ragishivanand / automatic-number-plate-recognition

PROCEDURE:

1. Install and Setup
2. Getting License Plate Data
3. Training a Object Detection Model
4. Detecting License Plates
5. Applying OCR to Text
6. output ROI's and Results

working process :

for this project we will be using two key libraries for Automatic Number Plate Detection

1 first we will use object detection to find a region of intrest

2 then we will use Easy OCR to extract the text

use easy ocr to extract text

Install

There are two key dependencies we will need to install to getup and running for this.

#Setup Tensorflow Object Detection

Step 1. Clone this repository: https://github.com/nicknochnack/TFODCourse

git clone https://githubhttps://github.com/nicknochnack/TFODCourse.git

#Install Easyocr !pip install easyocr

now open the command prompt

now open the d drive and check ANPR folder

creating a virtual environment

now open anprsys folder and check

now activating the virtual environment

now open the jupyter note book

now close the jupyter notebook

now enter #{control + c} in command prompt

now install

now open the jupyter notebook

now you can see the anprsys in our machine learning jupyter

now installing tensorflow object detection:

now open the training and detection.ipynb

change the kernel to anprsys

setup paths

now check tfod folder there is tensor folder

Download TF Models ,clone the github repository,install all pip codes , run all the codes :

automatic-number-plate-recognition's Issues

ocr

tensor flow object detection

4 folders

setup paths

anprsys

44

trrr

123

tfod

command prompt1

real time web cam

command prompt

jupyter notebook

trrr

22

creating a virtual encironment

install

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