如何解决如何在 tkinter 中使用另一个 pyton 项目启动项目?
我是 tkinter 的新手。我有一个实时情绪检测项目。我从另一个 .py 文件调用,它们都在同一个文件中。视频捕获部分在 test.py 中定义了 cap,我调用了 cap 方法和添加按钮。但是当我首先运行项目视频捕获工作时,当我关闭视频捕获修补程序窗口时,当我单击按钮时,它不起作用。我的代码错在哪里?我希望第一个 tkinter 窗口出现,当我点击按钮时,它开始视频捕获。我该怎么办?
from tkinter import *
from test import cap
root = Tk()
root.title('Emotion Detection')
root.iconbitmap(r'C:\Users\Doğukan\OneDrive\Masaüstü\ED\icon.ico')
root.geometry("500x300")
def run():
return cap
myButton = Button(root,text="calistir",command=run(),padx=50)
myButton.pack(pady=20)
root.mainloop()
test.py
from keras.models import load_model
from time import sleep
from keras.preprocessing.image import img_to_array
from keras.preprocessing import image
import cv2
import numpy as np
face_classifier = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')
classifier =load_model('./Emotion_Detection.h5')
class_labels = ['Sinirli','Mutlu','Dogal','Uzgun','Saskin','Korkmus']
cap = cv2.VideoCapture(0)
while True:
ret,frame = cap.read()
labels = []
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
faces = face_classifier.detectMultiScale(gray,1.3,5)
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_gray = cv2.resize(roi_gray,(48,48),interpolation=cv2.INTER_AREA)
if np.sum([roi_gray])!=0:
roi = roi_gray.astype('float')/255.0
roi = img_to_array(roi)
roi = np.expand_dims(roi,axis=0)
preds = classifier.predict(roi)[0]
print("\nprediction = ",preds)
label=class_labels[preds.argmax()]
print("\nprediction max = ",preds.argmax())
print("\nlabel = ",label)
label_position = (x,y)
cv2.putText(frame,label,label_position,cv2.FONT_HERShey_SIMPLEX,2,(255,255),3)
else:
cv2.putText(frame,'Yuz Bulunamadi',(20,60),3)
print("\n\n")
frame= cv2.resize(frame,(860,490))
cv2.imshow('Emotion Detector',frame)
if cv2.waitKey(1) & 0xFF == ord('q'): # çıkma tuşu
break
cap.release()
cv2.destroyAllWindows()
解决方法
将您的主脚本更改为:
from tkinter import *
from test import start_capturing
root = Tk()
root.title('Emotion Detection')
root.iconbitmap(r'C:\Users\Doğukan\OneDrive\Masaüstü\ED\icon.ico')
root.geometry("500x300")
def run():
root.destroy() # Destroy the root so it doesn't hang
start_capturing() # Start the function that is inside `test.py`
myButton = Button(root,text="calistir",command=run,padx=50)
myButton.pack(pady=20)
root.mainloop()
和您的 test.py
脚本:
from keras.models import load_model
from time import sleep
from keras.preprocessing.image import img_to_array
from keras.preprocessing import image
import cv2
import numpy as np
def start_capturing():
face_classifier = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')
classifier =load_model('./Emotion_Detection.h5')
class_labels = ['Sinirli','Mutlu','Dogal','Uzgun','Saskin','Korkmus']
cap = cv2.VideoCapture(0)
while True:
ret,frame = cap.read()
labels = []
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
faces = face_classifier.detectMultiScale(gray,1.3,5)
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_gray = cv2.resize(roi_gray,(48,48),interpolation=cv2.INTER_AREA)
if np.sum([roi_gray]) != 0:
roi = roi_gray.astype("float") / 255.0
roi = img_to_array(roi)
roi = np.expand_dims(roi,axis=0)
preds = classifier.predict(roi)[0]
print("\nprediction = ",preds)
label = class_labels[preds.argmax()]
print("\nprediction max = ",preds.argmax())
print("\nlabel = ",label)
label_position = (x,y)
cv2.putText(frame,label,label_position,cv2.FONT_HERSHEY_SIMPLEX,2,(255,255),3)
else:
cv2.putText(frame,'Yuz Bulunamadi',(20,60),3)
print("\n\n")
frame= cv2.resize(frame,(860,490))
cv2.imshow("Emotion Detector",frame)
if cv2.waitKey(1) and (0xFF == ord("q")): # çıkma tuşu
break
cap.release()
cv2.destroyAllWindows()
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