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App.py
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import sys
import cv2
import numpy as np
import os
import subprocess
from os import path
from collections import Counter
from collections import deque
import keras
import time
import threading
from PyQt5.QtWidgets import QApplication,QDesktopWidget, QWidget,QLabel,QTableWidget,QTableWidgetItem, QPushButton,QFileDialog, QHBoxLayout, QGroupBox, QDialog, QVBoxLayout, QGridLayout
from matplotlib.backends.qt_compat import QtCore, QtGui, QtWidgets
from matplotlib.backends.backend_qt5agg import FigureCanvas
from matplotlib.figure import Figure
from keras.models import model_from_json
from sklearn.preprocessing import LabelEncoder
import imutils
from PyQt5.QtCore import *
from PyQt5.QtGui import *
class Model():
def resource_path(self):
""" Get absolute path to resource, works for dev and for PyInstaller """
try:
# PyInstaller creates a temp folder and stores path in _MEIPASS
base_path = sys._MEIPASS
except Exception:
base_path = os.path.abspath(".")
return base_path
def __init__(self):
print('Creating model...')
self.modelJson = 'Model_loss_ES_40Ep.json'
self.modelH5 = 'Model_loss_ES_40Ep.h5'
pfrClassesPath = 'pfrClasses.npy'
ftClassesPath = 'ftClasses.npy'
pfrClassesPath = os.path.join(self.resource_path(),pfrClassesPath)
ftClassesPath = os.path.join(self.resource_path(),ftClassesPath)
self.pfrEncoder = LabelEncoder()
self.pfrEncoder.classes_ = np.load(pfrClassesPath,allow_pickle=True)
self.ftEncoder = LabelEncoder()
self.ftEncoder.classes_ = np.load(ftClassesPath,allow_pickle=True)
print('Loading Model')
self.model = self.loadModel()
print('Creating model...Done')
def labelDecoder(self,label,cls):
encoder = None
if cls == 'PFR':
encoder = self.pfrEncoder
elif cls == 'FT':
encoder = self.ftEncoder
trueLab = encoder.inverse_transform(label)
return(trueLab)
def loadModel(self):
modelJsonPath = self.modelJson
modelH5Path = self.modelH5
modelJsonPath = os.path.join(self.resource_path(),modelJsonPath)
modelH5Path = os.path.join(self.resource_path(),modelH5Path)
print(modelJsonPath+'##################'+modelH5Path)
with open(modelJsonPath, 'r') as f:
model = model_from_json(f.read())
model.load_weights(modelH5Path)
return model
def classify(self,image):
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image = cv2.resize(image, (224, 224))
image = image.astype("float32")/255
#mean = np.array([123.68, 116.779, 103.939][::-1], dtype="float32")
#image -= mean
# pass the image through the network to obtain our prediction
pfr,ft = self.model.predict(np.expand_dims(image, axis=0))
pfr,ft = pfr.argmax(axis=-1), ft.argmax(axis=-1)
truePFR,trueFT = self.labelDecoder(pfr,'PFR'),self.labelDecoder(ft,'FT')
return truePFR,trueFT
class Thread(QThread):
infLabel = pyqtSignal(str)
changePixmap = pyqtSignal(QImage)
trgLabel = pyqtSignal(str)
def __init__(self,appData):
QThread.__init__(self,appData)
print('Thread init')
if appData.model == None:
self.model = Model()
else:
self.model = appData.model
self.file = appData.file
self.rollAveragePFR = deque([])
self.rollAverageFT = deque([])
print('Thread init Done')
def rollAverage(self,pfr,ft):
#handle pfr rolling average
if len(self.rollAveragePFR) == 10:
self.rollAveragePFR.rotate(-1)
self.rollAveragePFR.pop()
self.rollAveragePFR.append(pfr[0])
else:
self.rollAveragePFR.append(pfr[0])
if len(self.rollAverageFT) == 10:
self.rollAverageFT.rotate(-1)
self.rollAverageFT.pop()
self.rollAverageFT.append(ft[0])
else:
self.rollAverageFT.append(ft[0])
pfrVals = list(Counter(self.rollAveragePFR).keys())
pfrValsCounts = list(Counter(self.rollAveragePFR).values())
maxInd = np.argmax(pfrValsCounts)
pfr = pfrVals[maxInd]
ftVals = list(Counter(self.rollAverageFT).keys())
ftValsCounts = list(Counter(self.rollAverageFT).values())
maxInd = np.argmax(ftValsCounts)
ft = ftVals[maxInd]
return pfr,ft
def run(self):
print('running thread')
self.infLabel.emit('Video loaded. Analyzing...')
