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K210 Module📖
0.Camera changes
  • Precautions for camera changes
1.K210-AI-Camera introduction
  • 1.K210 main chip introduction
  • 2.K210 visual recognition module introduction
  • 3.Module pin assignments
  • 4.MicroPython Introduction
  • 5. FAQ analysis
  • 6.Bracket installation
2.Development Environment Setup
  • 1.To install the serial port assistant
  • 2.Install CanMV IDE development software
  • 3.Flashcard factory firmware
  • 4.IDE import routine
  • 5.Call custom py library
  • 6.MicroPython API documentation
3.Basic experimental routines
  • 1.Lighting the RGB light experiment
  • 2.Key features of the experiment
  • 3.Timer experiment
  • 4.PWM breathing light experiment
  • 5.LCD display experiment
  • 6.The touchpad read the coordinates of the experiment
  • 7.The camera shows the experimental
  • 8.Memory card read and write files of the experiment
  • 9.External interface experimental
4.Graphical manipulation routines
  • 1.Draw graphics
  • 2.Button and the click event
  • 3.Slider
  • 4.Chart animation
  • 5.Multi-label layout
5.AI visual experiments routines
  • How to import the model file into memory cardnew
  • 1.Color recognition
  • 2.Barcode recognition
  • 3.QR code recognition
  • 4.Apriltags recognition
  • 5.Face detection
  • 6.Face feature detection
  • 7.Mask detection
  • 8.Face recognition
  • 9.Object detection
  • 10.Self-learning classification
  • 11.Handwritten digit recognition
  • 12. Multiple color recognition
  • 13. Human body detectionnew
  • 14. Yolo hand detectionnew
  • 15. License Plate Recognitionnew
  • 16. Autonomous training modelnew
6.Extended routines (sold separately)
6.1.For STM32 Car
  • 10. stm_ K210 Autonomous Learning Classification
  • 1.automatic driving
  • 2.color follow
  • 3.Handwriting digital operation
  • 4.Color reaction
  • 5.Road sign indicating the operation
  • 6.Following the apriltag
  • 7.QR code instruction
  • 8.PTZ tracking color
  • 9.PTZ tracking face
6.2.1 arduino_k210
  • 1.ard_k210-Color recognition
  • 2.ard_k210-Bar code identification
  • 3.ard_k210-QR code identification
  • 4.ard_ K210-mechanical code identification
  • 5.ard_ K210-Face Detection
  • 6. ard_ K210-facial feature detection
  • 7. ard_ K210-mask detection
  • 8. ard_ K210-facial recognition
  • 9. ard_ K210-object detection
  • 10. ard_ K210 Autonomous Learning Classification
  • 11. ard_ K210 Handwritten Digit Recognition
6.2 K210 as a coprocessor
  • ReadMe
6.2.2 stm32_k210
  • 1.stm_ K210 color recognition
  • 2. stm_ K210 barcode recognition
  • 3. stm_ K210 QR code recognition
  • 4. stm_ K210 mechanical code identification
  • 5. stm_ K210 Face Detection
  • 6.stm_ K210 facial feature detection
  • 7. stm_ K210 mask detection
  • 8. stm_ K210 facial recognition
  • 9. stm_ K210 object detection
  • 11. stm_ K210 Handwritten Digit Recognition
6.2.3 microbit_k210
  • 1.microbit_ K210 color recognition
  • 2.microbit_ K210 barcode recognition
  • 3.microbit_ K210 QR code recognition
  • 4.microbit_ K210 mechanical code identification
  • 5. microbit_ K210 Face Detection
  • 6. microbit_ K210 facial feature detection
  • 7. microbit_ K210 mask detection
  • 8. microbit_ K210 facial recognition
  • 9. microbit_ K210 object detection
  • 10. microbit_ K210 autonomous classification learning
  • 11. microbit_ K210 Handwritten Digit Recognition
6.2.4 pico_k210
  • 1. pico_ K210 color recognition
  • 2. Pico_ K210 barcode recognition
  • 3. Pico_ K210 QR code recognition
  • 4. pico_ K210 machine code recognition
  • 5. pico_ K210 Face Detection
  • 6. pico_ K210 facial feature detection
  • 7. pico_ K210 mask recognition
  • 8. pico_ K210 facial recognition
  • 9. pico_ K210 object detection
  • 10. pico_ K210 Autonomous Learning Classification
  • 11. pico_ K210 Handwritten Digit Recognition
6.2.5 MSPM0G3507_k210
  • 1.MSPM0_K210 color recognition
  • 2.MSPM0_K210 barcode recognition
  • 3.MSPM0_K210 QR code recognition
  • 4.MSPM0_K210 mechanical code recognition
  • 5.MSPM0_K210 face detection
  • 6.MSPM0_K210 facial feature detection
  • 7.MSPM0_K210 mask detection
  • 8.MSPM0_K210 face recognition
  • 9.MSPM0_K210 Object Detection
  • 10.MSPM0_K210 Self-study classification
  • 11.MSPM0_K210 handwritten digit recognition
6.2.6 MSPM0G3519_k210
  • 1. MSPM0_K210 Color Recognitionnew
  • 2. MSPM0_K210 Barcode Recognitionnew
  • 3. MSPM0_K210 QR Code Recognitionnew
  • 4. MSPM0_K210 Mechanical Code Recognitionnew
  • 5. MSPM0_K210 Face Detectionnew
  • 6. MSPM0_K210 Facial Feature Detectionnew
  • 7. MSPM0_K210 Mask Detectionnew
  • 8. MSPM0_K210 Face Recognitionnew
  • 9. MSPM0_K210 Object Detectionnew
  • 10. MSPM0_K210 Self-study Classificationnew
  • 11. MSPM0_K210 Handwritten Digit Recognitionnew
6.3 For 24 channel servo drive board
  • 1. 2DOF PTZ Color Tracking
  • 2. 2DOF Face Tracking
  • 3. 2DOF Fruit sorting
6.4 For autopilot map
  • 1.k210 model training
  • 2.Assembly and wiring of stm32 car
  • 3.Recognize left and right sign
  • 4.Identify and remove speed limit
  • 5.Identify parking spaces and park
  • 6.STM32 car autopilot
6.5.1 For MSPM0G3507_Wheeled Chassis Kit
  • 1.MSPM0-Automatic Driving
  • 2.MSPM0-Color follow
  • 3.MSPM0-Number recognition
  • 4.MSPM0-Color reaction
  • 5.MSPM0-Road signs
  • 6.MSPM0-Machine code following
  • 7.MSPM0-QR code recognition
6.5.2 For MSPM0G3519_Wheeled Chassis Kit
  • 1.MSPM0-Automatic Drivingnew
  • 2.MSPM0-Color follownew
  • 3.MSPM0-Number recognitionnew
  • 4.MSPM0-Color reactionnew
  • 5.MSPM0-Road signsnew
  • 6.MSPM0-Machine code followingnew
  • 7.MSPM0-QR code recognitionnew
6.5.3 For STM32_Wheeled Chassis Kit
  • 1.STM32-Automatic Driving
  • 2.STM32-Color follow
  • 3.STM32-Number recognition
  • 4.STM32-K210-Color Reaction
  • 5.STM32-Road signs
  • 6.STM32-Machine code following
  • 7.STM32-QR code recognition
Download
  • Driver development software
  • AI model
  • Source code
  • Instruction manual
  • Hardware_3DModelFile
  • K210_Chip_Data
Download ZIP

