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conceptual_learning_of_colors.py
664 lines (558 loc) · 27.9 KB
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conceptual_learning_of_colors.py
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#----------- Cognitive Vision Principle for Conceptual Learning of Colors ------------#
#------------------------------- Author: Jagadeesh Hariharan -------------------------#
#------------------------------- Date Modified: June 01,2017 -------------------------#
#----importing required packages--------#
import pandas as pd
from sklearn.cluster import KMeans
import sys
import cv2
import numpy as np
from PyQt4 import QtCore, QtGui
from PyQt4.QtGui import *
#----- Initiating try-catch blocks-----------------#
try:
_fromUtf8 = QtCore.QString.fromUtf8
except AttributeError:
def _fromUtf8(s):
return s
try:
_encoding = QtGui.QApplication.UnicodeUTF8
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig, _encoding)
except AttributeError:
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig)
class EmittingStream(QtCore.QObject):
textWritten = QtCore.pyqtSignal(str)
def write(self, text):
self.textWritten.emit(str(text))
#---- Learning of Colors Class--------#
class Ui_MainWindow(object):
def __init__(self):
super(Ui_MainWindow, self).__init__()
# self.setupUi(self)
# ---- Design Elements for GUI--------#
def setupUi(self, MainWindow):
MainWindow.setObjectName(_fromUtf8("MainWindow"))
MainWindow.resize(599, 477)
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
MainWindow.setFont(font)
# ---- Importing the logo for the GUI--------#
MainWindow.setWindowIcon(QtGui.QIcon('/home/jagadeesh/Desktop/py/PycharmProjects/QT/cw.png'))
self.centralwidget = QtGui.QWidget(MainWindow)
self.centralwidget.setObjectName(_fromUtf8("centralwidget"))
self.tabWidget = QtGui.QTabWidget(self.centralwidget)
self.tabWidget.setGeometry(QtCore.QRect(0, 0, 601, 271))
self.tabWidget.setObjectName(_fromUtf8("tabWidget"))
self.learn = QtGui.QWidget()
self.learn.setEnabled(True)
self.learn.setObjectName(_fromUtf8("learn"))
self.label_6 = QtGui.QLabel(self.learn)
self.label_6.setGeometry(QtCore.QRect(10, 80, 301, 17))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.label_6.setFont(font)
self.label_6.setObjectName(_fromUtf8("label_6"))
self.label = QtGui.QLabel(self.learn)
self.label.setGeometry(QtCore.QRect(10, 110, 21, 17))
self.label.setObjectName(_fromUtf8("label"))
self.Rinput = QtGui.QTextEdit(self.learn)
self.Rinput.setGeometry(QtCore.QRect(30, 100, 50, 30))
self.Rinput.setObjectName(_fromUtf8("Rinput"))
self.label_2 = QtGui.QLabel(self.learn)
self.label_2.setGeometry(QtCore.QRect(90, 110, 21, 17))
self.label_2.setObjectName(_fromUtf8("label_2"))
self.Ginput = QtGui.QTextEdit(self.learn)
self.Ginput.setGeometry(QtCore.QRect(110, 100, 50, 30))
self.Ginput.setObjectName(_fromUtf8("Ginput"))
self.label_3 = QtGui.QLabel(self.learn)
self.label_3.setGeometry(QtCore.QRect(170, 110, 21, 17))
self.label_3.setObjectName(_fromUtf8("label_3"))
self.Binput = QtGui.QTextEdit(self.learn)
self.Binput.setGeometry(QtCore.QRect(190, 100, 50, 30))
self.Binput.setObjectName(_fromUtf8("Binput"))
self.enterrgb = QtGui.QPushButton(self.learn)
self.enterrgb.setGeometry(QtCore.QRect(245, 100, 120, 30))
self.enterrgb.setObjectName(_fromUtf8("enterrgb"))
#QtCore.QObject.connect(self.enterrgb, QtCore.SIGNAL("clicked()"), self.inputrgb)
self.enterrgb.clicked.connect(self.inputrgb)
self.line_10 = QtGui.QFrame(self.learn)
self.line_10.setGeometry(QtCore.QRect(0, 60, 371, 20))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.line_10.setFont(font)
self.line_10.setFrameShadow(QtGui.QFrame.Raised)
self.line_10.setLineWidth(2)
self.line_10.setFrameShape(QtGui.QFrame.HLine)
self.line_10.setFrameShadow(QtGui.QFrame.Sunken)
self.line_10.setObjectName(_fromUtf8("line_10"))
self.learnload = QtGui.QPushButton(self.learn)
self.learnload.setGeometry(QtCore.QRect(10, 160, 101, 27))