vidcap = cv2.VideoCapture(self.file)
success,image = vidcap.read()
while success:
output = image.copy()
output = imutils.resize(output, width=400)
truePFR,trueFT = self.model.classify(image)
print(truePFR,trueFT)
truePFR,trueFT = self.rollAverage(truePFR,trueFT)
pfrtext = "PFR : {pfr}".format(pfr =truePFR)
fttext = "Fuel Type : {ft}".format(ft=trueFT)
cv2.putText(output, pfrtext, (3, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(0, 255, 0), 2)
cv2.putText(output, fttext, (3, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(0, 255, 0), 2)
#h, w, ch = output.shape
#bytesPerLine = ch * w
#p = QImage(image, w, h, bytesPerLine, QImage.Format_RGB888)
output = QtGui.QImage(output.data, output.shape[1], output.shape[0], QtGui.QImage.Format_RGB888).rgbSwapped()
#p = convertToQtFormat.scaled(640, 480, Qt.KeepAspectRatio)
self.changePixmap.emit(output)
self.trgLabel.emit(pfrtext+'\n'+fttext)
self.infLabel.emit('Running pedictions on each frame ...')
success,image = vidcap.read()
print('Done')
self.infLabel.emit('Finished! Click "Load File" to analyze again.')
class ThreadImage(QThread):
changePixmapImage = pyqtSignal(QImage)
infLabel = pyqtSignal(str)
trgLabel = pyqtSignal(str)
def __init__(self,appData):
self.file = appData.file
QThread.__init__(self,appData)
print('Thread Image init')
if appData.model == None:
self.model = Model()
else:
self.model = appData.model
self.file = appData.file
print('Thread init Done')
def run(self):
print('running thread Image')
print('Analyzing data..')
self.infLabel.emit('Image loaded. Analyzing...')
try:
img = cv2.imread(self.file)
output = img.copy()
output = imutils.resize(output, width=400)
except Exception as e:
print('Error in reading Image: ',e)
truePFR,trueFT = self.model.classify(img)
# Image write
pfrtext = "PFR : {pfr}".format(pfr =truePFR)
fttext = "Fuel Type : {ft}".format(ft=trueFT)
cv2.putText(output, pfrtext, (3, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(0, 255, 0), 2)
cv2.putText(output, fttext, (3, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(0, 255, 0), 2)
output = QtGui.QImage(output.data, output.shape[1],output.shape[0], QtGui.QImage.Format_RGB888).rgbSwapped()
self.trgLabel.emit(pfrtext+'\n'+fttext)
self.changePixmapImage.emit(output)
self.infLabel.emit('Finished! Click "Load File" to analyze again.')
class App(QWidget):
def resource_path(self,relative_path):
""" Get absolute path to resource, works for dev and for PyInstaller """
try:
# PyInstaller creates a temp folder and stores path in _MEIPASS
base_path = sys._MEIPASS
except Exception:
base_path = os.path.abspath(".")
