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7. Computer Vision¶

This project will officially enter the field of computer vision!

Run the Code

cd ~/picar-x/example
sudo python3 7.display.py

View the Image

After the code runs, the terminal will display the following prompt:

No desktop !
* Serving Flask app "vilib.vilib" (lazy loading)
* Environment: production
WARNING: Do not use the development server in a production environment.
Use a production WSGI server instead.
* Debug mode: off
* Running on http://0.0.0.0:9000/ (Press CTRL+C to quit)

Then you can enter http://<your IP>:9000/mjpg in the browser to view the video screen. such as: https://192.168.18.113:9000/mjpg

../_images/display.png

After the program runs, you will see the following information in the final:

  • Input key to call the function!

  • q: Take photo

  • 1: Color detect : red

  • 2: Color detect : orange

  • 3: Color detect : yellow

  • 4: Color detect : green

  • 5: Color detect : blue

  • 6: Color detect : purple

  • 0: Switch off Color detect

  • r: Scan the QR code

  • f: Switch ON/OFF face detect

  • s: Display detected object information

Please follow the prompts to activate the corresponding functions.

  • Take Photo

    Type q in the terminal and press Enter. The picture currently seen by the camera will be saved (if the color detection function is turned on, the mark box will also appear in the saved picture). You can see these photos from the /home/{username}/Pictures/ directory of the Raspberry Pi. You can use tools such as Filezilla Software to transfer photos to your PC.

  • Color Detect

    Entering a number between 1~6 will detect one of the colors in “red, orange, yellow, green, blue, purple”. Enter 0 to turn off color detection.

    ../_images/DTC2.png

    Note

    You can download and print the PDF Color Cards for color detection.

  • Face Detect

    Type f to turn on face detection.

    ../_images/DTC5.png

  • QR Code Detect

    Enter r to open the QR code recognition. No other operations can be performed before the QR code is recognized. The decoding information of the QR code will be printed in the terminal.

    ../_images/DTC4.png

  • Display Information

    Entering s will print the information of the face detection (and color detection) target in the terminal. Including the center coordinates (X, Y) and size (Weight, height) of the measured object.

Code

from pydoc import text
from vilib import Vilib
from time import sleep, time, strftime, localtime
import threading
import readchar
import os

flag_face = False
flag_color = False
qr_code_flag = False

manual = '''
Input key to call the function!
    q: Take photo
    1: Color detect : red
    2: Color detect : orange
    3: Color detect : yellow
    4: Color detect : green
    5: Color detect : blue
    6: Color detect : purple
    0: Switch off Color detect
    r: Scan the QR code
    f: Switch ON/OFF face detect
    s: Display detected object information
'''

color_list = ['close', 'red', 'orange', 'yellow',
        'green', 'blue', 'purple',
]

def face_detect(flag):
    print("Face Detect:" + str(flag))
    Vilib.face_detect_switch(flag)


def qrcode_detect():
    global qr_code_flag
    if qr_code_flag == True:
        Vilib.qrcode_detect_switch(True)
        print("Waitting for QR code")

    text = None
    while True:
        temp = Vilib.detect_obj_parameter['qr_data']
        if temp != "None" and temp != text:
            text = temp
            print('QR code:%s'%text)
        if qr_code_flag == False:
            break
        sleep(0.5)
    Vilib.qrcode_detect_switch(False)


def take_photo():
    _time = strftime('%Y-%m-%d-%H-%M-%S',localtime(time()))
    name = 'photo_%s'%_time
    username = os.getlogin()

    path = f"/home/{username}/Pictures/"
    Vilib.take_photo(name, path)
    print('photo save as %s%s.jpg'%(path,name))


def object_show():
    global flag_color, flag_face

    if flag_color is True:
        if Vilib.detect_obj_parameter['color_n'] == 0:
            print('Color Detect: None')
        else:
            color_coodinate = (Vilib.detect_obj_parameter['color_x'],Vilib.detect_obj_parameter['color_y'])
            color_size = (Vilib.detect_obj_parameter['color_w'],Vilib.detect_obj_parameter['color_h'])
            print("[Color Detect] ","Coordinate:",color_coodinate,"Size",color_size)

    if flag_face is True:
        if Vilib.detect_obj_parameter['human_n'] == 0:
            print('Face Detect: None')
        else:
            human_coodinate = (Vilib.detect_obj_parameter['human_x'],Vilib.detect_obj_parameter['human_y'])
            human_size = (Vilib.detect_obj_parameter['human_w'],Vilib.detect_obj_parameter['human_h'])
            print("[Face Detect] ","Coordinate:",human_coodinate,"Size",human_size)


def main():
    global flag_face, flag_color, qr_code_flag
    qrcode_thread = None

