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WonderMV Vision Recognition Module AI Intelligent Camera Python Development Board CanMV Sensor
- 【Artifncial Intelligence, Powerful Computing Power】WonderMV open source vision module is a powerful and cost-effective Al vision module. It is developed based on the K210 chip and supports 12 AI vision items such as color recognition, road sign recognition, vision line following, face recognition, mask recognition, and tag recognition function.
- 【Compatible with Various Controllers】WonderMV vision module is equipped with a serial interface and can be used with various controllers such as STM32, Raspberry Pi, Arduino, Micro:bit, etc. Users can easily output vision recognition results to an external controller through the serial port, without the need to delve into complex vision algorithms, making it easy to create creative AI projects.
AprilTag Recognition
WonderMV vision module can identify AprilTags on the screen, obtaining position data for each AprilTag and 3D conversion data for accurate positioning.
Barcode Recognition
Capable of recognizing the barcode, WonderMV vision module frames QR codes and retrieves barcode data. Data can be transmitted to external devices using the serial port.
QR Code Recognition
WonderMV vision module excels in recognizing QR codes on the screen and framing them. Through serial communication, external devices can acquire QR code data.
Handwritten Number Recognition
WonderMV vision module recognizes handwritten numbers on the screen, and displays the corresponding number in the upper left corner.
Face Detection
WonderMV vision module swiftly identifies the presence of a human face on the screen. Upon successful detection, the module outlines the human face on the screen, providing the position information. The external control device can access this information through serial communication.
Face Feature Detection
WonderMV vision module not only detects human faces but also marks key facial features such as the eyes, nose, and mouth using star symbols. This detailed information about the human face is accessible to external control devices through the serial port.
Mask Identification
WonderMV vision module is equipped to determine whether a person is wearing a mask. It outlines the human face on the screen and displays the result of mask identification. Through serial communication, the external control device can obtain information about individuals wearing masks.
Face Recognition
WonderMV vision module can learn and record specific human faces for recognition purposes. It can distinguish whether the detected human face matches the learned faces and, if successful, frames the face on the screen and displays the person's name. External control devices can obtain relevant data through serial communication.
1TOPS High-Performance
Computing Chip
Built on the Kendryte K210 AI chip, this module features a 64-bit RISC-V kernel processor and a 1TOPS high-performance computing chip. It ensures stable and smooth neural network operations, supporting AI image recognition, and handling complex computing tasks with efficiency.
Built-in LCD Capacitive Touch Screen
Featuring a 2.0-inch LCD capacitive screen with a clear display resolution of 320*240, the vision module facilitates swift debugging and control.
Support Real-time Firmware Upgrade
WonderMV vision module is equipped with a USB port, enabling users to connect it to a computer via a MicroUSB cable for swift firmware updates, facilitating easy downloading and debugging.
Provide 32GB Memory Card
Featuring a TF card slot, the module comes with a 32GB SD card for convenient storage of data and model files, streamlining the AI visual workflow.
Onboard Fill Light and
Customizable Keys
The module has a fill light for operation in dark environments. Additionally, customizable programmable keys meet individual preferences.
Compact and Elegant Design
With its compact size, WonderMV vision module can be easily installed on a controller using the corresponding bracket, allowing users to undertake a variety of AI creative projects.
| WonderMV Vision Module Parameter | |||
| Processor | Kendryte K210 | Display size | 2.0 inch |
| Chip architecture | RISC-V architecture | Built-in function | Micropython firmware |
| Development environment | CanMV IDE | LED | User-defined LED light |
| TF card slot * 1 | TF card can be inserted. 32GB TF card is recommend-ed | Fill light | Supply light for dim environ-ments, customiz-able by the user |
| Power supply | 5.0V | Camera | 2 magapixel |
| Working current | about 300mA | Key * 2 | Costume function key |
| Interface | Type-C, UART, IIC | Size | 58.9* 40.7* 16.2mm |
| Display | LCD capacitive touch screen with a resolution of 320x240 | Weight | 43g |
| K210 Chip Basic Parameter | |||
| Core | RISC-V Dual Core 64bit, with FPU | Voice recognition | Voice recognition |
| Main frequency | 400MHz (can be boosted to 600MHz) | Chip Manufacturing Process | TSMC's advanced |
| AI Vision | Equipped with KPU, supports convolutional neural network calculations, and more | Network models | Supports YOLOv3/ Mobilenetv2/ TinyYOLOv2, face recognition, and others |
| Core instruction set | RISC-V, a simplified instruction set | Deep learning frameworks | Compatible with TensorFlow/ Keras/ Darknet/ Caffe, among other mainstream frameworks |
| Image recognition | QVGA@60fps/ VGA@30fps | Peripheral interfaces | GPIO, FPIOA, UART, TIMER, SPI, I2C, I2S |
| SRAM | Built-in 8 megabytes | Operating temperature | -30°C to 85°C |
| Safety | Supports firmware encryption, AES, and SHA256 encryption algorithms | Operating voltage | Dual voltage support at 3.3V/ 1.8V, eliminating the need for level shifting |
| WonderMV Vision Module Parameter | |
| Processor | Kendryte K210 |
| Display size | 2.0 inch |
| Chip architecture | RISC-V architecture |
| Built-in function | Micropython firmware |
| Development environment | CanMV IDE |
| LED | User-defined LED light |
| Camera | 2 magapixel |
| Fill light | Supply light for dim environ-ments, customiz-able by the user |
| Power supply | 5.0V |
| TF card slot * 1 | TF card can be inserted. 32GB TF card is recommend-ed |
| Working current | about 300mA |
| Key * 2 | Costume function key |
| Interface | Type-C, UART, IIC |
| Size | 58.9* 40.7* 16.2mm |
| Display | LCD capacitive touch screen with a resolution of 320x240 |
| Weight | 43g |
| K210 Chip Basic Parameter | |
| Core | RISC-V Dual Core 64bit, with FPU |
| Voice recognition | Voice recognition |
| Main frequency | 400MHz (can be boosted to 600MHz) |
| AI Vision | Equipped with KPU, supports convolutional neural network calculations, and more |
| Chip Manufacturing Process | TSMC's advanced |
| Network models | Supports YOLOv3/ Mobilenetv2/ TinyYOLOv2, face recognition, and others |
| Core instruction set | RISC-V, a simplified instruction set |
| Deep learning frameworks | Compatible with TensorFlow/ Keras/ Darknet/ Caffe, among other mainstream frameworks |
| Safety | Supports firmware encryption, AES, and SHA256 encryption algorithms |
| Peripheral interfaces | GPIO, FPIOA, UART, TIMER, SPI, I2C, I2S |
| SRAM | Built-in 8 megabytes |
| Operating temperature | -30°C to 85°C |
| Image recognition | QVGA@60fps/ VGA@30fps |
| Operating voltage | Dual voltage support at 3.3V/ 1.8V, eliminating the need for level shifting |
| Item | Specification |
| Processor | Kendryte K210 |
| Display size | 2.0 inch |
| Chip architecture | RISC-V architecture |
| Development environment | CanMV IDE |
| LED | User-defined LED light |
| Camera | 2 magapixel |
| Fill light | Supply light for dim environments, customizable by the user |
| Power supply | 5.0V |
| TF card slot * 1 | TF card can be inserted. 32GB TF card is recommended |
| Working current | About 300mA |
| Key * 2 | Costume function key |
| Interface | Type-C, UART, IIC |
| Size | 58.9* 40.7* 16.2mm |
| Display | LCD capacitive touch screen with a resolution of 320x240 |
| Size | 58.9* 40.7* 16.2mm |
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