Before diving into installation, let's break down the terminology. When users refer to , they are typically discussing three distinct concepts:
CodeProject.AI operates as a completely local, self-hosted web service. It never transmits your private camera feeds to the cloud.
Getting your project verified is a straightforward process: codeproject blue iris verified
This all-in-one model is designed to detect a wide array of common objects and animals, including person, bicycle, car, motorcycle, bus, truck, bird, cat, dog, horse, sheep, cow, bear, deer, rabbit, raccoon, fox, skunk, squirrel, and pig. This model is ideal for general-purpose surveillance and home security, as it covers most daily scenarios.
Ensure the CodeProject.AI service is set to start automatically with Windows. 3. Configuring Blue Iris for Verified AI Open Blue Iris and go to Settings > AI . Select CodeProject.AI as your AI provider. Before diving into installation, let's break down the
Setting up ALPR is a more advanced but highly "verified" enhancement. Community members have built complete, free ALPR database platforms to complement a Blue Iris + CodeProject.AI setup, allowing you to store and search license plate data. This involves installing a dedicated ALPR module in CodeProject.AI and then configuring a Blue Iris camera to send snapshots of passing vehicles for plate analysis.
Here’s a proven, community-verified guide to getting your system up and running. The process is straightforward and can be broken down into a few key steps. Getting your project verified is a straightforward process:
Blue Iris connects, but AI always says "nothing found" or confidence is 0%. Fix: Ensure your motion zone is large enough. AI needs a minimum pixel size (usually > 2000 pixels). If the person is 50 pixels tall, the model cannot identify them. Increase the "Break time" or adjust the motion detection sensitivity.
: The AI analyzes the image to identify specific objects such as people, cars, dogs, or delivery trucks .