Implementing Object Detection with Yolov5 on Raspberry Pi

Implementing Object Detection with Yolov5 on Raspberry Pi

Click on the "Xiaobai Learns Vision" above, and choose to add "Star" or "Top" Heavyweight content delivered to you in real-time 1. Task Description Implement object recognition using machine vision, with the Raspberry Pi as the main controller, issuing different commands to the lower machine based on different recognition results to control the operation of … Read more

Animal Target Detection Based on YOLOv5 and Raspberry Pi 4B

Animal Target Detection Based on YOLOv5 and Raspberry Pi 4B

Object detection is of great significance in the field of computer vision. YOLOv5 (You Only Look One-level) is a representative method among object detection algorithms, renowned for its efficiency and accuracy, and has shown outstanding performance in various object detection tasks. This article will detail how to train the YOLOv5 model on a more powerful … Read more

Deploying Yolov5 on Raspberry Pi for Object Detection

Deploying Yolov5 on Raspberry Pi for Object Detection

Click the card below to follow the “New Machine Vision” public account Important content delivered at the first time 1. Task Description Realize the identification of workpieces through machine vision, using Raspberry Pi as the host, issuing different instructions to the lower machine based on different identification effects, controlling the entire machine operation. The process … Read more

Deploying and Evaluating the RK3588 YOLOv5s Model

Deploying and Evaluating the RK3588 YOLOv5s Model

MEGAWAY TECHNOLOGY RK3588 YOLOv5s Model Deployment and Evaluation 01/ Model Overview Model Name: YOLOv5s Model Type: Classification Model Official Repository: GitHub – ultralytics/yolov5: YOLOv5 in PyTorch> ONNX > CoreML > TFLite V7.0 Model Parameters (PARAMS): 7225885 Model Computation (FLOPS): 16.4 GFLOPs Deployment Device: RK3588 Deployment Environment: Ubuntu20.04/rknn_toolkit2 V1.6.0/OpenCV4.5.1 02/ Model Analysis YOLOV5 model outputs three … Read more