Object Detection using CNN Model
Task Description 📄
📌 In this task :
👉Create a model that will detect a car in a live stream or video and recognize characters on the number plate of the car.
👉Secondly, it will use the characters and fetch the owner's information using RTO APIs.
📌 Note: You may create your own detection model.
Steps Followed:
- Take image as input
- Convert image in a black and white format
- Image Noise Reduction
- Locating the Number Plate from the Image and cropping it
- Pass the Image in Prediction Model for Prediction
- Print the Output
Let’s talk about how it can be implemented?
In the first, step we have to create a model that will detect a car in a live stream or video and then recognize the characters on the number plate of the car.
Secondly, it will use the characters and fetch the owner’s information using RTO APIs.
Here, we used the flask framework for implementing it as a web application. Thereby, anyone can upload an image/video to detect the number plate of the vehicle. Once the required file is uploaded, first it detects the number plate. Then, find the corresponding vehicle details by using an API of RTO.
For more details visit here:
https://github.com/ajmalmohammedn/summer_program_2021/tree/main/Task-8
Thank you !!