Welcome to K210 Module repository

10. MSPM0_K210 Self-study Classification

MSPM0_K210 Self-learning Classification

1. K210 and MSPM0 Communication

1.1 Experimental Prerequisites

This tutorial uses the MSPM0G3519 development board. K210 needs to run the program in K210-AI(MSPM0) to start the experiment.

MSPM0G3519 *1

K210 vision module *1 (with SD card (with AI model) and camera)

USB to TTL module *1

1.2 Experimental Wiring

Method 1: Using USB to TTL module

MSPM0GK210 Vision Module
RXTXD
GNDGND
VCC5V
MSPM0GUSB to TTL Module
TXRXD
GNDGND

img

Method 2: Using onboard Type-C port

img

1.3 Main Code Explanation

This example sets the serial port print baud rate to 115200 bps, and the K210 module connection baud rate is also set to 115200 bps.

5

6

​x
int main(void)
{
    SYSCFG_DL_init();

    NVIC_ClearPendingIRQ(MYUART_INST_INT_IRQN);//Clear serial port interrupt flag
    NVIC_EnableIRQ(MYUART_INST_INT_IRQN);//Enable serial port interrupt



    while (1)
    {
         if (k210_msg.class_n != 0)//Example number is not empty
        {
            if(k210_msg.class_n == 10)//Self-learning classification
            {
                sprintf(buff_com,"id = %c\r\n",k210_msg.id);
                uart0_send_string(buff_com);

                k210_msg.class_n = 0;//Clear example number
            }

        }
        delay_ms(500);

    }
}

After the above program runs this example, the k210_msg structure members will have corresponding values and will be printed via serial port.

k210_msg: is the structure for receiving information. Its main members are:

  • x: is the x-coordinate of the upper-left corner of the recognized box (range: 0-240)

  • y: is the y-coordinate of the upper-left corner of the recognized box (range: 0-320)

  • w: is the width of the recognized box (range: 0-240)

  • h: is the height of the recognized box (range: 0-320)

  • id: is the recognized label

  • class_n: example number

  • msg_msg[20]: valid data

After data reception and processing, each member of k210_msg will store valid information. If you want to do secondary development, you can directly call the members of k210_msg.

Note: The Keil project source code must be placed under the SDK path for compilation.

1.4 Experimental Phenomenon

  1. After connecting the cables, the K210 vision module runs offline. Press key1 on K210 to record object information. Take 15 photos (5 photos for each object), storing 3 objects.

    K210 offline running method

  2. Set the serial assistant interface as shown in the figure

    3

  3. Then run the self-learning classification example. The serial assistant will print the important information transmitted by K210 to MSPM0G, as shown in the figure below.

    4

Object detection only transmits the 1 member variable of k210_msg: id.

id: is the object ID when taking photos. The range of id is (1-3)

MSPM0_K210 Object Detection
MSPM0_K210 Handwritten Digit Recognition

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