: If your main Blue Iris machine is struggling, you can easily offload CodeProject.AI to another server or a Docker container on a separate machine.
Open the global settings in Blue Iris and navigate straight to the tab: Check the box to enable CodeProject.AI .
The combination of and Blue Iris is widely considered the gold standard for self-hosted, local computer vision in home security. It acts as a gatekeeper for your security cameras, verifying motion alerts by running them through artificial intelligence to ensure you only get notified for things that actually matter (like people, cars, or dogs) instead of shifting shadows or blowing leaves. codeproject blue iris verified
: The system can be configured to only notify the user if a "Person" or "Vehicle" is detected, ignoring environmental noise. Verified Detection
Finally, configure how Blue Iris responds to verified alerts: : If your main Blue Iris machine is
Have you achieved verified status? Share your confidence levels and custom model setups in the comments below.
: CodeProject.AI allows for different "models"—small, medium, or large—depending on the desired accuracy versus speed. Blue Iris Configuration It acts as a gatekeeper for your security
: All image processing happens on your local hardware, ensuring privacy and speed.
The "verified" ecosystem shines brightest when you explore custom AI models and advanced integrations. The CodeProject community has created and documented solutions for nearly every surveillance need.
: AI processing is computationally heavy. Users often add dedicated GPUs or specialized hardware like the Coral Accelerator to ensure notifications are delivered in near real-time. Model Selection
Before diving into installation, let's break down the terminology. When users refer to , they are typically discussing three distinct concepts: