Detecting Car Speed & Empty Parking Spot with Pytorch & CNN
Build car speed detection system and empty parking spot detection system using OpenCV, Pytorch, CNN, Keras, and SSD
4.77 (11 reviews)
2,842
students
3 hours
content
May 2024
last update
$39.99
regular price
What you will learn
Learn how to build car speed detection system using OpenCV, Pytorch, and Single Shot Multi Box Detector
Learn how to train empty parking spot detection system using Keras and Convolutional Neural Network
Learn how build empty parking spot detection system using OpenCV
Learn how to extract parking spot coordinate using OpenCV
Learn how a car speed detection system works. This section will cover vehicle detection, trajectory estimation, speed calculation, and speed limit check
Learn how empty parking spot detection systems work. This section will cover data collection, image preprocessing, feature extraction, and object detection
Learn how to create function to detect speed
Learn how to set speed limit and check if the speed exceeds the speed limit
Learn how to create and issue speeding ticket
Learn how to calculate frame rate using OpenCV
Learn how to create function to count how many empty parking spot
Learn about computer vision applications in traffic management, such as getting to know its use cases, technical limitations, and technologies that will be used
Learn how to play video using OpenCV
Learn how to detect motion using OpenCV
Learn how to perform image processing using OpenCV
Learn how to conduct accuracy and performance testing on car speed and empty parking spot detection systems
Screenshots
5953692
udemy ID
5/2/2024
course created date
5/15/2024
course indexed date
Muhammad
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