Question

我试图将GUI（tkinter）添加到我的脚本中，但无济于事。如果有人能帮助我，我会非常感激。我使用的是Python 3.6，我认为最新的opencv？

我2周前才开始编程。所以，有点新的一切。基本上，我想创建一个窗口，只从我的文件夹中选择图像，然后通过脚本处理它，这样每当我想使用另一个图像时，我都不必更改脚本。我希望有意义..

这是我从youtube上从Chris Dahms那里获取的脚本，并设法将其更改为我想要的内容。

import cv2
import numpy as np
import os

import DetectChars
import DetectPlates
import PossiblePlate 

SCALAR_BLACK = (0.0, 0.0, 0.0)
SCALAR_WHITE = (255.0, 255.0, 255.0)
SCALAR_YELLOW = (0.0, 255.0, 255.0)
SCALAR_GREEN = (0.0, 255.0, 0.0)
SCALAR_CYAN = (255.0, 255.0, 0.0)

showSteps = False

def main():

blnKNNTrainingSuccessful = DetectChars.loadKNNDataAndTrainKNN()         

if blnKNNTrainingSuccessful == False:                               
    print ("\nerror: KNN training was not successful\n")    
    return                                                          

imgOriginalScene = cv2.imread("CAR/Malaysia/22.jpg")

if imgOriginalScene is None:
    print ("\nerror: image not read from file \n\n")
    os.system("pause")
    return 

if imgOriginalScene is None:                            
    print ("\nerror: image not read from file \n\n")    
    os.system("pause")                                  
    return

listOfPossiblePlates = DetectPlates.detectPlatesInScene(imgOriginalScene)           

listOfPossiblePlates = DetectChars.detectCharsInPlates(listOfPossiblePlates)        

cv2.imshow("imgOriginalScene", imgOriginalScene)            

if len(listOfPossiblePlates) == 0:                         
    print ("\nno license plates were detected\n")            
else:                                                   



    listOfPossiblePlates.sort(key = lambda possiblePlate: len(possiblePlate.strChars), reverse = True)


    licPlate = listOfPossiblePlates[0]

    cv2.imshow("Image Plate", licPlate.imgPlate)           
    cv2.imshow("Image Threshold", licPlate.imgThresh)

    if len(licPlate.strChars) == 0:                    
        print ("\nno characters were detected\n\n")      
        return                                       


     drawRedRectangleAroundPlate(imgOriginalScene, licPlate)           

    print ("\nlicense plate read from image = " + licPlate.strChars + "\n")      
    print ("----------------------------------------")

    writeLicensePlateCharsOnImage(imgOriginalScene, licPlate)     

    cv2.imshow("imgOriginalScene", imgOriginalScene)               

    cv2.imwrite("imgOriginalScene.png", imgOriginalScene)          



cv2.waitKey(0)              

return

def drawRedRectangleAroundPlate(imgOriginalScene, licPlate):

p2fRectPoints = cv2.boxPoints(licPlate.rrLocationOfPlateInScene)         

cv2.line(imgOriginalScene, tuple(p2fRectPoints[0]), tuple(p2fRectPoints[1]), SCALAR_RED, 2)       
cv2.line(imgOriginalScene, tuple(p2fRectPoints[1]), tuple(p2fRectPoints[2]), SCALAR_RED, 2)
cv2.line(imgOriginalScene, tuple(p2fRectPoints[2]), tuple(p2fRectPoints[3]), SCALAR_RED, 2)
cv2.line(imgOriginalScene, tuple(p2fRectPoints[3]), tuple(p2fRectPoints[0]), SCALAR_RED, 2)


def writeLicensePlateCharsOnImage(imgOriginalScene, licPlate):
ptCenterOfTextAreaX = 0                          
ptCenterOfTextAreaY = 0

ptLowerLeftTextOriginX = 0                         
ptLowerLeftTextOriginY = 0

sceneHeight, sceneWidth, sceneNumChannels = imgOriginalScene.shape
plateHeight, plateWidth, plateNumChannels = licPlate.imgPlate.shape

intFontFace = cv2.FONT_HERSHEY_SIMPLEX                  
fltFontScale = float(plateHeight) / 30.0                    
intFontThickness = int(round(fltFontScale * 2))        

textSize, baseline = cv2.getTextSize(licPlate.strChars, intFontFace, fltFontScale, intFontThickness)      


