The Real-Time Plate Number Detection Project was developed using Python and OpenCV.
License Plate Recognition is an image-processing technology used to identify vehicles by their license plates.
This technology is widely applied in various security and traffic management systems.
The Plate Number Detection system in Python aims to recognize license plates.
To achieve this, OpenCV is used to detect the plates, while Python’s Pytesseract library extracts the characters and digits from them.
If you are new to Python programming and are unfamiliar with using a Python IDE, I have compiled a list of the best Python IDEs for Windows, Linux, and macOS to help you get started.
I also provide instructions on how to download and install the latest version of Python on Windows.
To begin executing the Real-Time Plate Number Detection project, make sure you have installed Python 3.9 and PyCharm on your computer.
How to run the Real-Time Plate Number Detection using OpenCV in Python: A step-by-step Guide With Source Code
These are the steps on how to run Real-Time Plate Number Detection OpenCV Python With Source Code
- Download the source code below.
First, download the given source code and unzip the source code.
- Import the project to your PyCharm IDE.
Next, import the source code you’ve downloaded to your PyCharm IDE.
- Run the project.
Lastly, run the project with the command “py main.py”
from skimage.io import imread
from skimage.filters import threshold_otsu
import matplotlib.pyplot as plt
import imutils
import cv2
from skimage import measure
from skimage.measure import regionprops
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import os
import shutil