pdf-icon

UnitV-M12

SKU:U078-V-M12

Tutorial

Choose the development platform you want to use, view the corresponding tutorial&quick-Start.

V-Function V-Training Maixpy

Description

UNIT-V M12 is an AI camera unit with M12 lens specifications and K210 processor, which integrates dual-core 64-bit RISC-V CPU and neural network processor edge computing system-on-chip, it equippes with M12 optical lens OV7740 wide-angle camera module (can replace other M12 lenses), the body is equipped with two programmable buttons and TF card expansion slot. Its bottom provides an HY2.0-4P interface and a TYPE-C interface for data connection to the controller. The UNIT-V M12 AI camera is very small, it is suitable for embedding in various devices, with machine vision processing capabilities, supporting a variety of image recognition capabilities (such as real-time acquisition of the size and coordinates of the detected target Real-time acquisition of the type of detected target), and it can perform convolutional neural network calculations, which is a low-threshold machine vision embedded solution.

Features

  • Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)
  • Dual Independent Double Precision FPU
  • 8MiB 64bit width On-Chip SRAM
  • Neural Network Processor(KPU) / 0.8Tops
  • Field-Programmable IO Array (FPIOA)
  • AES, SHA256 Accelerator
  • Direct Memory Access Controller (DMAC)
  • Micropython Support
  • Firmware encryption support
  • On-board Hardware resources:
    • Flash: 16M
    • Camera :OV7740
    • Button: button * 2
    • External storage: TF card/Micro SD
    • Interface: HY2.0/compatible GROVE

Includes

  • 1x Unit V M12
  • 1x 20cm 4P Grove Cable
  • 1x 100cm USB-C Cable

Applications

  • Face recognition/detection
  • Object detection/classification
  • Obtaining size and coordinates of the target in real-time
  • Obtaining the type of detected target in real-time
  • Shape recognition
  • Video recorder

Specifications

Resources Parameters
Kendryte K210 Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal)
SRAM 8MiB
Flash 16M
Input voltage 5V @ 500mA
KPU Neural network parameter size 5.5MiB - 5.9MiB
Interface TypeC x 1, GROVE(I2C+I/0+UART) x 1
Button Custom button x 2
Image Sensor M12 wide-angle lens ov7740
FOV 80°
External storage TF Card/Micro SD
shell material Plastic ( PC )+CNC (ALUMINIUM)
Product Size 40* 24* 16.4mm
Package Size 70* 50* 30mm
Product Weight 13.9g
Package Weight 52.6g

SD card test

UNIT-V does not currently recognize all types of MicroSD cards. We have tested some common SD cards. The test results are as follows.


Brand Storage Type Class Format Test Results
Kingston 8G HC Class4 FAT32 OK
Kingston 16G HC Class10 FAT32 OK
Kingston 32G HC Class10 FAT32 NO
Kingston 64G XC Class10 exFAT OK
SanDisk 16G HC Class10 FAT32 OK
SanDisk 32G HC Class10 FAT32 OK
SanDisk 64G XC Class10 / NO
SanDisk 128G XC Class10 / NO
XIAKE 16G HC Class10 FAT32 OK(purple)
XIAKE 32G HC Class10 FAT32 OK
XIAKE 64G XC Class10 / NO
TURYE 32G HC Class10 / NO

PinMap

image

Model Size

module size

Examples

Arduino

Video

  • Color Recognition Example

FAQ

Question: What should I do if the computer does not detect Device?

  • UnitV may not work without a drive in some systems, and users can fix this problem by manually installing FTDI drivers ( https://ftdichip.com/drivers/vcp-drivers/ ). Taking the Win10 environment as an example, download the driver file that matches the operating system, extract it, and install it through Device Manager. (Note: In some system environments, you need to install twice before the driver takes effect, the unrecognized device name is usually M5Stack or USB Serial, Windows recommends using the driver file to install directly in Device Manager (custom update), the executable file installation method may not work normally).