Computer Vision - Object Detection on Videos - Deep Learning

Quick Starter on Object Detection and Image Classification on Videos using Deep Learning, OpenCV, YOLO and CNN Models

Ratings: 4.46 / 5.00




Description

Welcome to the course "Object Detection on Videos - Deep Learning" that provides an end-to-end coverage of Machine Learning on videos through Video analytics, Object Detection and Image Classification. It is a complete hands-on tutorial that teaches how to implement Video Analytics using the 3-step process of Capture, Process and Save Video. This course helps you to understand various Object Detection Models as well as teach how to implement them for a real-time case study of Social Distancing and last but not the least, take a deep dive into steps involved in using Deep Learning Models and Transfer Learning. By the end of the course, you will also learn how to create a model on face mask detection using Image Classification and leverage it to implement a solution of face mask detection.


This course is a must-have for all the developers in machine learning domain because of:

  • Dedicated In-Course Support is provided within 24 hours for any issues faced

  • Line-By-Line Code Walkthrough for object detection implementation on videos and training a model for image classification

  • Comprehensive Coverage of Object Detection and Image Classification Models

  • Working source code for People Footfall Tracking and Automatic Parking Management project


Here is the list of  key topics and projects we will be learning:

  • Video Analytics Architecture

  • Euclidean Distance

  • Object Detection Models - Haar Cascade, HOG, Faster RCNN, R-FCN, SSD, YOLO

  • Object Detection Model Implementation on Videos with Haar Cascade, HOG and YOLO

  • Image Classification

  • Training Image Classification Model on Google Colab

  • Image Classification Implementation on Videos with Trained InceptionV3 Model

  • Object Tracking with SORT Framework

  • People Footfall Tracking Solution

  • Automatic Parking Management Solution

What You Will Learn!

  • Learn how to implement Video Analytics using Deep Learning concepts
  • Understand how to implement Object Detection Models on Videos using Python
  • Build your own Deep Learning model using Transfer Learning for Image Classification
  • Executable Code of Faster RCNN, YOLO, HOG and Haar Cascade for Object Detection
  • Build a technical solution containing both Object Detection and Image Classification
  • Develop Image Classification Model using InceptionV3 model architecture
  • Learn to implement SORT Framework for Object Tracking
  • Executable Code of SORT for People Footfall Tracking and Automatic Parking Management

Who Should Attend!

  • Beginners to Data Science
  • Machine Learning Professionals
  • Developers willing to transition into Machine Learning
  • Anyone looking to implement Machine Learning on Videos
  • Anyone looking to become more employable as a Data Scientist