self.learnload.setObjectName(_fromUtf8("learnload"))
self.learnload.clicked.connect(self.file_open1)
self.label_5 = QtGui.QLabel(self.learn)
self.label_5.setGeometry(QtCore.QRect(10, 10, 141, 17))
self.label_5.setObjectName(_fromUtf8("label_5"))
self.learnbutton = QtGui.QPushButton(self.learn)
self.learnbutton.setGeometry(QtCore.QRect(100, 200, 141, 27))
self.learnbutton.setObjectName(_fromUtf8("learnbutton"))
self.line_9 = QtGui.QFrame(self.learn)
self.line_9.setGeometry(QtCore.QRect(0, 140, 371, 20))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.line_9.setFont(font)
self.line_9.setFrameShadow(QtGui.QFrame.Raised)
self.line_9.setLineWidth(2)
self.line_9.setFrameShape(QtGui.QFrame.HLine)
self.line_9.setFrameShadow(QtGui.QFrame.Sunken)
self.line_9.setObjectName(_fromUtf8("line_9"))
self.line = QtGui.QFrame(self.learn)
self.line.setGeometry(QtCore.QRect(360, 0, 20, 241))
self.line.setFrameShape(QtGui.QFrame.VLine)
self.line.setFrameShadow(QtGui.QFrame.Sunken)
self.line.setObjectName(_fromUtf8("line"))
self.learncolorinput = QtGui.QTextEdit(self.learn)
self.learncolorinput.setGeometry(QtCore.QRect(10, 30, 161, 31))
self.learncolorinput.setObjectName(_fromUtf8("learncolorinput"))
global color_entered
self.line_12 = QtGui.QFrame(self.learn)
self.line_12.setGeometry(QtCore.QRect(0, 230, 641, 20))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.line_12.setFont(font)
self.line_12.setFrameShadow(QtGui.QFrame.Raised)
self.line_12.setLineWidth(2)
self.line_12.setFrameShape(QtGui.QFrame.HLine)
self.line_12.setFrameShadow(QtGui.QFrame.Sunken)
self.line_12.setObjectName(_fromUtf8("line_12"))
self.learnimg = QtGui.QLabel(self.learn)
self.learnimg.setGeometry(QtCore.QRect(380, 40, 171, 181))
self.learnimg.setText(_fromUtf8(""))
self.learnimg.setObjectName(_fromUtf8("learnimg"))
self.txtlbl2_3 = QtGui.QLabel(self.learn)
self.txtlbl2_3.setGeometry(QtCore.QRect(380, 10, 121, 20))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.txtlbl2_3.setFont(font)
self.txtlbl2_3.setObjectName(_fromUtf8("txtlbl2_3"))
self.Binputfromimage = QtGui.QTextEdit(self.learn)
self.Binputfromimage.setGeometry(QtCore.QRect(280, 160, 45, 31))
self.Binputfromimage.setObjectName(_fromUtf8("Binputfromimage"))
self.Ginputfromimage = QtGui.QTextEdit(self.learn)
self.Ginputfromimage.setGeometry(QtCore.QRect(210, 160, 45, 31))
self.Ginputfromimage.setObjectName(_fromUtf8("Ginputfromimage"))
self.label_11 = QtGui.QLabel(self.learn)
self.label_11.setGeometry(QtCore.QRect(120, 170, 21, 17))
self.label_11.setObjectName(_fromUtf8("label_11"))
self.Rinputfromimage = QtGui.QTextEdit(self.learn)
self.Rinputfromimage.setGeometry(QtCore.QRect(140, 160, 45, 31))
self.Rinputfromimage.setObjectName(_fromUtf8("Rinputfromimage"))
self.label_12 = QtGui.QLabel(self.learn)
self.label_12.setGeometry(QtCore.QRect(190, 170, 21, 17))
self.label_12.setObjectName(_fromUtf8("label_12"))
self.label_13 = QtGui.QLabel(self.learn)
self.label_13.setGeometry(QtCore.QRect(260, 170, 21, 17))
self.label_13.setObjectName(_fromUtf8("label_13"))
icon1 = QtGui.QIcon()
icon1.addPixmap(QtGui.QPixmap(_fromUtf8("ll.png")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
self.tabWidget.addTab(self.learn, icon1, _fromUtf8(""))
self.rr = QtGui.QWidget()
self.rr.setObjectName(_fromUtf8("rr"))
self.line_7 = QtGui.QFrame(self.rr)
self.line_7.setGeometry(QtCore.QRect(0, 100, 391, 20))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.line_7.setFont(font)
self.line_7.setFrameShadow(QtGui.QFrame.Raised)
self.line_7.setLineWidth(2)
self.line_7.setFrameShape(QtGui.QFrame.HLine)
self.line_7.setFrameShadow(QtGui.QFrame.Sunken)
self.line_7.setObjectName(_fromUtf8("line_7"))
self.rrload = QtGui.QPushButton(self.rr)
self.rrload.setGeometry(QtCore.QRect(20, 40, 101, 27))
self.rrload.setObjectName(_fromUtf8("rrload"))
self.rrload.clicked.connect(self.file_open2)
self.rrcoloroutput = QtGui.QTextEdit(self.rr)
