Fall Detection App - Official YOLOv7 Pose Estimation
Offered By: Augmented Startups via YouTube
Course Description
Overview
Learn how to implement a Fall Detection App using YOLOv7 Pose Estimation in this comprehensive tutorial. Explore the potential of computer vision to save lives by creating a system that alerts health providers when a person falls. Dive into the implementation details, including YOLOv7 Pose Estimation, UI design concepts, and push-up counting logic. Follow along as the instructor guides you through the project files, library imports, icon loading, and fall detection coding. Witness the test run and discover how to apply the same techniques to yoga pose estimation. Gain valuable insights into YOLOv7's superior performance in object detection, boasting 56 FPS on V100 and 55.9% AP, while being 120% faster than YOLOv5.
Syllabus
Theory
Altium Designer
Downloading the course
Inside project files
Import Libraries
Load Icon
Fall Detection Coding
Test Run
Yoga Pose Estimation
Taught by
Augmented Startups
Related Courses
Computer Vision: The FundamentalsUniversity of California, Berkeley via Coursera Programming Languages
University of Virginia via Udacity Learn to Program: Crafting Quality Code
University of Toronto via Coursera Computational Photography
Georgia Institute of Technology via Coursera Algorithms: Design and Analysis, Part 2
Stanford University via Coursera