press. Ordering the book My book is called

Andrew Glassner 227 Jan 04, 2023
Politecnico of Turin Thesis: "Implementation and Evaluation of an Educational Chatbot based on NLP Techniques"

THESIS_CAIRONE_FIORENTINO Politecnico of Turin Thesis: "Implementation and Evaluation of an Educational Chatbot based on NLP Techniques" GENERATE TOKE

cairone_fiorentino97 1 Dec 10, 2021
Mengzi Pretrained Models

中文 | English Mengzi 尽管预训练语言模型在 NLP 的各个领域里得到了广泛的应用,但是其高昂的时间和算力成本依然是一个亟需解决的问题。这要求我们在一定的算力约束下,研发出各项指标更优的模型。 我们的目标不是追求更大的模型规模,而是轻量级但更强大,同时对部署和工业落地更友好的模型。

Langboat 424 Jan 04, 2023
Official implementation for TTT++: When Does Self-supervised Test-time Training Fail or Thrive

TTT++ This is an official implementation for TTT++: When Does Self-supervised Test-time Training Fail or Thrive? TL;DR: Online Feature Alignment + Str

VITA lab at EPFL 39 Dec 25, 2022
Repository for Multimodal AutoML Benchmark

Benchmarking Multimodal AutoML for Tabular Data with Text Fields Repository for the NeurIPS 2021 Dataset Track Submission "Benchmarking Multimodal Aut

Xingjian Shi 44 Nov 24, 2022
IMBENS: class-imbalanced ensemble learning in Python.

IMBENS: class-imbalanced ensemble learning in Python. Links: [Documentation] [Gallery] [PyPI] [Changelog] [Source] [Download] [知乎/Zhihu] [中文README] [a

Zhining Liu 176 Jan 04, 2023