self.rrcoloroutput.setGeometry(QtCore.QRect(270, 40, 111, 31))
self.rrcoloroutput.setObjectName(_fromUtf8("rrcoloroutput"))
self.label_7 = QtGui.QLabel(self.rr)
self.label_7.setGeometry(QtCore.QRect(140, 50, 121, 20))
self.label_7.setObjectName(_fromUtf8("label_7"))
self.rrcolorinput = QtGui.QTextEdit(self.rr)
self.rrcolorinput.setGeometry(QtCore.QRect(140, 140, 111, 31))
self.rrcolorinput.setObjectName(_fromUtf8("rrcolorinput"))
self.label_8 = QtGui.QLabel(self.rr)
self.label_8.setGeometry(QtCore.QRect(10, 150, 121, 17))
self.label_8.setObjectName(_fromUtf8("label_8"))
self.rrbutton = QtGui.QPushButton(self.rr)
self.rrbutton.setGeometry(QtCore.QRect(260, 140, 121, 27))
self.rrbutton.setObjectName(_fromUtf8("rrbutton"))
self.rrbutton.clicked.connect(self.Rkmeans)
self.label_4 = QtGui.QLabel(self.rr)
self.label_4.setGeometry(QtCore.QRect(10, 10, 161, 17))
self.label_4.setObjectName(_fromUtf8("label_4"))
self.label_9 = QtGui.QLabel(self.rr)
self.label_9.setGeometry(QtCore.QRect(10, 120, 141, 17))
self.label_9.setObjectName(_fromUtf8("label_9"))
self.txtlbl2_2 = QtGui.QLabel(self.rr)
self.txtlbl2_2.setGeometry(QtCore.QRect(400, 10, 121, 20))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.txtlbl2_2.setFont(font)
self.txtlbl2_2.setObjectName(_fromUtf8("txtlbl2_2"))
self.rrimageoutput = QtGui.QLabel(self.rr)
self.rrimageoutput.setGeometry(QtCore.QRect(400, 30, 191, 201))
self.rrimageoutput.setText(_fromUtf8(""))
self.rrimageoutput.setObjectName(_fromUtf8("rrimageoutput"))
self.line_2 = QtGui.QFrame(self.rr)
self.line_2.setGeometry(QtCore.QRect(380, 0, 16, 241))
self.line_2.setFrameShape(QtGui.QFrame.VLine)
self.line_2.setFrameShadow(QtGui.QFrame.Sunken)
self.line_2.setObjectName(_fromUtf8("line_2"))
self.line_11 = QtGui.QFrame(self.rr)
self.line_11.setGeometry(QtCore.QRect(0, 230, 601, 20))
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.line_11.setFont(font)
self.line_11.setFrameShadow(QtGui.QFrame.Raised)
self.line_11.setLineWidth(2)
self.line_11.setFrameShape(QtGui.QFrame.HLine)
self.line_11.setFrameShadow(QtGui.QFrame.Sunken)
self.line_11.setObjectName(_fromUtf8("line_11"))
icon2 = QtGui.QIcon()
icon2.addPixmap(QtGui.QPixmap(_fromUtf8("l.png")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
self.tabWidget.addTab(self.rr, icon2, _fromUtf8(""))
self.textEdit = QtGui.QTextEdit(self.centralwidget)
self.textEdit.setGeometry(QtCore.QRect(10, 300, 581, 151))
self.textEdit.setObjectName(_fromUtf8("textEdit"))
self.label_10 = QtGui.QLabel(self.centralwidget)
self.label_10.setGeometry(QtCore.QRect(10, 280, 141, 17))
self.label_10.setObjectName(_fromUtf8("label_10"))
MainWindow.setCentralWidget(self.centralwidget)
self.statusBar = QtGui.QStatusBar(MainWindow)
self.statusBar.setObjectName(_fromUtf8("statusBar"))
MainWindow.setStatusBar(self.statusBar)
self.actionAbout = QtGui.QAction(MainWindow)
self.actionAbout.setObjectName(_fromUtf8("actionAbout"))
sys.stdout = EmittingStream(textWritten=self.normalOutputWritten)
#print names
self.retranslateUi(MainWindow)
self.tabWidget.setCurrentIndex(0)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
# ---- Lables for elements in GUI--------#
def retranslateUi(self, MainWindow):
MainWindow.setWindowTitle(_translate("MainWindow", "Colour Learning", None))
self.label_6.setText(_translate("MainWindow", "Enter RGB Values or Load an image", None))
self.label.setText(_translate("MainWindow", "R", None))
self.label_2.setText(_translate("MainWindow", "G", None))
self.label_3.setText(_translate("MainWindow", "B", None))
self.enterrgb.setText(_translate("MainWindow", "Learn from RGB ", None))
self.learnload.setText(_translate("MainWindow", "Load Image", None))
self.label_5.setText(_translate("MainWindow", "Enter Color Name", None))
self.learnbutton.setText(_translate("MainWindow", "Learn from Image", None))
self.txtlbl2_3.setText(_translate("MainWindow", "Learning Image", None))
