Table 3 Hardware and software parameters of PB-Yolov5s.
From: Real-time detection of particleboard surface defects based on improved YOLOV5 target detection
Hardware environment | Software environment | ||
|---|---|---|---|
Memory | 256 GB | System | Windows Server 2012 R2 Standard |
CPU | Intel(R) Xeon(R) Gold6152 CPU@2.10 GHz | Environment configuration | Python 3.8.3 |
GPU | NIVIDIA Quadro RTX 8000 | Pytorch dynamic development framework | |
