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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

4.Apriltags recognition

 

4 Apriltags recognition

4 Apriltags recognition4.1 experimental goals4.2 experimental procedure4.3 experimental results4.4 experiment summary

4.1 experimental goals

This lesson mainly learns the machine code recognition function, according to the recognized machine code, box out, and print the relevant data.

The reference code path for this experiment is :CanMV\05-AI\find_apriltags.py

 

4.2 experimental procedure

The factory firmware of the module has integrated the AI vision algorithm module. If you have downloaded other firmware, please burn it back to the factory firmware before doing the experiment.

  1. Import the relevant libraries and initialize the camera and LCD display.

​x
import sensor, image, time, math, lcd

lcd.init()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 100)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)
clock = time.clock()
  1. Set the machine code family members to be identified, and comment out that line if you don't need to identify which one. The default here is the TAG 36 H 11 family.

xxxxxxxxxx
tag_families = 0
tag_families |= image.TAG16H5   # comment out to disable this family
tag_families |= image.TAG25H7   # comment out to disable this family
tag_families |= image.TAG25H9   # comment out to disable this family
tag_families |= image.TAG36H10  # comment out to disable this family
tag_families |= image.TAG36H11  # comment out to disable this family (default family)
tag_families |= image.ARTOOLKIT # comment out to disable this family
  1. Create a new function to convert the family name to a string.

xxxxxxxxxx
def family_name(tag):
    if(tag.family() == image.TAG16H5):
        return "TAG16H5"
    if(tag.family() == image.TAG25H7):
        return "TAG25H7"
    if(tag.family() == image.TAG25H9):
        return "TAG25H9"
    if(tag.family() == image.TAG36H10):
        return "TAG36H10"
    if(tag.family() == image.TAG36H11):
        return "TAG36H11"
    if(tag.family() == image.ARTOOLKIT):
        return "ARTOOLKIT"

4.Create a new while loop, call the find apriltags function to find the machine code in the image, box it when found, and print the relevant information.

xxxxxxxxxx
while(True):
    clock.tick()
    img = sensor.snapshot()
    #img = img.resize(280, 195)
    #img = img.resize(292, 210)
    for tag in img.find_apriltags(families=tag_families):
        img.draw_rectangle(tag.rect(), color = (255, 0, 0))
        img.draw_cross(tag.cx(), tag.cy(), color = (0, 255, 0))
        print_args = (family_name(tag), tag.id(), (180 * tag.rotation()) / math.pi)
        print("Tag Family %s, Tag ID %d, rotation %f (degrees)" % print_args)
    lcd.display(img)
    #print(clock.fps())

 

4.3 experimental results

Connect the K210 module to the computer through the microUSB data cable, CanMV IDE click the connect button, after the connection is completed click the Run button to run the routine code. You can also download the code as main.py and run it in the K210 module.

After waiting for the system initialization to be completed, the LCD displays the camera screen, and the camera is used to shoot the machine code, and the types of identification include: TAG16H5, TAG25H7, TAG25H9, TAG36H10, TAG36H11, ARTOOLKIT. Due to the limited processing power of the K210, processing the AprilTag machine code requires a lot of storage space and computing power, so it is currently impossible to set the full-screen resolution size screen.

You can see that the machine code is framed and the machine code information is printed out in the serial terminal at the bottom of the IDE.

image-20230216183237621

image-20230216183131033

 

4.4 experiment summary

Since machine code recognition requires a lot of calculations, the K 210 itself has limited conditions, so the screen cannot be set to full screen.

If you need to display a larger screen, you can set the sensor.set_framesize (sensor. QVGA), and then after capturing the camera image, increase img = img.resize(292, 210) to modify the image size. However, this will reduce the video frame rate and recognition rate, please do it with caution.

The machine code test uses the TAG36H11 family machine code by default, if you need to apply for other machine code, you can click Tools - > Machine Vision - > AprilTag machine code generator on the CanMV IDE.

image-20230216183822549

 

TAG36H11 photo:

tag36h11_0

 

tag36h11_1

QR code recognition
Face detection

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