Car Number Plate Detection and Information Provider System
Task Description:
_*Task 08*_ 👨🏻💻
*Team Task*
*Team Members*
👉Create a model that will detect a car from a video or an image and recognize characters on number plate of the car .
👉Secondly , it will use the characters and fetch the owners information using RTO API’s .
👉Create a Web portal where all this information will be displayed (using html,css)
Technologies Used:
1.Computer Vision(OpenCV)
2.Amazon Textract and Amazon S3
3.Flask
Computer Vision:
Computer Vision, often abbreviated as CV, is defined as a field of study that seeks to develop techniques to help computers “see” and understand the content of digital images such as photographs and videos.Computer vision works much the same as human vision human except humans have a head start. Human sight has the advantage of lifetimes of context to train how to tell objects apart, how far away they are, whether they are moving and whether there is something wrong in an image.
Computer vision trains machines to perform these functions, but it has to do it in much less time with cameras, data and algorithms rather than retinas, optic nerves and a visual cortex. Computer vision needs lots of data. It runs analyses of data over and over until it discerns distinctions and ultimately recognize images. For example, to train a computer to recognize dog , it needs to be fed vast quantities of dogs images in differen positions to learn the differences and recognize it.
Two essential technologies are used to accomplish this: a type of machine learning called deep learning and a convolutional neural network (CNN).
Implementation:
Computer Vision is used to identify car from the user’s uploaded image. Since there is a possibility that there are multiple objects in the image which the user has uploaded. So for car detection we have used CV and along with these it will detect the portion of number plate from that car.
Amazon Textract OCR:
In simple terms, AWS Textract is a deep learning-based service that converts different types of documents into an editable format. Consider we have hard copies of invoices from different companies and store all the vital information from them on excel/spreadsheets. Usually, we rely on data entry operators to manually enter them, which is hectic, time-consuming, and error-prone. But using Textract, all we need to do is upload our invoices to it and in turn, it returns all the text, forms, key-value pairs, and tables in the documents in a more structured way. Below is a screenshot of how AWS does intelligent information extraction:
Not just typed text, AWS Textract also identifies handwritten texts in the documents. This makes information extraction more useful, as in some cases extracting handwritten text is more complicated to extract than typed ones.
Implementation:
We have successfully detected the number plate and cropped it as well After this we need this identify the text of that number plate. For this we are using Amazon Cloud Textract,one of the powerful service used for extracting the text from the image. It helps us to identify the number plate.
AWS S3 Service
Amazon S3 or Amazon Simple Storage Service is a service offered by Amazon Web Services(AWS) that provides object storage through web interface.Amazon S3 (Simple Storage Service) provides object storage, which is built for storing and recovering any amount of information or data from anywhere over the internet. It provides this storage through a web services interface. While designed for developers for easier web-scale computing, it provides 99.999999999 percent durability and 99.99 percent availability of objects. It can also store computer files up to 5 terabytes in size.
Implementation:
When user uploads the image it get stored in S3 bucket and then we download it using curl command in our program. After cropping the number plate part we again send that cropped image into the S3 bucket so that it gets convenient to use Textract service and get the output.
Flask:
Flask is a popular Python web framework, meaning it is a third-party Python library used for developing web applications.
Implementation:
In this task we have used flask to create a web portal which is asking user to upload the image of car and displays all the information of the car like owner name, insurance, car company name, etc.
We have created two routes one is home and second is upload. When we search for the website on link generated by flask run command i.e http://127.0.0.1:5000 then we are on the home page and then after uploading the image it we will be automatically landed to the upload page.
Flow of the Task
Let’s understand the flow of this task.
1.First the code of flask will get run(app.py)
2.When user upload the image it get saved in S3 bucket.
3.We will first download this image with the help of curl command.
4.Then we have called the function detected number plate and pass that image to that function. This function is available in the Car_Number_Plate_Detection_Code.py
This file has been imported as a module in the flask code (app.py)
This function returns the number plate.
5.Now we have called rto function available in that same module. We pass that detected number plate into this function and get the information as an output.
Video of this Task:
Link:
https://youtu.be/nw5BRv11-rg
GitHub Url:
Link:
https://github.com/mahekbatra/Car-plate-recognition
