Raspberry pi YOLO Object Detection : yolov3-tiny-416

more info http://raspberrypi4u.blogspot.com/2022/08/raspberrypi-yolo-objectdetection.html YOLOv3-tiny-416 Performance : 7.x fps Hardware · Raspberry Pi Board (4B ) · Intel Neural Compute Stick 2 · SD Card 32GB · 5V DC. 2A Power Supply Software · OS Raspbian 10 ( Buster ) · Python 3.7.3 · OpenVINO Toolkit 2020.3 · OpenCV 4.0.0 What is a YOLO object detection? When it comes to deep learning-based object detection, there are three primary object detectors you’ll encounter: R-CNN and their variants, including the original R-CNN, Fast R- CNN, and · · Faster R-CNN · Single Shot Detector (SSDs) · YOLO First introduced in 2015 by Redmon et al., their paper, You Only Look Once: Unified, Real-Time Object Detection, details an object detector capable of super real-time object detection, obtaining 45 FPS on a GPU. You Only Look Once: Unified, Real-Time Object Detection https://arxiv.org/pdf/1506.02640v3.pdf YOLOv3 improved on the YOLOv2 paper and both Joseph Redmon and Ali Farhadi, the original authors, contributed. Together they published YOLOv3: An Incremental Improvement https://pjreddie.com/darknet/yolo/ The original YOLO papers were are hosted here https://pjreddie.com/darknet/yolo/ Author: Joseph Redmon and Ali Farhadi Released: 8 Apr 2018 We’ll be using YOLOv3 in this blog post, in particular, YOLO trained on the COCO dataset. The COCO dataset consists of 80 labels. Install OpenVINO™ toolkit for Raspbian* OS https://docs.openvino.ai/latest/openvino_docs_install_guides_installing_openvino_raspbian.html สอบถาม เพิ่มเติม : อดุลย์ นันทะแก้ว 081-6452400 LINE : adunnan Page : https://www.facebook.com/softpowergroup FaceBook : https://www.facebook.com/adun.nantakaew email : [email protected]