Automated Car Parking Detection
- 0 Collaborators
Devised algorithms that can detect cars parked at multiple parking spots, compare if two cars are same or not, predict the colour of a car and output each car that was detected and how long it was parked for (approximately) within a given time interval. ...learn more
Project status: Concept
Groups
Student Developers for AI
Intel Technologies
Intel CPU
Overview / Usage
In this project I tried solving many aspects of real world problems associated with security in parking lots. The first thing I solved was detecting the presence of a car at any given parking spot, secondly, I solved finding similarity between two cars, finding colour of a car and lastly, finding out each car that was detected and how long it was parked for (approximately) within a given time interval at a particular parking spot.
My model can be used in surveillance at parking spaces and it can also be enhanced to predict any unusual activity.
Methodology / Approach
I utilized various technologies like OpenCV, Numpy and state of the art, Neural Networks. For detecting cars, I used YOLO network and for rest of the task I used OpenCV algorithms to solve them.
For more information, please go to my Github account!
https://github.com/chiravdave/Deep-Learning/tree/master/Car_Parking_Detection
Technologies Used
Technology Stack: Python, OpenCV, Numpy, Convolutional Neural Network
Repository
https://github.com/chiravdave/Deep-Learning/tree/master/Car_Parking_Detection