CHF123
产品描述
Dual NPU cores running AI models in sync, ultra-compact 2.5cm × 2.5cm size, 240+ FPS color global shutter, 60+ FPS YOLO object detection, 180+ FPS FOMO object detection!
The all-new OpenMV AE3 high-performance AI smart image recognition camera is now officially on sale!








































The OpenMV AE3 is a small, low power, microcontroller board which allows you to easily implement applications using machine vision in the real-world. You program the OpenMV AE3 in high level Python scripts (courtesy of the MicroPython Operating System) instead of C/C++. This makes it easier to deal with the complex outputs of machine vision algorithms and working with high level data structures. But, you still have total control over your OpenMV AE3 and its I/O pins in Python. You can easily trigger taking pictures and video on external events or execute machine vision algorithms to figure out how to control your I/O pins.

| Processor | Dual Core ARM® 32-bit Cortex®-M55 CPU w/ Double Precision FPU, both w/ ARM® MVE Helium™ technology (128-bit SIMD); 400/160 MHz (~640/~256 DMIPS); Core Mark Score: 1748/752 (compare w/ Raspberry Pi 3: 3800) |
| Camera Info | PAG7936 1MP Color Global Shutter Sensor; 1280x800 @ 30 FPS; 640x400 @ 120 FPS; 320x200 @ 240 FPS; Optical Format: 1/4"; Pixel Size: 3um x 3um; CRA: 20°; SNR: 36 dB; Dynamic Range: 64 dB |
| Lens Info | Max Image Circle Diameter: >6.8mm; Focal Length: 3.1mm +/- 5%; Aperture: F2.3 +/- 5%; Back Focal Length: 1.46mm; TV Distortion: <-2.5%; Relative Illumination: >43.3%; CRA: 20°; Format: 1/2.7"; DFOV = <87.7°, HFOV = <79°, VFOV = <49°; Mount: M8; IR Cut Filter: 650nm; @430nm-595nm: Tavg > 90% Tmin > 83%; @650nm +/- 6nm: T=50%; Structure: 5P+IR; Actual FoV with PAG7936 image sensor: D72.5° H63.8° V42.3° |
| Electrical Info | All pins are 3.3V tolerant with 3.3V output. All pins can sink or source up to 25mA. Do not draw more than 250mA from your OpenMV Cam's 3.3V rail. PLEASE NOTE THAT THE I/O PINS OF THE AE3 ARE NOT 5V TOLERANT! DO NOT CONNECT THE DEVICE DIRECTLY TO A 5V MCU LIKE THE ARDUINO MEGA. You may power the AE3 using 3.3V on its 3.3V pins. The AE3 will source 3.3V from its 3.3V pins when powered by USB, unless another source already provides 3.3V. |
| Performance Specs | Power-on to inference result (attached to PC): ~2.5s; Power-on to inference result (stand-alone): ~1.5s; Wakeup from deepsleep to inference result (attached to PC): ~2.5s; Wakeup from deepsleep to inference result (stand-alone): ~1.5s; Bypass bootloader, power-on/wakeup to inference result (attached to PC): ~1.5s; Bypass bootloader, power-on/wakeup to inference result (stand-alone): ~0.5s |
| Power Consumption | Full Power: 50-60mA @ 5V (0.25W-0.3W); Idling: 24mA @ 5V (to be improved); Deep Sleep: 80uA @ 3.3V |
| Weight | 8g |
| Length | 30mm (including case) |
| Width | 30mm (including case) |
| Height | 9mm (including case) |
| Storage Temperature | -30°C to +85°C |
| Operating Temperature | -30°C to +70°C |