return os.path.join(base_path, relative_path)
def __init__(self):
super().__init__()
self.title = 'Flame Characterization - Siemens Turbomachinery AB'
self.left = 10
self.top = 10
self.width = 320
self.height = 100
self.model = None
self.output = None
self.file = None
self.initUI()
@pyqtSlot(QImage)
def setImage(self, image):
self.label.setPixmap(QPixmap.fromImage(image))
@pyqtSlot(str)
def setLabel(self, text):
self.infoLabel.setText(text)
@pyqtSlot(str)
def setTargetLabel(self, text):
self.targetLabel.setText(text)
def fileExists(self,file):
if os.path.exists(file):
return True
else:
return False
def initUI(self):
self.setWindowTitle(self.title)
self.setFixedSize(900,800)
self.setGeometry(self.left, self.top, self.width, self.height)
self.window()
app = QApplication(sys.argv)
win = QWidget()
win.setFixedSize(900,800)
self.toolLabel = QLabel()
self.infoLabel = QLabel()
self.label = QLabel()
self.contactLabel = QtWidgets.QPushButton('Contact', self)
self.contactLabel.setFixedSize(100,20)
self.toolLabel.setText("Flame Characterization Tool")
self.toolLabel.setStyleSheet('font-size:40px')
self.contactLabel.setText("Contact")
self.infoLabel.setText('No file loaded! Please click "Load File" to load file')
self.infoLabel.setStyleSheet('color:red;font-size:20px')
self.targetLabel = QLabel()
self.targetLabel.setText('')
self.targetLabel.setStyleSheet('color:blue;font-size:15px')
self.browseBtn = QtWidgets.QPushButton('Load File', self)
self.browseBtn.setMaximumWidth(100)
self.browseBtn.clicked.connect(self.getfiles)
self.toolLabel.setAlignment(Qt.AlignCenter)
self.infoLabel.setAlignment(Qt.AlignLeft)
self.label.setAlignment(Qt.AlignCenter)
imPath= 'Siemens.jpg'
imPath = self.resource_path(imPath)
print('logo: ',imPath)
pixmap = QPixmap(imPath)
self.label.setPixmap(pixmap)
self.label.setFixedSize(480,480)
self.contactLabel.clicked.connect(self.cWindow)
vbox = QVBoxLayout()
vbox.addWidget(self.toolLabel)
vbox.addStretch()
vbox.addWidget(self.infoLabel)
vbox.addStretch()
vbox.addWidget(self.browseBtn)
vbox.addStretch()
vbox.addWidget(self.targetLabel)
vbox.addStretch()
vbox.addWidget(self.label)
vbox.addStretch()
vbox.addWidget(self.contactLabel,alignment=Qt.AlignRight)
win.setLayout(vbox)
win.setWindowTitle("FC Demo")
win.show()
sys.exit(app.exec_())
def cWindow(self):
self.contactInf = QLabel('Info',self)
self.contactInf.setText('This tool is developed as a part of Master\'s Thesis titled as "Multi Task Convolutional Learning for flame characterization", \ndevloped by: Obaid Ur Rehman')
self.clabel = QLabel("Contact", self)
self.clabel.setText('Contact:\nName:Obaid Ur Rehman\nEmail:[email protected]\nPhone:+46761593548\nLinkedIn:https://www.linkedin.com/in/obaidurrehman1994')
self.clabel.move(0,50)
self.setWindowTitle(self.title)
self.setFixedSize(700,150)
self.setGeometry(self.top, self.left, self.width, self.height)
centerPoint = QDesktopWidget().availableGeometry().center()
self.move(centerPoint)
self.show()
def getfiles(self):
dlg = QFileDialog()
dlg.setFileMode(QFileDialog.AnyFile)
dlg.setNameFilters(["Images (*.jpeg *.png *.jpg)","Videos (*.mp4 *.avi)"])
filenames = []
if dlg.exec_():
filenames = dlg.selectedFiles()
file = filenames[0]
if self.fileExists(file):
if '.jpg' in file or '.jpeg' in file or '.png' in file:
print('Image file found: ',file)
try:
pixmap = QPixmap(file)
self.label.setPixmap(pixmap)
self.label.resize(480, 480)
self.file = file
th = ThreadImage(self)
th.infLabel.connect(self.setLabel)
th.trgLabel.connect(self.setTargetLabel)
th.changePixmapImage.connect(self.setImage)
th.start()
#self.show()
print('th killed')
except Exception as e:
print(e)
else:
self.file = file
self.infoLabel.setText('Video Loaded. Please wait, analyzing...')
th = Thread(self)
th.infLabel.connect(self.setLabel)
th.trgLabel.connect(self.setTargetLabel)
th.changePixmap.connect(self.setImage)
th.start()
print('th killed')
self.infoLabel.setText('Finished!')
else:
pass
def analyse(self):
print('Analyzing data..')
try:
img = cv2.imread(self.file)
self.output = img.copy()
self.output = imutils.resize(self.output, width=400)
except Exception as e:
print('Error in reading Image: ',e)
truePFR,trueFT = self.model.classify(img)
# Image write
pfrtext = "PFR : {pfr}".format(pfr =truePFR)
fttext = "Fuel Type : {ft}".format(ft=trueFT)
cv2.putText(self.output, pfrtext, (3, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(0, 255, 0), 2)
cv2.putText(self.output, fttext, (3, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(0, 255, 0), 2)
self.output = QtGui.QImage(self.output.data, self.output.shape[1], self.output.shape[0], QtGui.QImage.Format_RGB888).rgbSwapped()
self.label.setPixmap(QtGui.QPixmap.fromImage(self.output))
if __name__ == '__main__':
app = QApplication(sys.argv)
ex = App()
sys.exit(app.exec_())