Fall Detection with YOLOv7 Pose Estimation Demo

Not everyone has an Apple Watch⌚️ for Fall Detection, but we can use a camera with some AI. Whether you’d want a camera watching📷 you 24/7 is a topic for another day however this technology is essential for frail care. ==================== If you would like to code apps like this for health care applications⛑, I can show you, from scratch, step-by-step using YOLOv7. 👾Click this link to learn - 🏂Or get started with YOLOv7 for Free ==================== You may have an elderly👴🏼🧓🏼 or frail loved one👨🏻‍🦽 who does not own a smartwatch and even if they do, they don’t want to wear (or maybe forget to wear) the device. This is where we can apply YOLOv7 Pose Estimation for Fall Detection, which can inform you or a health care provider🧑🏻‍⚕️ that a person has fallen. This is so that they may attend to the patient as soon as possible🩺. When it comes to health🏥, every second counts⏱, and the sooner you are notified of the person falling, the sooner they can be cared for or treated⚕️. I have put together a compilation of people falling, or rather intentionally falling in a martial arts setting. I will post another video demo, to relate more to actual falling events soon. ☕️ Show your appreciation for this tutorial - Please Buy me a Coffee/Chai so I can create more free tutorials for you 😊 - ✅YOLOv7 surpasses all known object detectors (speed & accuracy) ✅56 FPS V100, 55.9% AP ✅120% faster than YOLOv5 ✅State-of-the-Art ⭐ JOIN our Membership to get access to Source Code: ===Product Links=== ✔️ Roboflow - ✔️ Webcam - ✔️ Deep Learning PC - ✔️ OpenCV Python Books - ✔️ Camera Gear - ✔️ Drone Kit - ✔️ Raspberry Pi 4 - ✔️ OpenCV AI Kit - ✔️ Arduino Electronics kit - ------------------------------------------------------------ Buy me a Coffee/Chai☕️ ► Whatsapp Computer Vision Tribe ► Chat to us on Discord ► Interact with us on Facebook ► Check my latest work on LinkedIn ► ------------------------------------------------------------ #yolov7 #objectdetection #ubuntu