YOLO: Automatic License Plate Detection & Extract text App

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Project Architecture

Lecture 3: Install Anaconda Python

Lecture 4: Install OpenCV and TensorFlow 2.x

Lecture 5: Download the Resources

Lecture 6: Facing Any issue with the Course ? here is the solution.

Chapter 2: Labeling

Lecture 1: Get the Data

Lecture 2: Download Image Annotation Tool

Lecture 3: Install Dependencies

Lecture 4: Label Images

Lecture 5: Error: LabelImg Crashing after clicking on "Create RectBox"

Lecture 6: XML to CSV

Chapter 3: Data Processing

Lecture 1: Read Data

Lecture 2: Verify Labeled Data

Lecture 3: Data Preprocessing

Lecture 4: Split train and test set

Chapter 4: Deep Learning for Object Detection

Lecture 1: Download the Resources

Lecture 2: Updated all codes compatible for latest TensorFlow version 2.13.0

Lecture 3: Get Transfer Learning from TensorFlow 2.x

Lecture 4: InceptionResnet V2 model building

Lecture 5: Defining Inputs and Outputs

Lecture 6: Compiling Model

Lecture 7: InceptionResnet V2 Training

Lecture 8: InceptionResnet V2 Training – Part 2

Lecture 9: Save Deep Learning Model

Lecture 10: Tensorboard

Chapter 5: Pipeline Object Detection Model

Lecture 1: Make Predictions

Lecture 2: Make Predictions part2

Lecture 3: De-normalize the Output

Lecture 4: Bounding Box

Lecture 5: Create Pipeline

Chapter 6: Optical Character Recognition (OCR)

Lecture 1: Install Tesseract

Lecture 2: Install Pytesseract

Lecture 3: Extract Number Plate text from Image

Lecture 4: Limitations of Pytesseract

Lecture 5: Challenges & Beyond the Scope of Course

Chapter 7: Flask App

Lecture 1: Install Visual Studio Code

Lecture 2: First Flask App

Lecture 3: Render HTML Template

Lecture 4: Import Boostrap

Chapter 8: Number Plate Web App

Lecture 1: Download the Flask Web App for your Reference

Lecture 2: Create Web App

Lecture 3: Footer

Lecture 4: Template Inheritance

Lecture 5: Upload Form in HTML

Lecture 6: HTTP Method Upload File in Flask

Lecture 7: Integrate Deep Learning Object Detection Model

Lecture 8: Integrate Number Plate Detection and OCR to Flask App

Lecture 9: Display Output in HTML Page

Lecture 10: Display Output in HTML Page part 2

Lecture 11: Updated Code

Chapter 9: Real Time Number Plate Recognition with YOLO

Lecture 1: Download the Resources

Lecture 2: Introduction to YOLO

Lecture 3: Data Preparation for Yolo

Lecture 4: Data Preparation Code for MAC and Linux OS

Lecture 5: Preparing Images folder structure for YOLO

Lecture 6: More Data

Lecture 7: Create "yaml" file for YOLO data

Lecture 8: Challenges in Training Yolo

Lecture 9: Install and Setting up Google Colab

Lecture 10: Connect your notebook to GPU

Lecture 11: Training YOLO model

Lecture 12: New update in training YOLO model

Lecture 13: Save YOLO Model for OpenCV compatible

Lecture 14: New Update in Export YOLO model in ONNX

Lecture 15: Interpreting Results

Lecture 16: Predicting Results from YOLO

Lecture 17: Predicting Results from YOLO: Get Bounding Boxes

Lecture 18: Predicting Results from YOLO: Apply Non Maximum Suppression on Bounding Box

Lecture 19: Predicting Results from YOLO: Draw Bounding Box

Lecture 20: Clean the Code and Create Functions

Lecture 21: Real Time plate detection with YOLO (on videos)

Lecture 22: Error Error Error !!!

Lecture 23: Extract Text from License plate

Chapter 10: YOLO Number Plate Web App Code

Lecture 1: Coding Exercise

Lecture 2: YOLO Number Plate Web App Code Solution

Chapter 11: BONUS

Lecture 1: Bonus Lecture