HomeFree Udemy CourseCar Speed & Empty Parking Spot Detection with OpenCV, Pytorch & CNN...

Car Speed & Empty Parking Spot Detection with OpenCV, Pytorch & CNN | 100% Off Detecting Car Speed & Empty Parking Spot with Pytorch & CNN Free Course Coupon

Car speed detection, empty parking spot detection, OpenCV, Pytorch, Convolutional Neural Network, computer vision, motion detection, image processing

This comprehensive course teaches you how to build a car speed detection system and an empty parking spot finder using OpenCV, Pytorch, and CNN. Learn about computer vision applications in traffic management, vehicle detection, trajectory estimation, speed calculation, empty parking spot detection, motion detection, image processing, and more. Enroll now with coupon code “41870696C82BFE12F638” for a 100% discount (limited to the first 1000 learners).

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Course DescriptionDetails
Course NameDetecting Car Speed & Empty Parking Spot with Pytorch & CNN
Coupon Code41870696C82BFE12F638
Course Duration3 hours on-demand video
AccessMobile and TV
CertificateYes
Car Speed & Empty Parking Spot Detection with OpenCV, Pytorch & CNN | 100% Off Detecting Car Speed & Empty Parking Spot with Pytorch & CNN Free Course Coupon

What you’ll 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

This course includes:

  • 3 hours on-demand video
  • 4 downloadable resources
  • Access on mobile and TV
  • Full lifetime access
  • Certificate of completion

Description

Welcome to Detecting Car Speed & Empty Parking Spot with Pytorch & CNN course. This is a comprehensive project based course where you will learn step by step on how to build a cutting edge car speed detection system and empty parking spot finder using OpenCV, Convolutional Neural Network, and Pytorch. This course is a perfect combination between computer vision and motion detection, making it an ideal opportunity for you to practice your programming skills while integrating advanced computer vision technologies into traffic management and also open doors for future innovations in urban transportation. In the introduction session, you will learn about computer vision applications in traffic management, such as getting to know its use cases, technologies that will be used, and some technical limitations. Then, in the next session, you learn how the car speed detection system works? This section will cover vehicle detection, trajectory estimation, speed calculation, and speed limit check. In addition, you will also learn how empty parking lot detection systems work. This section will cover the full process from data collection to parking occupancy classification. Before starting the project, we will download a training dataset from Kaggle, the dataset contains hundreds or even thousands of images of occupied parking lots and unoccupied parking lots. We will use this dataset to train the model to be able to distinguish which parking lot has been occupied and which ones have not been occupied by cars. Once everything is ready, we will start the project section, in the first section, you will be guided step by step on how to build a vehicle speed detection system using OpenCV and Pytorch. In addition to that, we will also set a speed limit, so, whenever there is a car exceeding the speed limit, the system will immediately send you a notification and issue a speeding ticket. Meanwhile, in the second project, you will build an empty parking lot detection system using OpenCV and Convolutional Neural Network. Once we have built those detection systems, we will be conducting testing to make sure that they have been fully functioning and all programming logics have been implemented correctly.

First of all, before getting into the course, we need to ask ourselves this question: why should we build a car detection system and empty parking lot detection system? Well, here is my answer, regarding the speed detection system, its implementation can significantly aid law enforcement agencies in enforcing speed limits and enhancing road safety. By accurately detecting and recording vehicle speeds, law enforcement officers can effectively identify and address instances of speeding, thereby reducing the risk of accidents and promoting safer driving behaviors. Moreover, the data collected by the speed detection system can serve as valuable evidence in prosecuting traffic violations, ensuring accountability and deterrence among drivers.On the other hand, the empty parking lot detection system offers numerous benefits to individuals and communities. By providing real-time information on available parking spaces, this system helps to reduce time wasted searching for parking, particularly in densely populated urban areas.

Below are things that you can expect to learn from this course:

  • 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 a car speed detection system works. This section will cover vehicle detection, trajectory estimation, speed calculation, speed limit check, and speed ticket generator
  • Learn how empty parking spot detection systems work. This section will cover data collection, image preprocessing, feature extraction, object detection, and occupancy classification
  • 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 create function to detect speed
  • Learn how to build car speed detection system using OpenCV, Pytorch, and Single Shot Multibox Detector
  • 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 build empty parking spot detection system using OpenCV
  • Learn how to train empty parking spot detection system using Keras and Convolutional Neural Network
  • Learn how to create function to count how many empty parking spot
  • Learn how to extract parking spot coordinate using OpenCV
  • Learn how to conduct accuracy and performance testing on car speed and empty parking spot detection systems

Who this course is for:

  • People who are interested in building car speed detection system using OpenCV, Pytorch, and SSD
  • People who are interested in building empty parking spot detection system using OpenCV, Keras, and CNN

How to Get this course FREE?

Get a 100% Discount On Udemy Paid Courses by clicking on the Apply Here Button. This Course coupon code is automatically added to the Apply Here Button.

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Pratik Nagda
Pratik Nagdahttp://careerboostzone.com
My name is Pratik Nagda and I am a resident of the small town of Nallasopara in Maharashtra. I come from a very poor family and I live with my mom. My father was dead when I was in 4th grade. Due to that financial issue, I was forced to go to a hostel from the 5th to the 10th. I know the basics of blogging and all because in my final year of school, after that, when I came home, I had a great fight with my mom because she wanted to take me science and I wanted to take science. Finally, I convinced my mom. I have done engineering at St. John College of Engineering and Management, which is in Palghar. I still love my college very much. Even today, I keep sharing the experiences of my college with my readers. Today I am the owner of the CareerBoostZone English blogging site and through my blog, I have prepared a better employment platform for Readers I feel happy that I tried to empower readers by helping in employment and the development of the country. And my efforts are continuing towards success.
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