    Vilib.camera_start(vflip=False,hflip=False)
    Vilib.display(local=True,web=True)
    print(manual)

    while True:
        # readkey
        key = readchar.readkey()
        key = key.lower()
        # take photo
        if key == 'q':
            take_photo()
        # color detect
        elif key != '' and key in ('0123456'):  # '' in ('0123') -> True
            index = int(key)
            if index == 0:
                flag_color = False
                Vilib.color_detect('close')
            else:
                flag_color = True
                Vilib.color_detect(color_list[index]) # color_detect(color:str -> color_name/close)
            print('Color detect : %s'%color_list[index])
        # face detection
        elif key =="f":
            flag_face = not flag_face
            face_detect(flag_face)
        # qrcode detection
        elif key =="r":
            qr_code_flag = not qr_code_flag
            if qr_code_flag == True:
                if qrcode_thread == None or not qrcode_thread.is_alive():
                    qrcode_thread = threading.Thread(target=qrcode_detect)
                    qrcode_thread.setDaemon(True)
                    qrcode_thread.start()
            else:
                if qrcode_thread != None and qrcode_thread.is_alive():
                # wait for thread to end
                    qrcode_thread.join()
                    print('QRcode Detect: close')
        # show detected object information
        elif key == "s":
            object_show()

        sleep(0.5)


if __name__ == "__main__":
    main()

How it works?

The first thing you need to pay attention to here is the following function. These two functions allow you to start the camera.

Vilib.camera_start()
Vilib.display()

Functions related to “object detection”:

  • Vilib.face_detect_switch(True) : Switch ON/OFF face detection

  • Vilib.color_detect(color) : For color detection, only one color detection can be performed at the same time. The parameters that can be input are: "red", "orange", "yellow", "green", "blue", "purple"

  • Vilib.color_detect_switch(False) : Switch OFF color detection

  • Vilib.qrcode_detect_switch(False) : Switch ON/OFF QR code detection, Returns the decoded data of the QR code.

  • Vilib.gesture_detect_switch(False) : Switch ON/OFF gesture detection

  • Vilib.traffic_sign_detect_switch(False) : Switch ON/OFF traffic sign detection

The information detected by the target will be stored in the detect_obj_parameter = Manager().dict() dictionary.

In the main program, you can use it like this:

Vilib.detect_obj_parameter['color_x']

The keys of the dictionary and their uses are shown in the following list:

  • color_x: the x value of the center coordinate of the detected color block, the range is 0~320

  • color_y: the y value of the center coordinate of the detected color block, the range is 0~240

  • color_w: the width of the detected color block, the range is 0~320

  • color_h: the height of the detected color block, the range is 0~240

  • color_n: the number of detected color patches

  • human_x: the x value of the center coordinate of the detected human face, the range is 0~320

  • human_y: the y value of the center coordinate of the detected face, the range is 0~240

  • human_w: the width of the detected human face, the range is 0~320

  • human_h: the height of the detected face, the range is 0~240

  • human_n: the number of detected faces

  • traffic_sign_x: the center coordinate x value of the detected traffic sign, the range is 0~320

  • traffic_sign_y: the center coordinate y value of the detected traffic sign, the range is 0~240

  • traffic_sign_w: the width of the detected traffic sign, the range is 0~320

  • traffic_sign_h: the height of the detected traffic sign, the range is 0~240

  • traffic_sign_t: the content of the detected traffic sign, the value list is [‘stop’,’right’,’left’,’forward’]

  • gesture_x: The center coordinate x value of the detected gesture, the range is 0~320

  • gesture_y: The center coordinate y value of the detected gesture, the range is 0~240

  • gesture_w: The width of the detected gesture, the range is 0~320

  • gesture_h: The height of the detected gesture, the range is 0~240

  • gesture_t: The content of the detected gesture, the value list is [“paper”,”scissor”,”rock”]

  • qr_date: the content of the QR code being detected

  • qr_x: the center coordinate x value of the QR code to be detected, the range is 0~320

  • qr_y: the center coordinate y value of the QR code to be detected, the range is 0~240

  • qr_w: the width of the QR code to be detected, the range is 0~320

  • qr_h: the height of the QR code to be detected, the range is 0~320