Overview

In this application you will learn how to build a complex, multi-model application that can detect and read license plates from video. The corresponding Colab Notebook will guide you through the following steps from scratch so you can build your very own end to end AI vision app.

1. Frame Extraction
2. License Plate Detection
3. Image Cropping
4. OCR and Data Retrieval

By the end of this notebook, you will not only will have a functioning license plate reader, but you’ll also possess foundational knowledge and techniques that are transferable to a variety of other computer vision applications. Whether you’re aiming to recognize faces, track objects, or read text from images, the principles and methods showcased here will serve as a valuable cornerstone for your future projects.

Check out the video below for a quick walkthrough of the end to end app.

Here are 10 project ideas that can leverage these techniques:

1. Face Recognition Security System: Use the frame extraction and object detection components to identify and authorize faces for a secure entry system.
2. Real-Time Traffic Monitoring: Combine the license plate detection and OCR components to monitor traffic and automatically detect vehicles that are speeding or breaking other traffic rules.
3. Retail Analytics: Utilize the object tracking technique to analyze customer behavior in a store, such as identifying hotspots where people spend the most time.
4. Lost and Found Pet Detection: Adapt the system to identify lost pets by scanning and recognizing tags or special markers.
5. Handwriting Recognition: Leverage the OCR component to develop a system that can digitize handwritten notes.
6. Text Translation App: Use the OCR part to read text from images and then translate it into different languages in real-time.
7. Vehicle Type Classification: Expand the license plate detection model to classify vehicle types (sedan, SUV, truck, etc.) for parking management or toll collection.
8. Food Recognition for Caloric Estimation: Use the image cropping and object detection modules to identify food items on a plate and estimate caloric intake.
9. Luggage Identification in Airports: Implement a system in airports to automatically detect and track luggage by reading identification tags, helping to prevent loss or theft.
10. Sign Language Recognition: Apply frame extraction and object detection to recognize hand gestures for a sign language translation application.