Details
Based on the IMX500 Intelligent Vision Sensor
AI compact camera module Designed By Raspberry Pi
The Raspberry Pi AI Camera is a compact camera module from Raspberry Pi, based on the IMX500 Intelligent Vision Sensor. IMX500 combines a 12.3MP CMOS image sensor with onboard inferencing accelerator for a variety of common neural network models, enabling users to develop sophisticated vision-based AI applications without the need for a separate accelerator
The AI Camera transparently augments captured still image or video with tensor metadata, leaving the processor in the host Raspberry Pi free to perform other operations. Support for tensor metadata in the libcamera and Picamera2 libraries, and in the rpicam-apps application suite, make it easy for beginners to use, while offering advanced users unparalleled power and flexibility.
The Raspberry Pi AI Camera is compatible with all Raspberry Pi computers. The PCB outline and mounting hole locations are identical to those of Raspberry Pi Camera Module 3, while the overall depth is greater to accommodate the larger IMX500 sensor and optical subassembly.
Key features include:
- 12.3MP IMX500 Intelligent Vision Sensor with a powerful neural network accelerator
- Framerates:
- 2×2 binned: 2028×1520 10-bit 30fps
- Full resolution: 4056×3040 10-bit 10fps
- Sensor size: 7.857 mm
- Pixel size: 1.55 μm × 1.55 μm
- FoV: 78.3°±3°, with manual/mechanical adjustable focus
- Focal ratio: F1.79
- Module dimensions: 25 × 24 × 11.9 mm
- Integrated RP2040 for neural network firmware management
- Works with all Raspberry Pi models, using Raspberry Pi standard camera connector cable
| Sensor | IMX500 |
|---|---|
| Resolution | 12.3MP |
| Sensor size | 7.857 mm (type 1/2.3) |
| Pixel size | 1.55 μm × 1.55 μm |
| Horizontal/vertical | 4056 × 3040 pixels |
| IR cut filter | Integrated |
| Autofocus system | Manual adjustable focus |
| Focus range | 20 cm – ∞ |
| Focal length | 4.74 mm |
| Diagonal FOV | 78.3°±3° |
| Horizontal FOV | 66°±3° |
| Vertical FOV | 52.3°±3° |
| Focal ratio (F-stop) | F1.79 |
| Infrared sensitive | No |
| Output | Image (Bayer RAW10), ISP output (YUV/RGB), ROI, metadata |
| Input tensor maximum size | 640(H) × 640(V) |
| Input data type | "int8" or "uint8" |
| Memory size | 8388480 bytes for firmware, network weight file, and working memory |
| Framerate | 2×2 binned: 2028×1520 10-bit 30fps Full resolution: 4056×3040 10-bit 10fps |
| Dimensions | 25 × 24 × 11.9 mm |
| Ribbon cable length | 200 mm |
| Cable connector | 15pin × 1 mm FPC or 22pin × 0.5 mm FPC |
| Operating temperature | 0°C ~ 50°C |
The Raspberry Pi AI Camera works differently from traditional AI-based camera image processing systems, as shown in the diagram below:
The left side demonstrates the architecture of a traditional AI camera system. In such a system, the camera delivers images to the Raspberry Pi. The Raspberry Pi processes the images and then performs AI inference. Traditional systems may use external AI accelerators (as shown) or rely exclusively on the CPU.
The right side demonstrates the architecture of a system that uses IMX500. The camera module contains a small Image Signal Processor (ISP) which turns the raw camera image data into an input tensor. The camera module sends this tensor directly into the AI accelerator within the camera, which produces an output tensor that contains the inferencing results. The AI accelerator sends this tensor to the Raspberry Pi. There is no need for an external accelerator, nor for the Raspberry Pi to run neural network software on the CPU.
Compatible with all Raspberry Pi computers, based on the IMX500 Intelligent Vision Sensor to help users create impressive vision AI applications and neural network models.
The IMX500's tight integration with Raspberry Pi's camera software stack allows users to deploy their own neural network models. To get started, the Raspberry Pi Official has developed a guide to get you running either a pre-packaged or custom-made neural network model on the camera.
Create AI models and applications for the IMX500 Intelligent Vision Sensor and Raspberry Pi, then scale up to an enterprise deployment with AITRIOS.
Local Studio walks you through the necessary steps to efficiently label, train and produce AI models.
Weight: 0.018 kg
Quick Overview
- Raspberry Pi AI Camera x1
- Lens adjustment tool x1
- Raspberry Pi Camera Cable x1
- Raspberry Pi Camera and Display Cable x1
