![]() "Enabling GPU" in this case means "re-enabling GPU support that's already installed and working". For those having issues with GPUs, the dashboard now provides the means to enable / disable a module, or enable / disable GPU support.Image handling improvements on Linux, multi-thread ONNX on.New, simplified setup and install scripts.Code and run natively directly on the Raspberry Pi using VSCode natively Optional YOLO 3.1 Object Detection module for older GPUs.Improved performance for the Object Detection modules.Our new Module Registry: download and install modules at runtime via the dashboard.2.0.6: Corrected issues with downloadaable modules installed.Adding a New Module to CodeProject.AI Server.How to Train a Custom YOLOv5 Model to Detect Objects.Solutions for Common Issues with Blue Iris and CodeProject.AI Server.Guide to Package Detection in CodeProject.AI with Blue Iris.CodeProject.AI Server, Blue Iris and Face Recognition.How to Run CodeProject.AI Server in Docker. ![]() Setting Up a Wyze Cam with Blue Iris and CodeProject.AI Server.Here are a few articles on how to use CodeProject.AI Server: This is the main documentation page for CodeProject.AI Server which includes links to the latest version, a quick guide to setting up and running CodeProject.AI Server in Visual Studio Code or Visual Studio. It details what it is, what's new, what it includes, and what it can do. This is the main article about CodeProject.AI Server on the CodeProject site. There is an ongoing thread about CodeProject.AI Server, but recently someone asked for a thread trimmed down to the basics: what it is, how to install, how to use, and latest changes.
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