Object Identification Showdown: AI Hat + (Raspberry Pi 5) vs AI Camera (Raspberry Pi 4) скачать в хорошем качестве

Object Identification Showdown: AI Hat + (Raspberry Pi 5) vs AI Camera (Raspberry Pi 4)

It’s a head-to-head AI hardware battle! In this video, we test the Raspberry Pi AI Hat + on a Pi 5 against the Raspberry Pi AI Camera on a Raspberry Pi 4 to find out which one delivers better object identification. We put both systems through the same 15+ item test including: Bottle, Cat, Wine Glass, Bowl, Vase, Spoon, Cup, Chair, Car, Suitcase, Potted Plant, Scissors, Handbag, Mouse, Keyboard, Backpack, and Hair Dryer. 👀 Which setup performs best? Watch to find out! 📺 Watch These First (Prerequisite Videos): • Raspberry Pi 5 setup with Active Cooler →    • Getting Started with Raspberry Pi 5 + Acti...   • Assembly and setup of the Raspberry PI AI Hat+ →    • Raspberry Pi AI Hat + Unboxing, Setup & Ob...   • Assembly and setup of the Raspberry Pi AI Camera →    • Object Detection Raspberry Pi AI Camera   📚 Resources & Documentation: • Raspberry Pi AI Camera documentation → http://www.raspberrypi.com/products/a... • List of detectable objects (COCO labels) → https://github.com/raspberrypi/picame... • AI Hat + Product Documentation → https://www.raspberrypi.com/products/... 🧰 Materials Needed: • Raspberry Pi 5 kit → https://amzn.to/4lAiYdT • Raspberry Pi AI Hat → https://amzn.to/46h6V0r • Raspberry Pi Camera → https://amzn.to/4lqIPoh • Camera cables → https://amzn.to/3TNO9X6 • 3D printed camera mount → https://www.thingiverse.com/thing:410... • Mouse & Keyboard → https://amzn.to/4kc8WOL • Monitor → https://amzn.to/44qy0Mn • microSD card → https://amzn.to/4lw9non • Small Screwdriver Set → https://amzn.to/4lteSEb • Raspberry PI AI Camera → https://amzn.to/3Ti8XWG 📘 My book: A Woman’s Guide to Winning in Tech → https://amzn.to/3YxHVO7 Affiliate Disclosure: As an Amazon Associate, I earn from qualifying purchases. Using these links helps support my channel at no extra cost to you. Thank you! 👍 Like, subscribe, and comment with which system YOU think won the object identification challenge!