( (intPlateCenterX, intPlateCenterY), (intPlateWidth, intPlateHeight), fltCorrectionAngleInDeg ) = licPlate.rrLocationOfPlateInScene

intPlateCenterX = int(intPlateCenterX)          
intPlateCenterY = int(intPlateCenterY)

ptCenterOfTextAreaX = int(intPlateCenterX)         

if intPlateCenterY < (sceneHeight * 0.75):                                               
    ptCenterOfTextAreaY = int(round(intPlateCenterY)) + int(round(plateHeight * 1.6))   
else:                                                                                
    ptCenterOfTextAreaY = int(round(intPlateCenterY)) - int(round(plateHeight * 1.6))    


textSizeWidth, textSizeHeight = textSize               

ptLowerLeftTextOriginX = int(ptCenterOfTextAreaX - (textSizeWidth / 2))         
ptLowerLeftTextOriginY = int(ptCenterOfTextAreaY + (textSizeHeight / 2))         


cv2.putText(imgOriginalScene, licPlate.strChars, (ptLowerLeftTextOriginX, ptLowerLeftTextOriginY), intFontFace, fltFontScale, SCALAR_CYAN, intFontThickness)



if __name__ == "__main__":
main()

cv2.waitKey()
cv2.destroyAllWindows()

预处理阶段

# Preprocess.py

import numpy as np
import math

# module level variables ##########################################################################
GAUSSIAN_SMOOTH_FILTER_SIZE = (5, 5)
ADAPTIVE_THRESH_BLOCK_SIZE = 19
ADAPTIVE_THRESH_WEIGHT = 9


def preprocess(imgOriginal):
imgGrayscale = extractValue(imgOriginal)

imgMaxContrastGrayscale = maximizeContrast(imgGrayscale)

height, width = imgGrayscale.shape

grayscaled = cv2.cvtColor(imgOriginal,cv2.COLOR_BGR2GRAY)

imgBlurred = np.zeros((height, width, 1), np.uint8)

imgBlurred, otsu = cv2.threshold(grayscaled,125,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)

imgThresh = cv2.medianBlur(otsu,5)

return imgGrayscale, imgThresh
# end function


def extractValue(imgOriginal):
height, width, numChannels = imgOriginal.shape

imgHSV = np.zeros((height, width, 3), np.uint8)

imgHSV = cv2.cvtColor(imgOriginal, cv2.COLOR_BGR2HSV)

imgHue, imgSaturation, imgValue = cv2.split(imgHSV)

return imgValue
# end function

def maximizeContrast(imgGrayscale):

height, width = imgGrayscale.shape

imgTopHat = np.zeros((height, width, 1), np.uint8)
imgBlackHat = np.zeros((height, width, 1), np.uint8)

structuringElement = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))

imgTopHat = cv2.morphologyEx(imgGrayscale, cv2.MORPH_TOPHAT, structuringElement)
imgBlackHat = cv2.morphologyEx(imgGrayscale, cv2.MORPH_BLACKHAT, structuringElement)

imgGrayscalePlusTopHat = cv2.add(imgGrayscale, imgTopHat)
imgGrayscalePlusTopHatMinusBlackHat = cv2.subtract(imgGrayscalePlusTopHat, imgBlackHat)

return imgGrayscalePlusTopHatMinusBlackHat
# end function

Answer 1

我推荐使用Gtk3作为GUI。这是一个带按钮的简单Gtk窗口：

#!/usr/bin/env python3

import gi
gi.require_version( 'Gtk', '3.0' )
from gi.repository import Gtk

class Window( Gtk.Window ):
    def __init__( self ):
        Gtk.Window.__init__( self )
        self.connect( 'destroy', lambda q: Gtk.main_quit() )

        button = Gtk.Button( "Gtk.Button" )
        button.connect( "clicked", self.on_button_clicked )

        grid = Gtk.Grid( )
        grid.attach( button, 0, 0, 1, 1 )

        self.add( grid )
        self.show_all()

    def on_button_clicked( self, button ):
        print( "Gtk.Button was clicked" )

w = Window()
Gtk.main()

Answer 2

如果你想要的只是一个选择文件的窗口，那么这应该可行。

import Tkinter
from Tkinter import *
import tkSimpleDialog
from tkFileDialog import askopenfilename

master = Tk()
master.withdraw()
my_file = askopenfilename()
mainloop()

将GUI添加到python脚本中

2 个答案: