python - 在 GUI 中模拟从一个无限循环到另一个无限循环的键盘按下

Question

我正在尝试做一个 GUI，用户将通过眨眼来控制按钮。基本上，短暂的闪烁应该模拟按下键盘键 Tab（从一个按钮移动到另一个按钮），而长时间的闪烁应该模拟按下键 Space（输入所选按钮）。

这个想法是，窗口和眨眼检测系统这两个进程同时运行。所以在这里我遇到了所有问题：因为它们都是 while 循环，所以我不能同时运行它们。

在我附加的代码中，我通过首先打开主窗口然后单击开始按钮来运行 eyeblink 系统来简化此操作。使用 pyautogui.press() 我想模拟主窗口中的键盘按下。但是，当眨眼检测系统工作时，主窗口不再可访问（您不能按任何东西）。

我试图唤起每一帧的闪烁功能，而不是无限循环，但它太慢并且无法正确检测到闪烁。我也尝试过多处理和“Python 意外退出”，没有显示错误，所以不确定发生了什么（我用来尝试这个的代码在最后注释）。我也尝试了线程，但以一种简单的方式没有错误，但也没有出现任何错误（同样，我用来尝试这个的代码最后被注释了）。在这里我附上文件的链接（.mp3、.xml、.py）： https ://drive.google.com/drive/folders/1U2uwHXzl2MtSTlAKw1L68L3xcRmelP2d?usp=sharing

我刚开始使用 Python，所以我的知识不高，我的时间不多了，我被困在这一点上……所以欢迎任何帮助！提前致谢 ;）

MacOs Python 2.7 OpenCV 3.4 Tkinter（我之所以选择它是因为它易于处理，但如果有必要我愿意更改）

# Ventana+Blink
from Tkinter import *
import numpy as np
import cv2
# To emulate a keyboard pressing
import pyautogui
import time
# To play the sounds
import subprocess 
# from Blink import funcion_blink
# from multiprocessing import Process
# import threading 


def Onbutton_clicked():
    # while True:
    # Repeating 2 times the sound
    for x in range (0,2):
        subprocess.call(['afplay', 'alarm2.mp3'])

def Onbutton2_clicked():
    # Repeating 1 times the sound
    for x in range (0,1):
        subprocess.call(['afplay', 'sound.mp3'])


def execute_func1():
    print('enter\n')
    pyautogui.press('space')  # press the Space key
    for x in range (1,2):
        subprocess.call(['afplay', 'unconvinced.mp3'])

def execute_func2():
    print('tab\n')
    pyautogui.press('tab')  # press the Tab key
    for x in range (1,2):
        subprocess.call(['afplay', 'case-closed.mp3'])

def execute_func3():
    print('space\n')
    pyautogui.press('space')  # press the Space key
    for x in range (1,2):
        subprocess.call(['afplay', 'cheerful.mp3'])


# ----- Eyeblink detection system -----
def funcion_blink():
#XML classifiers should be in the folder with this file
    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
    eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')

    video_capture = cv2.VideoCapture(0)
    det = 0
    n = 0

    while True:
    # Capture frame-by-frame
        ret, frame = video_capture.read()
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        faces = face_cascade.detectMultiScale(
            gray,
            scaleFactor=1.1,
            minNeighbors=5,
            minSize=(100, 100),
            flags=cv2.CASCADE_SCALE_IMAGE
        )

            # Draw a rectangle around the faces
        for (x, y, w, h) in faces:
            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
            roi_gray = gray[y:y + h, x:x + w]
            roi_color = frame[y:y + h, x:x + w]
            eyes = eye_cascade.detectMultiScale(
                roi_gray,
                scaleFactor = 1.1,
                minNeighbors = 5,
                minSize = (30, 30),
                flags = cv2.CASCADE_SCALE_IMAGE
            )
            for (ex, ey, ew, eh) in eyes:
                cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
            face_img = gray[x:x + w, y:y + h]
            face_res = cv2.resize(face_img, (100, 100), interpolation=cv2.INTER_CUBIC)
            eye_reg = face_res[15:85, 20:50]
            cv2.rectangle(frame, (x+15*w/100, y + 2*h / 10), (x + w*85/100, y + (5 * h / 10)), (0, 0, 255), 2)
            if (det < 10):
                tmpl_eyes = eye_reg
                det = det + 1
                print('template acquired\n')
            elif (det == 10):
                        # template matching
                wt, ht = tmpl_eyes.shape[::-1]
                        #res_templ = cv2.matchTemplate(eye_reg, tmpl_eyes, cv2.TM_CCORR_NORMED)
                res_templ = cv2.matchTemplate(eye_reg, tmpl_eyes, cv2.TM_CCOEFF_NORMED)
                min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res_templ)
                            # print(max_val, n)
                        #value 0.92 should be adapted to the conditions and camera position
                if (max_val>0.90):
                    n=n+1
                else:
                    if (n>=12):
                        execute_func1()
                                #here should go the code that triggers some action when the person blinks??                 
                    elif (n>=6):
                        execute_func2()              
                    elif (n>=3):
                        execute_func3()

                    n = 0
                print(max_val, n)

        # Display the resulting frame
        cv2.imshow('Video', frame)

        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    # When everything is done, release the capture
    cv2.destroyAllWindows()
    video_capture.release()


# ---- Main window ----
def main_window():
    root= Tk()   
    root.geometry('700x700')

    # Create the buttons of the main window
    button=Button(root, text='alarm', command=Onbutton_clicked)
    button.bind('<Return>', Onbutton_clicked)
    button.pack()

    button2=Button(root, text='extra', command=Onbutton2_clicked)
    button2.bind('<Return>', Onbutton2_clicked)
    button2.pack()

    # By pressing this button we start running the eyeblink detection system
    button3=Button(root, text='Start', command=funcion_blink)
    button3.bind('<Button-1>', funcion_blink)
    button3.pack()

    # To maintain the window until you close it
    root.mainloop()

# Execute the main window
main_window()


# ---- Trials ----

# while True:
#     main_window()
#     funcion_blink()  
# It just plays one function and when it finishes it plays the next one

# Multiprocessing
# if __name__ == '__main__':
#     Process(target=main_window).start()
#     Process(target=funcion_blink).start()
# PYTHON QUITS UNEXPECTADLY

# Threading
# p1 = threading.Thread(target=main_window, args=())
# p2 = threading.Thread(target=funcion_blink, args=())
# p1.start()
# p2.start()

标签： pythonmultithreadinguser-interfaceinfinite-loopkeypress