Detecting Car Speed & Empty Parking Spot with Pytorch & CNN

🚘 Master Traffic Management with AI: Detecting Car Speed & Empty Parking Spots with Pytorch & CNN

Course Headline:

Build a state-of-the-art car speed detection system and an empty parking spot finder using OpenCV, Convolutional Neural Network (CNN), and Pytorch. Learn the ins and outs of traffic management through advanced computer vision! 🚦✨

Course Description:

Welcome to the "Detecting Car Speed & Empty Parking Spot with Pytorch & CNN" course! This is not just another project-based course; it's a deep dive into the world of computer vision and motion detection, where you can enhance your programming skills while exploring the latest in AI for traffic management. 🛣️

Why This Course? Understanding the importance of efficient traffic management is crucial, especially as urban populations grow. The car speed detection system we'll build can empower law enforcement to enforce speed limits and promote road safety. While the empty parking spot detection system aims to alleviate parking hassles in busy areas, making life easier for everyone involved. 🅿️🚗

What You'll Learn:

• Computer Vision Applications in Traffic Management: Get introduced to use cases, technologies (like OpenCV), and understand some technical limitations you might encounter.

• Car Speed Detection System: Uncover the mechanics behind vehicle detection, trajectory estimation, speed calculation, and setting up speed limits. You'll also learn how to generate a speeding ticket if necessary.

• Empty Parking Spot Detection System: From data collection to occupancy classification, this section covers everything you need to know about detecting available parking spots using image preprocessing, feature extraction, object detection techniques, and more.

Hands-On Learning:

• 🎥 Introduction Sessions: Dive into traffic management applications and get a roadmap of what's to come.

• 🚓 Car Speed Detection Project:

  • Play and process video footage with OpenCV.
  • Detect motion and vehicles within the video stream.
  • Calculate frame rate for real-time monitoring.
  • Build a speed detection system using Pytorch and SSD (Single Shot Multibox Detector).
  • Set up speed limits and detect when speeds exceed them.
  • Generate and issue digital speeding tickets.

• 🧭 Empty Parking Spot Detection Project:

  • Collect and preprocess data using a provided dataset from Kaggle.
  • Train your model for parking spot classification with Keras and CNN.
  • Detect empty parking spots using OpenCV and your trained model.
  • Count the number of available parking spaces.
  • Extract coordinates of detected parking spots.

• 🔍 Accuracy & Performance Testing: Ensure your car speed and empty parking spot detection systems are working correctly by conducting rigorous tests.

Skills You'll Acquire:

• Computer Vision Techniques: Master OpenCV for video playback, motion detection, and image processing.

• Deep Learning Models: Get hands-on experience with Pytorch and Keras to build robust AI models.

• Data Collection & Management: Learn how to handle datasets for training your models effectively.

• Object Detection & Classification: Understand the principles behind detecting objects (like cars and parking spots) and classifying their status (empty or occupied).

• Real-World Applications: Apply your newfound knowledge to solve real-world problems in traffic management.

Join us on this exciting journey to transform the way we interact with urban spaces using the power of AI and computer vision! 🚀📊