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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

7.The camera shows the experimental

7 camera display experiment

7 camera display experiment 7.1 the experimental goals 7.2 experimental procedure 7.3 experimental results 7.4 the experiments are summarized

7.1 the experimental goals

This lesson is mainly for learning microPython drive the camera to the display function.

The present experiments the reference code path is: CanMV\03-Hardware\camera.py

7.2 experimental procedure

Module factory firmware has been integrated camera sensor control module, if the download other firmware, please burn back to the factory firmware and then perform the experiment.

  1. Import sensor and lcd.

import sensor, lcd 
import time 
  1. Initialize the LCD display and camera sensor.

xxxxxxxxxx
lcd.init() 
sensor.reset() 
  1. Camera settings pixel format is RGB565, and the frame size in pixels as QVGA(320*240), began to grab the image, ignore the frame image.

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sensor.set_pixformat(sensor.RGB565) 
sensor.set_framesize(sensor.QVGA) 
sensor.run(1) 
sensor.skip_frames(10) 

Wherein, sensor.set_pixformat(format): Used to set the camera's output format.

Parameter formatRepresents the frame format, with optional frame format with GRAYSCALE, RGB565, YUV422; the

Returns a value of True indicates success, False indicates failure.

sensor.set_framesize(framesize): Used to set the camera output frame size, k210 maximum support VGA format, is greater than the VGA will not be able to get the image.

Parameter framesizeIndicates the frame size, optional parameters are VGA(640 * 480), the QVGA(320 * 240), the QQVGA(160 * 120), the screen resolution is 320*240, the recommended settings for QVGA format.

sensor.run(enable): Image Capture function control, set successful return True, return False indicates failure.

Parameter enable: 1 means that the start grabbing image, 0 means stop grabbing images.

sensor.skip_frames(n, [, time]): Indicates that skips the specified frame or skip a specified time within the image, allowing the camera to image the change camera settings after stabilized.

Parameter n: Skip the n-th frame image;

time: Skip the specified time, in milliseconds.

If n and time are not specified, the method skips 300 MS of the frame; if both are specified, the method will skip n number of frames, but will in time milliseconds after the return.

  1. Create a clock clock object, used to calculate the camera's frame rate.

xxxxxxxxxx
clock = time.clock() 
  1. Create a while loop, get the camera of the current screen, in the upper left corner of the Add current frame rate, and display on the LCD screen.

xxxxxxxxxx
while(True): 
 clock.tick() 
 img = sensor.snapshot() 
 fps = clock.fps() 
 img.draw_string(0, 0, "%2.1 ffps" %(fps), color=(0, 0, 255), scale=2.0) 
 lcd.display(img) 
 print(fps) 

Wherein, img = sensor.snapshot(): Indicates to use the camera to take a picture.

clock.tick()And fps = clock.fps(): Indicates calculate the current frame rate fps.

7.3 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.

You can see the display screen real-time display the current Camera Picture, left corner of the screen to print the current camera frame rate, while the IDE to the right of the camera preview window is also synchronizes the display screen.

image-20230209150649983

Due to the K210 chip itself is not with the USB communication module, but the use of USB to serial chip, the transmission of the camera when the screen takes a certain amount of resources, resulting in a frame rate drop, and the easy loss of data, caused by the serial port is disconnected, so it is recommended to disable the IDE of the camera preview function, or directly download the main.py program file to the chip internal use.

image-20230209150353363

7.4 the experiments are summarized

Use CanMV IDE, with the factory firmware write a good MicroPython syntax, configure the camera's simple operation, you can use the system clock signal to calculate the camera in real-time frame rate, but due to the USB-to-serial port problems, you need to disable the IDE to the image preview, to improve the frame rate, to avoid the IDE no disconnect problem.

The touchpad read the coordinates of the experiment
Memory card read and write files of the experiment

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