There are many robust ways to detect the number plate using Deep learning /machine learning using YOLO but in this repository i am going to introduce a basic number plate detector which doesn't require tons of training data
There are numerous applications in which recognition of number plate is requried as a primary or secondary task
Some of the applications include recognition of number plate for automatic fining system,for automatic entry of registered cars etc and many many.
This task can be achiverd in many ways one of the way was developed in the above code using open cv and easyocr.
EasyOCR, as the name suggests, is a Python package that allows computer vision developers to effortlessly perform Optical Character Recognition.
When it comes to OCR, EasyOCR is by far the most straightforward way to apply Optical Character Recognition:
The EasyOCR package can be installed with a single pip command.
The dependencies on the EasyOCR package are minimal, making it easy to configure your OCR development environment.
Once EasyOCR is installed, only one import statement is required to import the package into your project.
From there, all you need is two lines of code to perform OCR — one to initialize the Reader class and then another to OCR the image via the readtext function.
I HAVE PROVIDED SOME TEST IMAGES ALSO WHICH HELP THE USED TO TEST THE CODE
IN MY CASE THE ALGORITHM IS DETECTING THE NUMBER PLATE WITH 91.72% ACCURACY