1. Hardware Devices (1) RK3399Pro Development Board: This is a development board launched by Rockchip, equipped with NPU (Neural-network Processing Units), supporting 8-bit and 16-bit operations, with a computing performance of up to 3.0 TOPs. Compared to similar NPU chips, its performance is leading by as much as 150%, and it is compatible with various … Read more
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
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
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
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