YOLO: Automatic License Plate Detection & Extract text App

🚀 Course Headline: YOLO: Automatic License Plate Detection & Extract Text App 🚫

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

Dive into the fascinating world of Data Science with a focus on Image Processing and Object Detection. These skills are highly sought after across various industries, and this course is designed to equip you with the knowledge and practical experience to excel in this field.

Course Overview:

• Project Architecture & Development: Learn how to structure your project effectively using Python as the primary programming language. We'll outline the steps from data gathering to deployment.

• Data Annotation: Discover the process of labeling images for object detection, using an open-source Image Annotation Tool developed in python GUI (pyQT). This is a crucial step to prepare your dataset for training your model.

• Deep Learning Model Building & Training: Get hands-on experience with TensorFlow 2 by building and training a deep learning object detection model using the InceptionResNet V2 architecture. Learn how to fine-tune your model for optimal performance.

• Model Evaluation: Master the art of evaluating your model's performance using metrics such as Intersection Over Union (IoU) and precision. Understand the significance of these metrics in assessing the effectiveness of your object detection model.

• Region of Interest (ROI) Extraction & OCR: After detecting the license plate, extract it as the region of interest. Then, apply Optical Character Recognition (OCR) with Tesseract to read the text from images. This process is key to converting raw data into actionable information.

• Pipeline Development: Integrate all components to create a pipeline that handles both detection and OCR tasks seamlessly. This will form the core of your application's functionality.

• Web App Creation with Flask: Transform your project into a user-friendly web application using Flask, Python, HTML, and Bootstrap. Learn URL routing, template rendering, and inheritance to make your app interactive and responsive.

What You Will Learn:

✅ Building a Project in Python Programming: Gain practical experience in developing projects from the ground up using Python.

✅ Labeling Images for Object Detection: Understand how to prepare image data for training object detection models.

✅ Training Object Detection Model (InceptionResNet V2) in TensorFlow 2.x: Learn to use TensorFlow 2 to build and train state-of-the-art models for object detection tasks.

✅ Model Evaluation: Master the evaluation of your model's performance using industry-standard metrics.

✅ Optical Character Recognition with Pytesseract: Explore the capabilities of Tesseract in extracting text from images.

✅ Flask API: Learn to create a Flask API that serves your object detection and OCR needs.

✅ Flask Web App Development in HTML, Bootstrap: Develop a fully functional web application using HTML templates styled with Bootstrap.

✅ Train YOLO Model with Custom Data: Experiment with training the You Only Look Once (YOLO) model on custom datasets.

✅ Develop Web Application and Integrate YOLO Model: Integrate your trained YOLO model into a web application, allowing for real-time object detection and text extraction.

We understand that Computer Vision-Based Web Apps can be complex topics, and you might have questions. Our Q&A section is here to help clarify any doubts you may have.

Additional Resources:

All Notebooks, Python files, and resources used throughout the course are provided for your reference. These materials will serve as a valuable tool to deepen your understanding and aid in the development of your own projects.

Enroll now and embark on a journey to become proficient in developing License Plate Detection and OCR applications using Deep Learning, TensorFlow 2, Flask, and more! 🌟