UnitV-OV7740 is a powerful AI vision processing camera unit equipped with the Kendryte K210 chip, integrating a dual-core 64-bit RISC-V CPU and an advanced neural network processor edge computing system-on-chip.
This camera is compact and easy to embed into various devices, offering excellent machine vision processing capabilities. It supports multiple image recognition functions, such as real-time acquisition of the size, coordinates, and type of detected targets, and can perform convolutional neural network calculations even in low-power states, providing users with a zero-threshold machine vision embedded solution.
In terms of the development environment, it supports MicroPython, making the program code more concise during project development. The OV7740 image sensor it carries makes it an ideal choice for machine vision projects.
From a hardware configuration perspective, the device features two programmable buttons, a front-facing RGB LED indicator for status display, and a bottom-mounted HY2.0 x 4P interface and a TYPE-C interface for easy connection to the main control device. Additionally, it supports TF card expansion for memory, facilitating the use of relevant materials and model files.
Features
Dual-core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz (Normal)
Double-precision FPU
8MiB 64-bit on-chip SRAM
Neural Network Processor (KPU) / 0.8Tops
Programmable I/O Array (FPIOA)
AES, SHA256 Accelerator
Direct Memory Access Controller (DMAC)
Supports MicroPython
Firmware encryption support
Onboard hardware resources:
Flash: 16M
Camera: OV7740
Buttons: 2
Status LED: WS2812 LED
Expansion card interface: TF card/Micro SD
Interface: HY2.0/compatible GROVE
Includes
1 x UnitV-OV7740
1 x HY2.0-4P Grove cable (20cm)
1 x USB Type-C cable (1m)
Applications
Object detection/classification
Real-time acquisition of target size and coordinates
Real-time acquisition of detected target types
Shape recognition
Video recording
Specifications
Specification
Parameter
Kendryte K210
Dual-core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz (Normal)
SRAM
8MiB
Flash
16M
Input voltage
5V @ 500mA
KPU neural network size
5.5MiB-5.9MiB
Interface
TypeC x 1, HY2.0-4P (I2C+I/O+UART) x 1
RGB LED
WS2812 x 1
Buttons
Custom buttons x 2
Camera
OV7740 (30W pixels)
FOV
65°
External storage
TF Card/Micro SD
Net weight
8g
Gross weight
45g
Product dimensions
40 x 24 x 13mm
Packaging dimensions
70 x 50 x 30mm
Casing material
Plastic (PC)
Learn
KENDRYTE K210
Kendryte K210 is a system-on-chip (SoC) with integrated machine vision capabilities. Using TSMC's ultra-low-power 28nm advanced process, it features a dual-core 64-bit processor with excellent power efficiency, stability, and reliability. This solution aims for zero-threshold development, enabling rapid deployment into user products, empowering AI applications.
Equipped with machine vision capabilities
Better low-power vision processing speed and accuracy
Features a convolutional neural network hardware accelerator KPU for high-performance convolutional neural network operations
TSMC 28nm advanced process, temperature range -40°C to 125°C, stable and reliable
Supports firmware encryption, difficult to crack using ordinary methods
Unique programmable IO array, making product design more flexible
Low voltage, lower power consumption compared to systems with similar processing capabilities
3.3V/1.8V dual voltage support, no need for level conversion, saving costs
This product features a dual-core 64-bit high-performance low-power CPU based on RISC-V ISA, with the following characteristics:
Core count: Dual-core processor
Processor width: 64-bit CPU 400MHz
Nominal frequency: 400MHz
Instruction set extension: IMAFDC
Floating-point processing unit (FPU): Double precision
Platform interrupt management: PLIC
Local interrupt management: CLINT
Instruction cache: 32KiB x 2
Data cache: 32KiB x 2
On-chip SRAM: 8MiB
OV7740
Supported output formats: RAW RGB and YUV
Supported image sizes: VGA, QVGA, CIF, or smaller sizes
Supports sunspot elimination
Supports internal and external frame synchronization
Standard SCCB serial interface
Digital video port (DVP) parallel output interface
UnitV may not work without drivers in some systems. Users can manually install the
FTDI driver
to fix this issue. For example, in a Win10 environment, download the driver file matching the operating system, extract it, and install it via Device Manager. (Note: In some system environments, the driver may need to be installed twice to take effect. The unrecognized device name is usually M5Stack or USB Serial. Windows recommends using the driver file for direct installation in Device Manager (custom update), as the executable installation method may not work properly).