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K230 Vision Module📖
1. Quick Start
  • 0.Get start
  • 1. K230 firmware download and burning
  • 2. Install the programming environment
  • 3. Debug and run routines
  • 4. Offline running routine
  • 5. Micropython Quick Start
  • 6. GUI Program Instructions
  • 7.K230 module bracket installation tutorial
  • 8.K230 module 2DOF PTZ installation tutorial
2. Basic Courses
  • 1.FPIOA pin assignment
  • 2.RGB lights
  • 3.Buzzer
  • 4.Buttons
  • 5.Serial communication
  • 6.I2C communication
  • 7.PWM
  • 8.WDT watchdog
  • 9.Timer
  • 10.Fourier Transform
  • 11.SHA256 encryption
  • 12.AES encryption
  • 13.Multithreading
  • 14.File reading and writing
  • 15.Image Display
  • 16.Touch Display
  • 17.Camera display
  • 18.Image Flip
  • 19.Camera
3. Draw the image
  • 1. Draw the lines
  • 2. Draw the circle
  • 3. Draw the rectangle
  • 4. Draw the ellipse
  • 5. Draw the arrow
  • 6. Draw the crosshairs
  • 7. Draw text
  • 8. Draw key points
4. Graphics detection
  • 1. Line segment detection
  • 2. Rectangle Detection
  • 3. Circle detection
  • 4. Object edge detection
  • 5. Line inspection basics:fast linear regression
5. Color recognition
  • 1. Color recognition
  • 2. Object Counting
  • 3. Multi-color recognition
  • 4. K230 Color Line Patrol
6.1 CV_lite Image Processing Special Topic
  • 1.Introduction to cv_litenew
  • 2.cv_lite API Reference Manualnew
  • 3.Color Block Recognition - Grayscale Imagenew
  • 4.Color Block Recognition - Color Imagenew
  • 5.Circle Recognition - Grayscale Imagenew
  • 6.Circle Recognition - Color Imagenew
  • 7.Corner Recognition - Grayscale Imagenew
  • 8.Corner Recognition - Color Imagenew
  • 9.Edge Recognition - Grayscale Imagenew
  • 10. Edge Recognition - Color Imagenew
  • 11. Rectangle Recognition - Grayscale Imagenew
  • 12.Rectangle Recognition - Color Imagenew
  • 13.Rectangle recognition combined with corner recognition - grayscale imagenew
  • 14.Rectangle recognition combined with corner recognition - color imagenew
  • 15.Image Binarization - Grayscalenew
  • 16.Image Binarization - Color Imagenew
  • 17.Exposure Adjustmentnew
  • 18.Image Black Hat Operationsnew
  • 19.Image Color Histogramnew
  • 20.Image Closingnew
  • 21.Image Expansionnew
  • 22.Image Corrosionnew
  • 23.Gaussian Blurnew
  • 24.Gradient Transformationnew
  • 25.Mean Fuzzynew
  • 26.Image Openingnew
  • 27.Image Top Hat Operationnew
  • 28.PnP rangingnew
  • 29.Find rectangles and measure distancesnew
  • 30.Image grayscale world white balancenew
6.2 OpenCV Image Processing Special Topicnew
  • 1. OpenCV Introduction
  • 2. OpenCV API Reference
  • 3. Image Basic Transforms
  • 4. Morphological Operations
  • 5. Color Segmentation and Shape Classification
  • 6. Corner and Centroid Detection
  • 7. Hough Circle Detection
  • 8. Hough Line Detection
  • 9. Contour Analysis
  • 10. Drawing Functions
  • 11. Template Matching
  • 12. Image Blur Filtering
  • 13. Edge Detection
  • 14. Thresholding
  • 15. Color Segmentation
  • 16. Histogram and Pixel Transformation
  • 17. Arithmetic and Bitwise Operations
  • 18. Channel Operation and Statistics
  • 19. Image File Read and Write
  • 20. Pixel Level Transformation
7. Code type recognition
  • 1.Barcode recognition
  • 2.QR code recognition
  • 3.AprilTag tag recognition
  • 4.DM code recognition
8. Face Recognition
