From Training to Deployment: Custom YOLOv10 Models for NI LabVIEW Applications
In this comprehensive tutorial, we focus on training a custom object detection model using YOLOv10, the latest in YOLO technology, within ANS Model Training Studio (ANSTS). This video demonstrates how to efficiently train YOLOv10 models for PCB inspection and deploy them into LabVIEW applications for real-time AI-driven object detection.
YOLOv10 for LabVIEW is an industry-first feature offered by ANSTS, making this tutorial essential for anyone looking to leverage cutting-edge AI technology in their projects.
What You'll Learn:
How to train a custom object detection model using YOLOv10 within ANSTS
Verifying and labeling your PCB dataset using the ANS Labelling Tool
Optimizing model training for YOLOv10
Real-time monitoring of YOLOv10 training progress and validation
Exporting trained YOLOv10 models for both GPU and CPU inferencing
Deploying YOLOv10 models natively into LabVIEW using the ANS Deep Learning Toolkit (ANSDL)
Integrating AI BOX to enhance LabVIEW applications with real-time inferencing via TCP/IP
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