Tkinter Penceresi Çalışırken Arka planda Fonksiyon Çalıştırma

canerates · Ağustos 31, 2017, 8:19ös

Merhabalar, ufak bir sorum olacak tkinter penceresi açıkken arka planda fonksiyonun çalışmasını istiyorum aşağıda küçük bir deneme uygulaması yazdım. Programı çalıştırdığımda ilk başta kodu çalıştırıyor sonra pencereyi açıyor, arkada kod çalışırken tkinter penceresin gözükmesini nasıl yapabilirim?

from tkinter import *
import time

def deneme():
i = 0

while True:

    time.sleep(1)
    print("Deneme")
    i = i+1

    if i == 5:
        break
root = Tk()

deneme()
root.mainloop()

canerates · Ağustos 31, 2017, 8:50ös

Threading ile sorunu çözdüm

from tkinter import *
from threading import Thread
import time

def deneme():
i = 0

while True:

    time.sleep(1)
    print("Deneme")
    i = i+1

    if i == 5:
        break
def pencere():
root = Tk()

root.mainloop()
deneme_run = Thread(target=deneme)
pencere_run = Thread(target=pencere)

deneme_run.start()
pencere_run.start()

Sevgi_Gundogdu · Nisan 27, 2018, 10:10ös

Arkadaşlar Mac OS ta çalışıyorum yukarıdaki kodları çalıştırdığımda böyle bir hata verdi

dyld: loaded: /Users/sevgigundogdu/PycharmProjects/ProjectDeaf/venv/bin/python
dyld: loaded: /System/Library/Frameworks/Python.framework/Versions/2.7/Python
dyld: loaded: /usr/lib/libSystem.B.dylib
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dyld: loaded: /usr/lib/system/libcompiler_rt.dylib
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dyld: loaded: /usr/lib/system/libkeymgr.dylib
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dyld: loaded: /Users/sevgigundogdu/PycharmProjects/ProjectDeaf/venv/lib/python2.7/lib-dynload/_tkinter.so
dyld: loaded: /System/Library/Frameworks/Tcl.framework/Versions/8.5/Tcl
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dyld: loaded: /System/Library/Frameworks/ApplicationServices.framework/Versions/A/Frameworks/PrintCore.framework/Versions/A/PrintCore
dyld: loaded: /System/Library/Frameworks/ApplicationServices.framework/Versions/A/Frameworks/QD.framework/Versions/A/QD
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dyld: loaded: /System/Library/PrivateFrameworks/IOAccelerator.framework/Versions/A/IOAccelerator
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dyld: loaded: /System/Library/PrivateFrameworks/DSExternalDisplay.framework/Versions/A/DSExternalDisplay
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dyld: loaded: /System/Library/Frameworks/CoreVideo.framework/Versions/A/CoreVideo
dyld: loaded: /System/Library/PrivateFrameworks/GraphVisualizer.framework/Versions/A/GraphVisualizer
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Deneme
Deneme
Deneme
Deneme
Deneme

Process finished with exit code 0

Sebebini bilen yardımcı olursa çok sevinirim?

dildeolupbiten · Nisan 27, 2018, 10:33ös

Yanılmıyorsam python2.7 kullanıyorsunuz. Yukarıdaki kodlarda dikkatimi çeken şey; tkinter’in from tkinter import * şeklinde import edilmesi. Bu yazım python3 için geçerlidir. Siz tkinter’i from Tkinter import * yazarak import edin ve kodları tekrar çalıştırmayı bir deneyin, belki sorun bundan kaynaklanıyordur.

Sevgi_Gundogdu · Nisan 27, 2018, 10:42ös

Söylediğinizi denedim fakat sorun halen devam ediyor

dildeolupbiten · Nisan 27, 2018, 10:47ös

Daha önce hiç Mac OS kullanmadım, çıktıdan da bir şey anlamadım. Normalde yukarıdaki kodlar çalışır durumda.

Bu arada paylaştığınız hata çıktısında şöyle bir kısım var:
/Users/sevgigundogdu/PycharmProjects/ProjectDeaf/venv/bin/python Python’ı virtualenv ile mi kullanıyorsunuz?

Sevgi_Gundogdu · Nisan 27, 2018, 10:49ös

Evet Python’ı virtualenv ile kullanıyorum.

dildeolupbiten · Nisan 27, 2018, 10:52ös

Acaba ondan mı kaynaklanıyor diye düşündüm. Sonra tkinter’ı virtualenv’e yüklememiş olabileceğini düşündüm ama sonra tkinter’in Python’la beraber yüklenen bir uygulama olması sebebiyle bundan kaynaklanmıyor olabilir diye geçti aklımdan.