  • 1.[Must-read] General code structure and prerequisite knowledge of AI vision routines
  • 2.Face Detection
  • 3.Facial key point recognition
  • 4.Face orientation detection
  • 5.Face 3D Network
  • 6.Gaze direction detection
  • 7.Register for face recognition
9. Human body characteristics
  • 1. Human body detection
  • 2. Human key point detection
  • 3. Human posture recognition
  • 4. Fall detection
  • 5. Palm detection
  • 6. Palm key point detection
  • 7. Palm key point classification
  • 8. Gesture Recognition
  • 9. Dynamic gesture recognition
  • 10. Rock, Paper, Scissors
10. Scenario Application
  • 1.OCR character detection
  • 2.OCR character recognition
  • 3.yolov8n target detection
  • 4.yolov8n segmentation
  • 5. Self-learning object recognition
  • 6. License plate detection
  • 7. License Plate Recognition
  • 8. Target Tracking
  • 9. Fruit classification
  • 10. Garbage classification
  • 11. Road sign recognition
11. Audio and video processing
  • 1. Audio Recording
  • 2. Play Audio
  • 3. Video Recording
  • 4. Play Video
  • 5. Keyword wake-up
12. Network Basics
  • 1. Wireless network connection
  • 2. AP hotspot mode
  • 3. TCP-Server Example
  • 4. TCP-Client Example
  • 5. UDP-Server Example
  • 6. UDP-Client Example
  • 7. HTTP-Server Example
  • 8. HTTP-Client Example
  • 9. MQTT Quick Start
  • 10. MQTT-Publisher
  • 11. MQTT-Subscriber
  • 12. RTSP real-time image transmission
  • 13. RTSP real-time image transmission combined with AIDemo
  • 14. Call OpenRouter large model aggregation service
  • 15. Open the Resource Monitoring Panel
13. LVGL Graphical Interface
  • 1. Introduction to LVGL
  • 2. Create a button
  • 3. Create a slider
  • 4. Create an Image
  • 5. Create a text box and keyboard
14. GUI Code Tutorial & Secondary Development
  • 01.GUI System Architecture
  • 02.Core Engine Initialization
  • 03.Application Discovery Mechanism in GUI
  • 04.Desktop Layout Algorithm
  • 05.Advanced UI Styling
  • 06.BaseApp Base Class Analysis
  • 07.Hello_World Practical
  • 08.GUI Application Lifecycle and Resource Management
15. Train your own model
  • 1. Local deployment of yolo training environment
  • 2. Use online platforms for training
16.Touch Course
  • 1.Touch point detectionnew
  • 2.Touch Paintingnew
  • 3.Touch to take a photonew
17. Multi-master communication (purchased separately)
ESP32-K230
  • 1.k230 color recognition
  • 2.k230 barcode recognition
  • 3.k230 QR code recognition
  • 4.k230Apriltag code recognition
  • 5.k230DM code recognition
  • 6.k230 face detection
  • 7.k230 gaze direction
  • 8.k230 face recognition
  • 9.k230 human body detection
  • 10.k230 fall detection
  • 11.k230 palm detection
  • 12.k230 gesture recognition
  • 13.k230OCR character recognition
  • 14.k230 object detection
  • 15.k230 target tracking
  • 16.k230 self-learning object recognition
  • 17.k230 license plate recognition
Jetson-K230
  • 1.k230 color recognition
  • 2.k230 barcode recognition
  • 3.k230 QR code recognition
  • 4.k230Apriltag code recognition
  • 5.k230DM code recognition
  • 6.k230 face detection
  • 7.k230 gaze direction
  • 8.k230 face recognition
  • 9.k230 human body detection
  • 10.k230 fall detection
  • 11.k230 palm detection
  • 12.k230 gesture recognition
  • 13.k230OCR character recognition
  • 14.k230 object detection
  • 15.k230 target tracking
