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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.Chart animation

4 Chart animation

4 Chart animation4.1 experimental goals 4.2 experimental procedure4.3 experimental results4.4 experiment summary

4.1 experimental goals

In this lesson, you will learn how to animate a chart.

The reference code path for this experiment is :CanMV\04-GUI\chart_anime.py

 

4.2 experimental procedure

The factory firmware of the module has been integrated with the lvgl graphical library. If you have downloaded other firmware, please burn it back to the factory firmware before experimenting.

  1. Import the relevant libraries and initialize the lvgl, register the display interface, and register the input interface.

  2. Create a new animation class, Anim.

class Anim(lv.anim_t):
    def __init__(self, obj, val, size, exec_cb, path_cb, time=500, playback = False, ready_cb=None):
        super().__init__()
        lv.anim_init(self)
        lv.anim_set_time(self, time, 0)
        lv.anim_set_values(self, val, val+size)
        if callable(exec_cb):
            lv.anim_set_custom_exec_cb(self, exec_cb)
        else:
            lv.anim_set_exec_cb(self, obj, exec_cb)
        lv.anim_set_path_cb(self, path_cb )
        if playback: lv.anim_set_playback(self, 0)
        if ready_cb: lv.anim_set_ready_cb(self, ready_cb)
        lv.anim_create(self)
  1. Create a new animated chart class, AnimatedChart.

​x
class AnimatedChart(lv.chart):
    def __init__(self, parent, val, size):
        super().__init__(parent)
        self.val = val
        self.size = size
        self.max = 2000
        self.min = 500
        self.factor = 100
        self.anim_phase1()

    def anim_phase1(self):
        Anim(
            self,
            self.val,
            self.size,
            lambda a, val: self.set_range(0, val),
            lv.anim_path_ease_in,
            ready_cb=lambda a:self.anim_phase2(),
            time=(self.max * self.factor) // 100)

    def anim_phase2(self):
        Anim(
            self,
            self.val+self.size,
            -self.size,
            lambda a, val: self.set_range(0, val),
            lv.anim_path_ease_out,
            ready_cb=lambda a:self.anim_phase1(),
            time=(self.min * self.factor) // 100)
  1. Configure the parameters for the animated chart.

xxxxxxxxxx
scr = lv.obj()
chart = AnimatedChart(scr, 100, 1000)
chart.set_width(scr.get_width() - 100)
chart.set_height(scr.get_height() - 60)
chart.align(scr, lv.ALIGN.CENTER, 0, 0)
series1 = chart.add_series(lv.color_hex(0xFF0000))
chart.set_type(chart.TYPE.POINT | chart.TYPE.LINE)
chart.set_series_width(3)
chart.set_range(0,100)
chart.init_points(series1, 10)
chart.set_points(series1, [10,20,35,20,10,40,51,90,95,80])
chart.set_x_tick_texts('a\nb\nc\nd\ne', 2, lv.chart.AXIS.DRAW_LAST_TICK)
chart.set_x_tick_length(10, 5)
chart.set_y_tick_texts('1\n2\n3\n4\n5', 2, lv.chart.AXIS.DRAW_LAST_TICK)
chart.set_y_tick_length(10, 5)
chart.set_div_line_count(3, 3)
chart.set_margin(30)
  1. Create a new slider to change the speed at which the animation changes.

xxxxxxxxxx
def on_slider_changed(self, obj=None, event=-1):
    chart.factor = slider.get_value()

slider = lv.slider(scr)
slider.align(chart, lv.ALIGN.OUT_RIGHT_TOP, 10, 0)
slider.set_width(30)
slider.set_height(chart.get_height())
slider.set_range(10, 200)
slider.set_value(chart.factor, 0)
slider.set_event_cb(on_slider_changed)
  1. Load the lvgl project object. Since the images of the lvgl need to be updated in real time, the tasks of the lvgl need to be refreshes every 5 milliseconds.

xxxxxxxxxx
lv.scr_load(scr)
tim = time.ticks_ms()
while True:
    if time.ticks_ms()-tim > 5:
        tim = time.ticks_ms()
        lv.task_handler()
        lv.tick_inc(5)

 

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.

You can see that a chart is displayed in the middle of the LCD screen, and the curve in the chart will change. You can change the speed of the curve in the chart by sliding the slider on the right.

image-20230214180124071

 

4.4 experiment summary

Animating a chart is a complex task, so you'll need to create two new animation-related classes to store the corresponding parameter information. The slider changes the rate at which the animation takes place. It doesn't take effect until the slider has finished animating, that is, until all the curves have reached their lowest point.

 

Slider
Multi-label layout

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