EyeCloudAI CDK is an open source edge-AI camera development kit for applications where privacy, real-time performance, reliability, and flexibility are paramount. With this camera-development kit (CDK), developing and deploying custom edge-AI camera solutions is easy. We’ve taken care of the AI optimization, sensor tuning, optics, tooling, and supply chain management so you can focus on your application.

• EyeCloudAI CDK is based on the Intel Movidius Myriad X VPU and is compatible with the Intel Distribution of OpenVINO Toolkit. We are offering two versions of our core board. The first model is designed to be used while connected to an external host device or integrated into a larger system, be it a laptop, a single-board computer (SBC), a robot, or something else. The second model supports independent, stand-alone operation by allowing the CDK to boot from an 8 GB eMMC expansion board and access AI models stored there.
• You can pair either version of the core board with any of three image signal processor (ISP) sensor modules: a 2 MP rolling-shutter module for normal applications, an 8 MP rolling shutter module for high-resolution applications, or a 2 MP global-shutter module (based on the ON Semi AR0234) for high-speed applications.

Features:

• High Compute Capacity: 4 trillion operations per second (TOPS)
• Three ISP-Ready Sensor Modules: Up to 8 MP, Up to 120 FPS, Rolling Shutter or Global Shutter
• Hardware Video Encoding: H.264/H.265 at 2 MP (30 FPS) & MJPEG at 2MP (30 FPS)
• Flexible Connectivity: USB Type-C 3.0 & 2.0 selectable by cable orientation
• Versatile Design: built for prototyping and for integration into new products
• Capable of Running Two CNN Models in Series: Use one model's output as another model's input
• Rich Interfaces Available for Customization: GPIO, I²C, SPI, SD/SDIO, UART, 2x two-lane DSI (up to 2.5 Gbps per lane)
• Compatibility: Works with computers, ARM devices, and Raspberry Pi SBCs
• Available Variant With 8 GB of eMMC: Allows booting from ROM and local storage of AI models
• Lightweight & Compact: Each board weighs 9 - 12 g and measures 38 x 38 mm
• Open Source: Schematic and open source client software

Specifications:

• VPU: Intel Movidius Myriad X MA2085
• Vector Processors: 16 SHAVEs
• Vision Accelerators: 20+
• Neural Network Capability: Two neural compute engines (up to 4 TOPS)
• RAM:  8 Gbits, LPDDR4 (1600 MHz, 32-bit)
• Power Supply: 5 V / 2 A
• Input Data Interface: MIPI 4 lane
• Output Data Interface: USB Type-C 3.0 & 2.0 selectable by cable orientation
• Expansion Interfaces: GPIO, I²C, SPI, SD/SDIO, UART, 2x two-lane DSI (up to 2.5 Gbps per lane)
• Dimensions: 38 mm x 38 mm
• Weight: 9 g
• Cable: 30 cm USB Type-C

Documents:

• GitHub

Package Includes:

• 1 x EyeCloudAI CDK with eMMC Expansion Board