  • 16.k230 self-learning object recognition
  • 17.k230 license plate recognition
MSPM0G3507-K230
  • 1.k230 color recognition
  • 2.k230 barcode recognition
  • 3.k230 QR code recognition
  • 4.k230Apriltag code recognition
  • 5.k230DM code recognition
  • 6.k230 face detection
  • 7.k230 gaze direction
  • 8.k230 face recognition
  • 9.k230 human body detection
  • 10.k230 fall detection
  • 11.k230 palm detection
  • 12.k230 gesture recognition
  • 13.k230OCR character recognition
  • 14.k230 object detection
  • 15.k230 target tracking
  • 16.k230 self-learning object recognition
  • 17.k230 license plate recognition
Pico-K230
  • 1.k230 color recognition
  • 2.k230 barcode recognition
  • 3.k230 QR code recognition
  • 4.k230Apriltag code recognition
  • 5.k230DM code recognition
  • 6.k230 face detection
  • 7.k230 gaze direction
  • 8.k230 face recognition
  • 9.k230 human body detection
  • 10.k230 fall detection
  • 11.k230 palm detection
  • 12.k230 gesture recognition
  • 13.k230OCR character recognition
  • 14.k230 object detection
  • 15.k230 target tracking
  • 16.k230 self-learning object recognition
  • 17.k230 license plate recognition
raspberrypi-K230
  • 1.k230 color recognition
  • 2.k230 barcode recognition
  • 3.k230 QR code recognition
  • 4.k230Apriltag code recognition
  • 5.k230DM code recognition
  • 6.k230 face detection
  • 7.k230 gaze direction
  • 8.k230 face recognition
  • 9.k230 human body detection
  • 10.k230 fall detection
  • 11.k230 palm detection
  • 12.k230 gesture recognition
  • 13.k230OCR character recognition
  • 14.k230 object detection
  • 15.k230 target tracking
  • 16.k230 self-learning object recognition
  • 17.k230 license plate recognition
RDK-K230
  • 1.k230 color recognition
  • 2.k230 barcode recognition
  • 3.k230 QR code recognition
  • 4.k230Apriltag code recognition
  • 5.k230DM code recognition
  • 6.k230 face detection
  • 7.k230 gaze direction
  • 8.k230 face recognition
  • 9.k230 human body detection
  • 10.k230 fall detection
  • 11.k230 palm detection
  • 12.k230 gesture recognition
  • 13.k230OCR character recognition
  • 14.k230 object detection
  • 15.k230 target tracking
  • 16.k230 self-learning object recognition
  • 17.k230 license plate recognition
STM32-K230
  • 1. stm32_k230 color recognition
  • 2. stm32_k230 barcode recognition
  • 3. stm32_k230 QR code recognition
  • 4. stm32_k230Apriltag code recognition
  • 5. stm32_k230DM code recognition
  • 6. stm32_k230 face detection
  • 7.stm32_k230 looking direction
  • 8. stm32_k230 face recognition
  • 9. stm32_k230 human body detection
  • 10. stm32_k230 fall detection
  • 11. stm32_k230 palm detection
  • 12. stm32_k230 gesture recognition
  • 13. stm32_k230OCR character recognition
  • 14. stm32_k230 object detection
  • 15. stm32_k230 target tracking
  • 16. stm32_k230 self-learning object recognition
  • 17.stm32_k230 license plate recognition
Arduino-K230
  • 1.arduino_k230 color recognition
  • 2.arduino_k230 barcode recognition
  • 3.arduino_k230 QR code recognition
  • 4.arduino_k230 Apriltag code recognition
  • 5.arduino_k230 DM code recognition
  • 6.arduino_k230 face detection
  • 7.arduino_k230 looking direction
  • 8.arduino_k230 face recognition
  • 9.arduino_k230 human body detection
  • 10.arduino_k230 fall detection
  • 11.arduino_k230 palm detection
  • 12.arduino_k230 gesture recognition