Bu arada IDLE and tkinter with Tcl/Tk on macOS | Python.org adresinden bir alıntı paylaşayım sizinle, belki yardımı dokunur.

Sevgi_Gundogdu · Nisan 27, 2018, 10:57ös

Aslında benim amacım tkinter penceresi ekranda çalışırken arka planda aynı zamanda bu kodları da çalıştırabilmek rica etsem nasıl yapabileceğim konusunda yardımcı olur musunuz?
Kod:

import cv2
import numpy as np
import util as ut
import svm_train as st
import re

model = st.trainSVM()
cap = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_SIMPLEX


def nothing(x):
    pass


text = " "

temp = 0
previouslabel = None
previousText = " "
label = None
while (cap.isOpened()):
    _, img = cap.read()
    cv2.rectangle(img, (900, 100), (1300, 500), (255, 0, 0),3)  # bounding box which captures ASL sign to be detected by the system
    img1 = img[100:500, 900:1300]
    img_ycrcb = cv2.cvtColor(img1, cv2.COLOR_BGR2YCR_CB)
    blur = cv2.GaussianBlur(img_ycrcb, (11, 11), 0)
    skin_ycrcb_min = np.array((0, 138, 67))
    skin_ycrcb_max = np.array((255, 173, 133))
    mask = cv2.inRange(blur, skin_ycrcb_min,skin_ycrcb_max)  # detecting the hand in the bounding box using skin detection
    _,contours, hierarchy = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, 2)
    cnt = ut.getMaxContour(contours, 4000)  # using contours to capture the skin filtered image of the hand
    #cnt!= None
    if cnt is not None:
        gesture,label = ut.getGestureImg(cnt, img1, mask,model)  # passing the trained model for prediction and fetching the result
        if label is not None:
            if (temp == 0):
                previouslabel = label
        if previouslabel == label:
            previouslabel = label
            temp += 1
        else:
            temp = 0
        if (temp == 60):
            text = text + label
            # text=previousText
            print (text)

        cv2.imshow('PredictedGesture', gesture)  # showing the best match or prediction
        cv2.putText(img, label, (50, 150), font, 8, (0, 125, 155),
                     2)  # displaying the predicted letter on the main screen
        cv2.putText(img, text, (50, 450), font, 3, (0, 0, 255), 2)

    cv2.imshow('Frame', img)
    cv2.imshow('Mask', mask)
    k = 0xFF & cv2.waitKey(10)
    if k == 27:
        break

cap.release()
cv2.destroyAllWindows()

dildeolupbiten · Nisan 27, 2018, 10:59ös

Kodlarınızı aşağıdaki ifadelerin arasına alırsanız, kod görünümü kazanabilirler.

[code]

[/code]

Sevgi_Gundogdu · Nisan 27, 2018, 11:02ös

Üstte Düzenledim inceleyebilirsiniz.

dildeolupbiten · Nisan 27, 2018, 11:16ös

Üstteki kodlarda util’i import edemiyorum, böyle bir modül yok uyarısı alıyorum. Sanırım benden önce bir kaç kişi daha benzer bir sorunla karşılaşmış. Ayrıca svm_train’i nerden edinebilirim?

Sevgi_Gundogdu · Nisan 27, 2018, 11:19ös

util.py

import cv2
import svm_train as st

def getMaxContour(contours, minArea=200):
    maxC = None
    maxArea = minArea
    for cnt in contours:
        area = cv2.contourArea(cnt)
        if (area > maxArea):
            maxArea = area
            maxC = cnt
    return maxC



def getGestureImg(cnt, img, th1, model):
    x, y, w, h = cv2.boundingRect(cnt)
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
    imgT = img[y:y + h, x:x + w]
    imgT = cv2.bitwise_and(imgT, imgT, mask=th1[y:y + h, x:x + w])
    imgT = cv2.resize(imgT, (200, 200))
    imgTG = cv2.cvtColor(imgT, cv2.COLOR_BGR2GRAY)
    resp = st.predict(model, imgTG)
    img = cv2.imread('DataSet/' + unichr(int(resp[0]) + 64) + '_2.jpg')
    return img, unichr(int(resp[0]) + 64)

Sevgi_Gundogdu · Nisan 27, 2018, 11:22ös

sim_train kendim yazdım.

svm_train:

