Price: $48.99
(as of Jun 20, 2025 04:39:22 UTC – Details)
Product Description
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K210 Visual Recognition Module
Yahboom K210 visual recognition module is an image processing module based on artificial intelligence technology. It possess a dual-core 64-bit processor, computing power up to 1TOPS. It adopts deep learning algorithm, which can efficiently identify various objects and features in the image. The module integrates a serial interface, which can be connected and interacted with various controllers such as STM32, Raspberry Pico, Arduino, Micro:bit and other hardware devices and platforms. K210 module is small in size and low in power consumption, making it suitable for various embedded systems and intelligent hardware products. Users can easily create many creative AI projects by this module.
1) On board 2MP camera OV2640, serial port, 2.0-inch LCD touch screen, programmable RGB lights and other hardware resources, support TF card (32GTF card will be provided for free).
2) Adopt Kendryte K210 chip, with dual-core 64-bit processor, computing power can reach 1TOPS.
3) Support face recognition, mask recognition, feature detection, number recognition, color recognition, road sign recognition and visual line inspection.
4) All MicroPython codes are open source, and we will provide 40+ detailed tutorials for users’ reference.
5) Three brackets with different heights for choice, users can fix module on different robots or smart cars.
Main processor, AI vision module series parameters, programming, page functions
AI vision recognition, face recognition, object recognition, color recognition
1 AI Vision Case
2 Product Features
3 Module Function
4 Multiple Control
1 Product Parameters
2 Product Size
3 Documentation
Yahboom Ros Programming Robot Kit
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Price
$1,919.00$1,919.00
$1,389.00$1,389.00
$259.99$259.99
$279.99$279.99
$279.99$279.99
Master Control
Jetson Series
Jetson Series
Raspberry Pi5
Raspberry Pi5
PC Virtual Machine
Compatible with ROS
ROS2
ROS2
ROS2
ROS2
ROS1
ROS Version
Melodic/Humble
Melodic/Humble
Docker+Humble
Docker+Humble
Noetic
Linux System
Ubuntu22.04
Ubuntu22.04
raspios-bookworm
raspios-bookworm
Ubuntu20.04
Product Positioning
Intelligent Gripping,AI Vision
3D Space Recognition Grasping
360° movement, AI vision tech
ROS2 develop, SLAM navigation
ROS + AI OpenCV, Movelt Motion
1Tops computing power, efficient image processing capabilities: The K210 vision module is equipped with an efficient AI chip, a 2 million pixel OV2640 camera, and a built-in 2.0-inch LCD capacitive touch screen. It can process image data at a very fast speed while consuming low power, supporting various application scenarios such as face feature recognition, barcode recognition, object detection, color recognition, and visual line tracking.
Simplified AI vision development learning: The Smart Vision Sensor uses MicroPython programming, with CanMV as the development environment. According to Yahboom’s tutorials, users can skip the complex process of deploying visual algorithms and only need to record 5 images to complete autonomous model training, lowering the learning and use threshold of AI technology.
Multi-controller compatibility: The K210 vision recognition module is equipped with a serial interface and can be used with various controllers such as STM32, Raspberry Pi Pico, Ard-uino, BBC-V2, MSPM0, etc. Users can easily output visual recognition results to an external controller through the serial port, without the need to delve into complex visual algorithms, making it easy to create creative AI projects.Identify multiple colors simultaneously
Open source code: The program source code of the Smart AI Lens Kit is completely open source, not a closed-source product that can only be used without further development. This enables users to more easily develop and customize their own visual application programs. In addition to powerful AI recognition functions, we also provide rich development materials to facilitate users to learn and develop their own AI projects.
Diverse application scenarios: The compact K210 vision module can be widely used in electronic competitions, efficient experimental teaching, robot extensions or personal DIY projects, and even widely used in various fields such as smart homes, industrial automation, etc., providing users with more possibilities and innovation space.