Get started with Raspberry Pi AI Camera

Set up your Raspberry Pi AI Camera and start creating your vision AI solution

Set up your AI Camera

Get your camera ready for AI projects

Start by setting up and installing your Raspberry Pi AI Camera. For detailed instructions, visit the Raspberry Pi website.

Video tutorial

Quickstart with Raspberry Pi AI Camera

Try AI models

Evaluate, create, and train AI models

Next, start testing AI models on the Raspberry Pi AI Camera. Whether you're a beginner or an experienced developer, you can choose from codeless development tools, use pretrained models, or build your own to quickly evaluate and deploy your AI model.

Choose from 3 options:

Train AI models with Brain Builder for AITRIOS ❯

If you want to evaluate your AI model with no coding, try Brain Builder for AITRIOS.

Use pretrained models from Model Zoo ❯

Browse and download precompiled AI models, already trained and ready to deploy.

Get started with AI models ❯

Deploy AI models to Raspberry Pi AI Camera with IMX500.

Related docs

IMX500 Converter ❯

IMX500 Packager ❯

Get Started with Brain Builder for AITRIOS ❯

Explore use cases

Learn from real-world applications

Discover real-world applications built with the Raspberry Pi AI Camera featuring the IMX500 Intelligent Vision Sensor, from smart facilities and cities to retail and wellbeing. Explore the use cases on GitHub to accelerate development and spark ideas for your own project.

Smart facility

An edge application that runs on Raspberry Pi and utilizes the IMX500-based AI Camera to identify and track high visibility vests in real-time.

View the code on GitHub ❯

Smart city

An edge application to track cars and analyze if they are parked in a marked parking space, to ensure efficient and organized parking solutions.

View the code on GitHub ❯

See all use cases »

Next: More on AI model development

Retrain and optimize models tailored to your solution

Take your AI project further by customizing models for your specific use case. Learn how to retrain and optimize AI models using hands-on tutorials.

image illustrating tutorial for retraining classification models

Retrain classification models

This tutorial guides you step by step through training and quantizing a MobileNet model with a custom dataset.

See the tutorial on GitHub ❯

Run the tutorial on Google Colab ❯

image illustrating tutorial for retraining object detection models

Retrain object detection models

Learn how to train and quantize NanoDet with a custom dataset for IMX500 in this step by step tutorial.

See the tutorial on GitHub ❯

Run the tutorial on Google Colab ❯

See all tutorials »