SKU:U078-C


















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.
| 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 | Type-C 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/microSD |
| Product Size | 40.0 x 24.0 x 12.7mm |
| Product weight | 8.5g |
| Package Size | 54.0 x 37.0 x 15.0mm |
| Gross weight | 14.5g |
| Casing material | Plastic (PC) |
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.
This product features a dual-core 64-bit high-performance low-power CPU based on RISC-V ISA, with the following characteristics:
Unit V currently cannot recognize all types of microSD cards. We have tested some common microSD cards, and the results are as follows.

| Brand | Memory | Type | Transfer speed | Partition format | Test result |
|---|---|---|---|---|---|
| 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 |
| UnitV | G8 | G19 | G18 | G34, G35 |
|---|---|---|---|---|
| Hardware | RGB LED | Button A | Button B | |
| HY2.0-4P | Interface |
Choose the development platform you want to use and check the corresponding tutorial & quick start guide.



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