# coding=utf-8_

import cv2
import numpy as np
from numpy.linalg import norm


svm_params = dict(kernel_type=cv2.ml.SVM_RBF, svm_type=cv2.ml.SVM_C_SVC,C=2.67, gamma=5.383)

class StatModel(object):
    def load(self, fn):
        self.model.load(fn)  # python rapper bug

    def save(self, fn):
        self.model.save(fn)


class SVM(StatModel):
    def __init__(self, C=1, gamma=0.5):
        #self.model = cv2.SVM()
        self.model = cv2.ml.SVM_create()
        self.model.setGamma(gamma)
        self.model.setC(C)
        self.model.setKernel(cv2.ml.SVM_RBF)
        self.model.setType(cv2.ml.SVM_C_SVC)

    def train(self, samples, responses):
        #self.model.train(samples, responses,params=svm_params)  # inbuilt training function
        self.model.setType(cv2.ml.SVM_C_SVC)
        self.model.setC(1)
        self.model.setKernel(cv2.ml.SVM_RBF)
        self.model.setGamma(.1)
        self.model.train(samples, cv2.ml.ROW_SAMPLE, responses.astype(int))

    def predict(self, samples):
        #return self.model.predict_all(samples).ravel()
        _ret, resp = self.model.predict(samples)
        return resp.ravel()


def preprocess_hog(digits):
    samples = []
    for img in digits:
        gx = cv2.Sobel(img, cv2.CV_32F,1,0)   #Resmin X ekseninine gore kenarliklarini belirtir.
        gy = cv2.Sobel(img, cv2.CV_32F,0,1) #Resmin Y ekseninine gore kenarliklarini belirtir.
        mag, ang = cv2.cartToPolar(gx, gy)    #2D vektörlerin büyüklüğünü ve açısını hesaplar.
        bin_n = 16
        bin = np.int32(bin_n * ang / (2 * np.pi))
        bin_cells = bin[:100, :100], bin[100:, :100], bin[:100, 100:], bin[100:, 100:]
        mag_cells = mag[:100, :100], mag[100:, :100], mag[:100, 100:], mag[100:, 100:]
        hists = [np.bincount(b.ravel(), m.ravel(), bin_n) for b, m in zip(bin_cells, mag_cells)]
        hist = np.hstack(hists)

        # transform to Hellinger kernel
        eps = 1e-7
        hist /= hist.sum() + eps
        hist = np.sqrt(hist)
        hist /= norm(hist) + eps

        samples.append(hist)
    return np.float32(samples)

# Here goes my wrappers:_
def hog_single(img):
    samples = []
    gx = cv2.Sobel(img, cv2.CV_32F, 1, 0)
    gy = cv2.Sobel(img, cv2.CV_32F, 0, 1)
    mag, ang = cv2.cartToPolar(gx, gy)
    bin_n = 16
    bin = np.int32(bin_n * ang / (2 * np.pi))
    bin_cells = bin[:100, :100], bin[100:, :100], bin[:100, 100:], bin[100:, 100:]
    mag_cells = mag[:100, :100], mag[100:, :100], mag[:100, 100:], mag[100:, 100:]
    hists = [np.bincount(b.ravel(), m.ravel(), bin_n) for b, m in zip(bin_cells, mag_cells)]
    hist = np.hstack(hists)

    # transform to Hellinger kernel
    eps = 1e-7
    hist /= hist.sum() + eps
    hist = np.sqrt(hist)
    hist /= norm(hist) + eps

    samples.append(hist)
    return np.float32(samples)


def trainSVM():
    imgs = []
    num=17
    for i in range(65, num + 65):

        for j in range(1, 401):
            print(
            'Class ' + chr(i) + ' is being loaded ')
            imgs.append(cv2.imread('DataSet/' + chr(i) + '_' + str(j) + '.jpg', 0))  # all images saved in a list
    labels = np.repeat(np.arange(1, num + 1), 400)  # label for each corresponding image saved above
    samples = preprocess_hog(imgs)  # images sent for pre processeing using hog which returns features for the images
    print("SVM is building wait some time ...")
    print (len(labels))
    print (len(samples))
    model=SVM(C=2.67, gamma=5.383)
    model.train(samples, labels)  # features trained against the labels using svm
    return model


def predict(model, img):
    samples = hog_single(img)
    resp = model.predict(samples)
    return resp

Sevgi_Gundogdu · Nisan 27, 2018, 11:26ös

aynı zamanda projemde 6800 adet harflerin tanımlı olduğu dataset mevcut

dildeolupbiten · Nisan 27, 2018, 11:34ös

Import sorunu çözüldü ancak herhalde bu dataset bende olmadan ilk paylaştığınız kodlar istenildiği gibi çalışmaz.

dildeolupbiten · Nisan 27, 2018, 11:42ös

Bu arada siz ilk mesajınızda yukarıdaki kodları çalıştırırken sorun yaşadığınızı söylemiştiniz. Yani siz tkinter’i arkadaşın yazdığı kodlarla çalıştırabiliyor musunuz yoksa sonradan verdiğiniz bu programlarla threading’i birleştirerek kullanmaya çalıştınız da o yüzden mi hata verdi?