  • 13.arduino_k230 OCR character recognition
  • 14.arduino_k230 object detection
  • 15.arduino_k230 target tracking
  • 16.arduino_k230 self-learning object recognition
  • 17.arduino_k230 license plate recognition
Microbit-K230
  • 1.microbit_k230 color recognition
  • 2.microbit_k230 barcode recognition
  • 3.microbit_k230 QR code recognition
  • 4.microbit_k230 Apriltag code recognition
  • 5.microbit_k230 DM code recognition
  • 6.microbit_k230 face detection
  • 7.microbit_k230 looking direction
  • 8.microbit_k230 face recognition
  • 9.microbit_k230 human body detection
  • 10.microbit_k230 fall detection
  • 11.microbit_k230 palm detection
  • 12.microbit_k230 gesture recognition
  • 13.microbit_k230 OCR character recognition
  • 14.microbit_k230 object detection
  • 15.microbit_k230 target tracking
  • 16.microbit_k230 self-learning object recognition
  • 17.microbit_k230 license plate recognition
MSPM0G3519-K230
  • 1. K230 Color Recognitionnew
  • 2. K230 Barcode Recognitionnew
  • 3. K230 QR Code Recognitionnew
  • 4. K230 Apriltag Code Recognitionnew
  • 5. K230 DM Code Recognitionnew
  • 6. K230 Face Detectionnew
  • 7. K230 Gaze Directionnew
  • 8. K230 Face Recognitionnew
  • 9. K230 Human Body Detectionnew
  • 10. K230 Fall Detectionnew
  • 11. K230 Palm Detectionnew
  • 12. K230 Gesture Recognitionnew
  • 13. K230 OCR Character Recognitionnew
  • 14. K230 Object Detectionnew
  • 15. K230 Target Trackingnew
  • 16. K230 Self-learning Object Recognitionnew
  • 17. K230 License Plate Recognitionnew
18.Extension case (purchase separately)
For 2DOF Electric Platform
  • 1.Moving target control and automatic tracking system
  • 2.Human body recognition alarm
  • 3.Gesture Recognition
  • 4.Rock Paper Scissors
  • 5.Fruit sorting
  • 6.Color Tracking
  • 7.Face Tracking
MSPM0G3507 wheeled chassis V1/V2 combined with K230 application case
  • 1.Visual tracking
  • 2.Color tracking
  • 3.Color response
  • 4.Road sign recognition
  • 5.Machine code tracking
  • 6.QR code recognition action
  • 7.Autonomous avoid
  • 8.License plate tracking
  • 9.Face tracking
  • 10.Gaze direction tracking
  • 11.Palm tracking
  • 12.Target tracking
  • 13.Human body tracking
  • 14.OCR character recognition action
STM32 wheeled chassis V1/V2 combined with K230 application case
  • 1.Visual tracking
  • 2.Color tracking
  • 3.Color response
  • 4.Road sign recognition
  • 5.Machine code tracking
  • 6.QR code recognition action
  • 7.Autonomous avoid
  • 8.License plate tracking
  • 9.Face tracking
  • 10.Gaze direction tracking
  • 11.Palm tracking
  • 12.Target tracking
  • 13.Human body tracking
  • 14.OCR character recognition action
MSPM0G3519 wheeled chassis V1/V2 combined with K230 application case
  • 1.Visual trackingnew
  • 2.Color trackingnew
  • 3.Color responsenew
  • 4.Road sign recognitionnew
  • 5.Machine code trackingnew
  • 6.QR code recognition actionnew
  • 7.Autonomous avoidnew
  • 8.License plate trackingnew
  • 9.Face trackingnew
  • 10.Gaze direction trackingnew
  • 11.Palm trackingnew
  • 12.Target trackingnew
  • 13.Human body trackingnew
  • 14.OCR character recognition actionnew
19. Expansion case(purchase separately)new
  • 1.Motion target control and Auto track system
  • 2.Vehicle-mounted balance ball motion control system
Download
  • Manual
  • CanMV IDE
  • Software Tools
  • Firmware
  • Source Code
  • Appendix
Download ZIP

