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Project of final thesis graduation

Python 50.59% CMake 1.12% Makefile 12.53% PowerShell 0.08% Shell 0.16% C# 0.03% Batchfile 0.11% C 12.79% Cuda 3.00% C++ 12.95% Jupyter Notebook 6.57% Dockerfile 0.07%
computer-vision convolutional-neural-networks deep-learning deep-neural-networks image-recognition object-detection python3 yolov3

autolpr-itera's Introduction

AutoLPR: Automated License Plate Recognition Based on Itera

Thesis: Identification Of Police Number Characters On Vehicle Plates Using Convolutional Neural Networks

Author


This repository contains the implementation of my final assignment on character identification on vehicle plates using Convolutional Neural Networks (CNNs). The project is divided into three main stages:

  1. Object Detection Plate using SSD ResNet-50
  2. Object Detection Plate using YOLO-V3
  3. Character Recognition using MobileNet-V2

Table of Contents


Datasets

The datasets used in this thesis are provided below:

  1. Dataset for Object Detection (SSD ResNet-50):

  2. Dataset for Object Detection (YOLO-V3):

  3. Dataset for Character Recognition (MobileNet-V2):


Models

Pre-trained models used in this project can be accessed through the following links:

  1. SSD ResNet-50 Models:

  2. YOLO-V3 Models:


Source Code

The source code for testing the YOLO-V3 model can be found at the following link:


Configuration

Configuration files for the SSD ResNet-50 model can be downloaded from the link below:


Thesis Document

The final thesis document, which provides a detailed explanation of the methodologies and results, can be accessed here:


How to Use

  1. Clone the Repository:
    git clone https://github.com/mftakhullaziz/automate-lpr.git
    cd automate-lpr
    

autolpr-itera's People

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