YOLO: Automatic License Plate Detection & Extract text App

Learn to Develop License Plate Object Detection, OCR and Create Web App Project using Deep Learning, TensorFlow 2, Flask

4.44 (234 reviews)
Udemy
platform
English
language
Data Science
category
1,899
students
5.5 hours
content
Sep 2023
last update
$69.99
regular price

What you will learn

Object Detection from Scratch

License Plate Detection

Extract text from Image using Tesseract

Train InceptionResnet V2 in TensorFlow 2 for Object Detection

Flask Based Web API

Labeling Object Detection Data using Image Annotation Tool

Train custom YOLO model from scratch

Real time license plate detection with YOLO

Description

Welcome to NUMBER PLATE DETECTION AND OCR: A DEEP LEARNING WEB APP PROJECT from scratch

Image Processing and Object Detection is one of the areas of Data Science and has a wide variety of applications in the industries in the current world. Many industries looking for a Data Scientist with these skills. This course covers modeling techniques including labeling Object Detection data (images), data preprocessing, Deep Learning Model building (InceptionResNet V2), evaluation, and production (Web App)

We start this course Project Architecture that was followed to Develop this App in Python. Then I will show how to gather data and label images for object detection for Licence Plate or Number Plate using Image Annotation Tool which is open-source software developed in python GUI (pyQT).

Then after we label the image we will work on data preprocessing, build and train deep learning object detection model (InceptionResnet V2) in TensorFlow 2. Once the model is trained with the best loss, we will evaluate the model. I will show you how to calculate the

  • Intersection Over Union (IoU)

  • The precision of the object detection model.

Once we have done with the Object Detection model, then using this model we will crop the image which contains the license plate which is also called the region of interest (ROI), and pass the ROI to Optical Character Recognition API Tesseract in Python (Pytesseract). In this model, I will show you how to extract text from images.  Now, we will put it all together and build a Pipeline Deep Learning model.

In the final module, we will learn to create a web app project using FLASK Python. Initially, we will learn basics concepts in Flask like URL routing, render the template, template inheritance, etc. Then we will create our website using HTML, Bootstrap. With that we are finally ready with our App.

WHAT YOU WILL LEARN?

  • Building Project in Python Programming

  • Labeling Image for Object Detection

  • Train Object Detection model (InceptionResNet V2) in TensorFlow 2.x

  • Model Evaluation

  • Optical Character Recognition with Pytesseract

  • Flask API

  • Flask Web App Development in HTML, Boostrap, Python

  • Train YOLO model with Custom data

  • Develop web application and integrate YOLO Model


We know that Computer Vision-Based Web App is one of those topics that always leaves some doubts. Feel free to ask questions in Q & A and we are very happy to answer all your questions.

We also provided all Notebooks, py files in the resources which will useful for reference.

Content

Introduction

Project Architecture
Download the Resources

Labeling

Get the Data
Download Image Annotation Tool
Install Dependencies
Label Images
XML to CSV

Data Processing

Read Data
Verify Labeled Data
Data Preprocessing
Split train and test set

Deep Learning for Object Detection

Get Transfer Learning from TensorFlow 2.x
InceptionResnet V2 model building
Defining Inputs and Outputs
Compiling Model
InceptionResnet V2 Training
InceptionResnet V2 Training - Part 2
Save Deep Learning Model
Tensorboard

Pipeline Object Detection Model

Make Predictions
Make Predictions part2
De-normalize the Output
Bounding Box
Create Pipeline

Optical Character Recognition (OCR)

Install Tesseract
Install Pytesseract
Exrtract Number Plate text from Image

Flask App

Install Visual Studio Code
First Flask App
Render HTML Template
Import Boostrap

Number Plate Web App

Create Web App
Footer
Template Inheritance
Upload Form in HTML
HTTP Method Upload File in Flask
Integrate Deep Learning Object Detection Model
Integrate Number Plate Detection and OCR to Flask App
Display Output in HTML Page
Display Output in HTML Page part 2

BONUS

Bonus Lecture

Screenshots

YOLO: Automatic License Plate Detection & Extract text App - Screenshot_01YOLO: Automatic License Plate Detection & Extract text App - Screenshot_02YOLO: Automatic License Plate Detection & Extract text App - Screenshot_03YOLO: Automatic License Plate Detection & Extract text App - Screenshot_04

Reviews

Seungbaek
September 16, 2023
The course environment is old, so many errors occur for beginners, making it difficult to take the course.
Durga
July 7, 2023
Very Nice Course .I have developed my first end to end object detection model using YOLO. Very Nice and More Informative
Kutay
February 17, 2023
It was the 2nd course I took. I was satisfied with both courses. Especially the data preparation sections are very useful. Of course, it would be better if the codes were explained in more detail. I recommend you to buy.
John
January 30, 2023
Excellent course, I think you should add an additional course for creating text reading ORCs without using pytesseract that would be awesome!
Yaron
August 30, 2022
The first half of the course teaches how to create an object recognition application starting from the data labeling and all the way to a Flask based Web app. The second half shows how to use the Yolo5 model to get excellent object detection results. The course weakness is in the text extraction. It uses Tesseract and as the lecturer repeatedly says - Tesseract out of the box has a low text extraction success rate. Another problem is the font size for the coding examples is quite small, even on a 24" monitor. However all code is included so you can download it and listen while separately following along. Conclusion: If you're mainly interested in the detect part - This is an excellent course. If you're interested in extracting text from images - you're going to be very disappointed.
HAZIQ
May 4, 2022
Amazing course. It could be better if the instructor could zoom in the screen a bit more so the student could see clearly what you trying to point out or highlight using the cursor.
Hari
April 14, 2022
Pros : Well paced, good intro to yolo and google colabs which I found useful. The course is a practical demo of api calls needed for a working application. Cons : Does not really develop intuition on how to get the best results.
Wojciech
February 11, 2022
This is more an instruction how to set up all tools and libraries rather than a course that will teach you how all those things really work. Maybe it is fine if you have to quickly implement something similar for your studies or work without understanding details. Most of the time is spend on installing software an setup, loading images. The real interesting parts (deep learning & ocr) are left practically with very little comment and no deeper thoughts... A promo price (couple of usd) is a fair deal but definitely I wouldn't pay the regular price for it.
Raj
December 9, 2021
Extremely well made and especially helpful staff in the QnA section with replies within a couple hours at maximum! Well made course and I love it
Pepirakun
November 28, 2021
I am yet to learn more and more.. I will update my ratings once I am done with this lovely course! Thank u! <3
Mario
May 21, 2021
I changed my review because you clarify that you did not delete my question, that was what bothered me the most and that the one who deleted it was Udemy, I just want to clarify that the fact of saying, that it does not detect the plates is a shame and ridiculous is not in no time a bad word, on the other hand after I finished the course you added 2 new videos that say that the effectiveness of the ocr depends on the tilt angles, and the pixel resolution. Cambié mi reseña porque me aclaras que tú no borraste mi pregunta, eso fue lo que más me molestó y que quien la borró fue Udemy, solo quiero aclarar que el hecho de decir, que no detecte las placas es una pena y ridículo no es en ningún momento una mala palabra, por otro lado después que terminé el curso agregaste 2 nuevos videos diciendo que la efectividad del ocr depende de los ángulos de inclinación, y la resolución de pixeles.

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3893664
udemy ID
3/5/2021
course created date
3/31/2021
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