Welcome to K230 Vision Module repository

02.Core Engine Initialization

Hardware Initialization and LVGL Binding

Hardware Initialization and LVGL Binding1. Course Objectives2. Core Source Code Analysis2.1 Display System Initialization (display_init)2.2 LVGL Graphics Library Initialization (lvgl_init)2.3 Core Callback: disp_drv_flush_cb3. Touch Screen Driver (touch_screen Class)4. Summary

1. Course Objectives

In the previous section, we saw that main.py called start(). In this lesson, we will dive deep into ybMain/main.py to analyze how the system "lights up" the screen and binds the LVGL graphics library with the K230's underlying hardware (display screen, touch screen).

2. Core Source Code Analysis

File Path: src/canmv/port/builtin_py/ybMain/main.py

2.1 Display System Initialization (display_init)

K230's display system is more complex than ordinary microcontrollers, involving the concept of PipeLine (video path) (using Pipeline is to facilitate multi-channel AI vision analysis tasks).

def display_init():
    global pl, config
    try:
        # ...
        display_mode = "lcd"
        display_size = [DISPLAY_WIDTH, 480]
        rgb888p_size = [640, 480]
        
        # Initialize PipeLine, this is the core of K230 multimedia framework
        # osd_layer_num=4 means 4 layers are reserved for screen display (On-Screen Display)
        pl = PipeLine(rgb888p_size=rgb888p_size, display_size=display_size, display_mode=display_mode, osd_layer_num=4)
        
        # Create display channel
        pl.create(...)
    except Exception as e:
        debug_print("display_init", e)

Key Points:

  • PipeLine: This is a hardware channel specifically for processing image data. The GUI does not directly write to video memory, but acts as a "layer" overlaid on video output. This allows us to easily display camera footage in the GUI background.

2.2 LVGL Graphics Library Initialization (lvgl_init)

LVGL is a pure software graphics library that doesn't know how to draw pixels. We need to provide a "callback function" to tell it how to push pixels to the screen.

​x
def lvgl_init():
    # 1. Initialize LVGL library
    lv.init()
​
    # 2. Create display driver
    disp_drv = lv.disp_create(DISPLAY_WIDTH, DISPLAY_HEIGHT)
    
    # 3. Set refresh callback function (most important part!)
    disp_drv.set_flush_cb(disp_drv_flush_cb)
​
    # 4. Allocate double buffers (Double Buffering)
    disp_img1 = image.Image(DISPLAY_WIDTH, DISPLAY_HEIGHT, image.BGRA8888)
    disp_img2 = image.Image(DISPLAY_WIDTH, DISPLAY_HEIGHT, image.BGRA8888)
    disp_drv.set_draw_buffers(disp_img1.bytearray(), disp_img2.bytearray(), ...)
    
    # 5. Initialize input device (touch screen)
    global_touch_dev = touch_screen()

2.3 Core Callback: disp_drv_flush_cb

This is the bridge connecting software (LVGL) and hardware (Display).

xxxxxxxxxx
def disp_drv_flush_cb(disp_drv, area, color):
    # When LVGL finishes rendering part of the screen, this function is called
    # color: points to the rendered pixel data
    
    if disp_drv.flush_is_last() == True:
        # If this is the last piece of data for the current frame, call Display.show_image to display
        if disp_img1.virtaddr() == ...:
            Display.show_image(disp_img1)
        else:
            Display.show_image(disp_img2)
            
    # Tell LVGL that refresh is complete, ready for next frame
    disp_drv.flush_ready()

Working Principle Analysis:

  1. LVGL draws the interface in memory.
  2. Call disp_drv_flush_cb, passing in the drawn data.
  3. We call K230's Display.show_image() to send the data from this memory to the display controller.
  4. Using double buffering (disp_img1, disp_img2) can avoid screen tearing and ensure smooth UI.

3. Touch Screen Driver (touch_screen Class)

To make the screen respond to clicks, we need to convert physical touch coordinates to coordinates that LVGL understands.

xxxxxxxxxx
class touch_screen():
    def __init__(self):
        # Create LVGL input driver
        self.indev_drv = lv.indev_create()
        self.indev_drv.set_type(lv.INDEV_TYPE.POINTER)
        self.indev_drv.set_read_cb(self.callback) # Register callback
​
    def callback(self, driver, data):
        # Read physical touch data
        tp = self.touch.read(1)
        if len(tp):
            # Assign physical coordinates to LVGL data structure
            data.point = lv.point_t({'x': tp[0].x, 'y': tp[0].y})
            data.state = lv.INDEV_STATE.PRESSED
        else:
            data.state = lv.INDEV_STATE.RELEASED

4. Summary

In this lesson, we learned about the "foundation" of the GUI system:

  1. PipeLine is responsible for opening up the video path.
  2. LVGL is responsible for generating graphics data.
  3. flush_cb is responsible for moving graphics data to the video path.
  4. touch_screen is responsible for translating finger movements into click events.

In the next section, we will explain the core part of the GUI: AppManager, and see how it manages those colorful application icons.

GUI System Architecture
Application Discovery Mechanism in GUI

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