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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

1.Touch point detection

Touch point Detection

Touch point DetectionExample ResultsCode Explanation1. Importing Necessary Modules2. Initializing the touch sensor and screen resolution3. Define touch point display function3.1 Creating and Initializing the Background Image3.2 Initializing the Display and Media Manager4. Touch Detection and Processing Logic4.1 Defining Touch State Variables4.2 Main Loop: Reading and Processing Touch Data4.2.1 Handling Touch Press Events4.2.2 Handling Touch Up Events4.3 Update Display5. Exception Handling and Resource Release6. Main program entry

Example Results

The example source code file for this section is named [1.show_touch_info.py]

Connect to the IDE, run the code in the IDE, and click anywhere on the screen to see the touch point information appear.

image-20251011181707934

Code Explanation

This section will detail the functionality and implementation logic of 1.show_touch_info.py to help users understand how to capture touch point information using the touch sensor and display it on the screen.

1. Importing Necessary Modules

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import time, os, urandom, sys
from media.display import *
from media.media import *
from machine import TOUCH
  • time, os, urandom, sys: These are system-related modules used for time control, operating system functions, random number generation, and system operations. - media.display and media.media: For screen display and media resource management.
  • machine.TOUCH: For initializing and operating the touch sensor.

2. Initializing the touch sensor and screen resolution

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tp = TOUCH(0)
DISPLAY_WIDTH = 640
DISPLAY_HEIGHT = 480
  • TOUCH(0): Initializes the touch sensor, tp is used to read touch data later.
  • DISPLAY_WIDTH and DISPLAY_HEIGHT: Define screen resolution constants, which are 640x480 respectively.

3. Define touch point display function

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def touch_point_display():
    print("Touch point display test")
  • touch_point_display() is the main function responsible for handling touch point detection and display.

3.1 Creating and Initializing the Background Image

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img = image.Image(DISPLAY_WIDTH, DISPLAY_HEIGHT, image.RGB888)
​
def clear_and_reset_background():
    """Clear the image and reset to white background"""
    img.clear()
    img.draw_rectangle(0, 0, DISPLAY_WIDTH, DISPLAY_HEIGHT, color=(255,255,255), fill=True)
​
clear_and_reset_background()
  • Create an image object img in RGB888 format, sized to the screen resolution.
  • Define the clear_and_reset_background() function to clear the image contents and reset the screen to a white background.
  • Call this function during initialization to ensure the screen is initially white.

3.2 Initializing the Display and Media Manager

xxxxxxxxxx
Display.init(Display.ST7701, width = DISPLAY_WIDTH, height = DISPLAY_HEIGHT, to_ide = True)
MediaManager.init()
  • Initialize the display using the ST7701 driver, set the resolution to 640x480, and enable IDE output ( to_ide = True).
  • Initialize the media manager to manage display-related resources.

4. Touch Detection and Processing Logic

4.1 Defining Touch State Variables

xxxxxxxxxx
current_touch_active = False
last_touch_down_time = 0
  • current_touch_active: A Boolean value that records whether a touch is currently active.
  • last_touch_down_time: Records the time of the last touch-down event.

4.2 Main Loop: Reading and Processing Touch Data

xxxxxxxxxx
while True:
    os.exitpoint()
    point = tp.read(1)
  • Use tp.read(1) to read touch data, and point to store touch point information.
4.2.1 Handling Touch Press Events
xxxxxxxxxx
if len(point):
    pt = point[0]
    if pt.event == TOUCH.EVENT_DOWN:
        clear_and_reset_background()
        circle_radius = 20
        img.draw_circle(pt.x, pt.y, circle_radius, color=(255, 0, 0), thickness=3)
        coord_text = f"({pt.x}, {pt.y})"
        text_x = pt.x + 30
        text_y = pt.y - 30
        if text_x + 100 > DISPLAY_WIDTH:
            text_x = pt.x - 100
        if text_y < 20:
            text_y = pt.y + 40
        img.draw_string_advanced(text_x, text_y, 24, coord_text, color=(0, 0, 0))
        current_touch_active = True
        last_touch_down_time = time.time()
        print(f"Touch detected at: {coord_text}")
  • When a touch down event ( TOUCH.EVENT_DOWN) is detected:

    • Clear the previous image and reset the background to white.
    • Draw a red circle with a radius of 20 at the touch point.
    • Calculate and display the touch point's coordinates in text, adjusting the text position based on the touch point to ensure it stays within the screen boundaries.
    • Update the touch state variable current_touch_active to True and record the touch down time.
    • Print the touch point coordinates to the console.
4.2.2 Handling Touch Up Events
xxxxxxxxxx
elif pt.event == TOUCH.EVENT_UP:
    current_touch_active = False
  • When a touch up event (TOUCH.EVENT_UP) is detected, current_touch_active is set to False, indicating that the touch has ended.

4.3 Update Display

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Display.show_image(img)
time.sleep(0.05)
  • Use Display.show_image(img) to update the screen to show the current image.
  • time.sleep(0.05) updates every 50 milliseconds to avoid performance issues caused by excessively fast refreshes.

5. Exception Handling and Resource Release

xxxxxxxxxx
except KeyboardInterrupt as e:
    print("User stop: ", e)
except BaseException as e:
    print(f"Exception {e}")
​
Display.deinit()
os.exitpoint(os.EXITPOINT_ENABLE_SLEEP)
time.sleep_ms(100)
MediaManager.deinit()
  • Catch KeyboardInterrupt (user interrupt) and BaseException (other exceptions) and print relevant information.
  • Call Display.deinit() to deinitialize the display.
  • Call MediaManager.deinit() to release media resources.

6. Main program entry

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if __name__ == "__main__":
    os.exitpoint(os.EXITPOINT_ENABLE)
    touch_point_display()
  • Enable the exit point (EXITPOINT_ENABLE) and call the touch_point_display() function to start the touch point display test.
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