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Raspbot📖
1.First Trial and Installation
  • 1.1 Installation video
  • 1.2 First Trial
2.Remote control course
  • 2.1 APP control car
  • 2.2 IR control car
3.Preparation
  • 3.1 Preparation
  • 3.2 Run a code on JupyterLab
  • 3.5 TF card expand capacity
4.OpenCV Basic course
A.Getting started with OpenCV
  • 1.Introduction of OpenCV
  • 2.OpenCV image read and display
  • 3.OpenCV image write
  • 4.OpenCV image quality
  • 5.OpenCV pixel operation
B.OpenCV Geometric transformat
  • 1.Picture Zoom
  • 2.Picture Cut
  • 3.Picture Shift
  • 4.Picture Mirroring
  • 5.Affine Map
  • 6.Picture Rotation
  • 7.Perspective Transformation
C.OpenCV picture processing
  • 1.Grayscale processing
  • 2.Image Binarization
  • 3.Edge detection
  • 4.Drawing line segment
  • 5.Drawing rectangle circle
  • 6.Drawing text picture
D.OpenCV image beautification
  • 1.Histogram of color pictures
  • 2.Histogram equalization
  • 3.Image restoration
  • 4.Brightness enhancement
  • 5.Skin whitening
  • 6.Gaussian mean filtering
  • 7.Median filtering
E.OpenCV machine learning
  • 1.KNN recognition of handwritten numbers
  • 2.CNN recognition of handwritten numbers
  • 3.SVM recognition of handwritten numbers
5.Hardware Control course
  • 5.1 Drive buzzer
  • 5.2 Drive motor
  • 5.3 Drive servo
  • 5.4 Ultrasonic ranging
  • 5.5 Ultrasonic avoid
  • 5.6 Ultrasonic+IR avoid
  • 5.7 Tracking
  • 5.8 Restricting
  • 5.9 Drive LED
  • 5.10 IR control test
  • 5.11 IR control car
6.AI vision course
  • 6.1 Driver camera
  • 6.2 Color recognition
  • 6.3 HSV value test
  • 6.4 Camera color tracking
  • 6.5 Car color tracking
  • 6.6 Tensorflow object recognition
  • 6.7 QR code recognition
  • 6.8 QR code control
  • 6.9 Face detection
  • 6.10 Face tracking
  • 6.11 Autopilot
7.Battery and charging
  • Battery and charging
Download
  • APP(iOS/Android)
  • Code
  • Download image
  • Instruction manual
  • More Annex
Download ZIP
FAQ
  • 1、Raspbot-Raspberry Pi 4b version desktop connection WiFi method
  • 2、Can't connect your home WiFi
  • 3、How to check IIC function on Raspbot
  • 4、Gesture recognition cannot work normally.
  • 5、How to write image file into SD card

Welcome to Raspbot repository

6.8 QR code control


As shown in the figure below, the five QR codes correspond to different functions and can be used to control the movement of the robot.

image.png  image.png

forword                                back

image.png    image.png

left                       right

image.png 

Stop

/home/pi/Yahboom_Project/Raspbot/3.AI Vision course/07.QR code control/QR code control.ipynb

#bgr8 to jpeg 
import enum
import cv2
 
def bgr8_to_jpeg(value, quality=75):
    return bytes(cv2.imencode('.jpg', value)[1])

# import the necessary packages
#import simple_barcode_detection
import cv2
import numpy as np
import pyzbar.pyzbar as pyzbar
from PIL import Image
import ipywidgets.widgets as widgets
 
import YB_Pcb_Car
car = YB_Pcb_Car.YB_Pcb_Car()
 
image_widget = widgets.Image(format='jpeg', width=320, height=240)
display(image_widget)

def detect_control(info):
    if info == "forward":
        car.Car_Run(60,60)         # advance
    elif info == "back":
        car.Car_Back(60,60)        #back
    elif info == "left":
        car.Car_Spin_Left(60,60)    #spin left
    elif info == "right":
        car.Car_Spin_Right(60,60)   #spin right
    elif info == "stop":              #stop
        car.Car_Stop()

def decodeDisplay(image):
    barcodes = pyzbar.decode(image)
    for barcode in barcodes:
        (x, y, w, h) = barcode.rect
        cv2.rectangle(image, (x, y), (x + w, y + h), (225, 225, 225), 2)
        barcodeData = barcode.data.decode("utf-8")
        barcodeType = barcode.type
        text = "{} ({})".format(barcodeData, barcodeType)
        cv2.putText(image, text, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (225, 225, 225), 2)
        
        print("[INFO] Found {} barcode: {}".format(barcodeType, barcodeData))
        detect_control(barcodeData)
    return image
 
def detect():
    camera = cv2.VideoCapture(0)
    camera.set(3, 320)
    camera.set(4, 240)
    camera.set(5, 30)  
    # fourcc = cv2.VideoWriter_fourcc(*"MPEG")
    camera.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M', 'J', 'P', 'G'))
    camera.set(cv2.CAP_PROP_BRIGHTNESS, 40)
    camera.set(cv2.CAP_PROP_CONTRAST, 50)
    camera.set(cv2.CAP_PROP_EXPOSURE, 156)
    ret, frame = camera.read()
    image_widget.value = bgr8_to_jpeg(frame)
    try:
        while True:
            ret, frame = camera.read()
            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
            im = decodeDisplay(gray)
            image_widget.value = bgr8_to_jpeg(im)
            cv2.waitKey(5)
    except:
        camera.release()

detect()
car.Car_Stop()
del car
print("Ending")

 

 


QR code recognition
Face detection

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