self.label_11.setText(_translate("MainWindow", "R", None))
self.label_12.setText(_translate("MainWindow", "G", None))
self.label_13.setText(_translate("MainWindow", "B", None))
self.tabWidget.setTabText(self.tabWidget.indexOf(self.learn), _translate("MainWindow", "Learning", None))
self.rrload.setText(_translate("MainWindow", "Load Image", None))
self.label_7.setText(_translate("MainWindow", "Color Recognised", None))
self.label_8.setText(_translate("MainWindow", "Type Color name", None))
self.rrbutton.setText(_translate("MainWindow", "Retrive Color", None))
self.label_4.setText(_translate("MainWindow", "Recognition of Color", None))
self.label_9.setText(_translate("MainWindow", "Retrieval of Color", None))
self.txtlbl2_2.setText(_translate("MainWindow", "Retrieved Image", None))
self.tabWidget.setTabText(self.tabWidget.indexOf(self.rr), _translate("MainWindow", "Recognition/Retrieval", None))
self.label_10.setText(_translate("MainWindow", "System Response", None))
self.actionAbout.setText(_translate("MainWindow", "About", None))
def __del__(self):
sys.stdout = sys.__stdout__
def normalOutputWritten(self, text):
cursor = self.textEdit.textCursor()
cursor.movePosition(QtGui.QTextCursor.End)
cursor.insertText(text)
self.textEdit.setTextCursor(cursor)
self.textEdit.ensureCursorVisible()
# ---- Input from User--------#
def inputrgb(self):
global Redinput
global Greeninput
global Blueinput
Redinput = int(self.Rinput.toPlainText())
Greeninput = int(self.Ginput.toPlainText())
Blueinput = int(self.Binput.toPlainText())
color_entered = str(self.learncolorinput.toPlainText())
color_entered = color_entered.lower()
# ---- Predicting color through k-means Clustering--------#
def kmeans(self):
# ---- creating kmeans cluster for the 1298 dataset-------_#
kmeans = KMeans(n_clusters=len(arr), random_state=0).fit(arr)
centroids = kmeans.cluster_centers_
labels = kmeans.labels_
# ---- gets RGB values from image--------#
testpt = []
testpt.append(Redinput)
testpt.append(Greeninput)
testpt.append(Blueinput)
# ----- displays the image for the corresponding RGB value ---------#
average_color_img = np.array([[testpt] * 250] * 250, np.uint8)
height, width, bytesPerComponent = average_color_img.shape
bytesPerLine = 3 * width
#average_color_img = cv2.cvtColor(average_color_img, cv2.COLOR_BGR2RGB)
qImg = QtGui.QImage(average_color_img.data, width, height, bytesPerLine, QImage.Format_RGB888)
self.learnimg.setPixmap(QtGui.QPixmap.fromImage(qImg))
# --------- user input of colorname --------------#
colorinput = color_entered
# ---------- loop checks whether color name already exist or not ---------------- #
for x in names:
if (x == colorinput.lower()):
print('Color Already Exist')
nametest = 0
break
else:
nametest = 1
# ------------- loop checks whether RGB already exist or not ----------------------#
for x in arr:
if (x == testpt):
print('RGB Already Exist')
rgbtest = 0
break
else:
rgbtest = 1
# ---------------- appends new colorname to the list ---------------------------#
if (nametest == 1 and rgbtest == 1):
# predicts the closest color
print ('Predicting!')
pred = kmeans.predict(np.array(testpt).reshape(1, -1))
predictedrgb = []
# ----------loop for plotting the predicted and the original color data-----#
for i in range(len(arr)):
# plots the graph in red for predefined color and blue for new color as x
if (labels[i] == pred):
predictedrgb = arr[i]
# ------------updating the list-------------------------------------#
names.append(colorinput)
red.append(predictedrgb[0])
green.append(predictedrgb[1])
blue.append(predictedrgb[2])
# writes the new list to the csv file
df = pd.DataFrame({'Name': names, 'R': red, 'G': green, 'B': blue})
df.to_csv('color_datasetapril26.csv', index=False)
print('New color name learnt!')
else:
print('Color and RGB value already exist')
kmeans(self)
# ------------------- Image Processing of the input image ----------------------------------------#
def file_open1(self):
dl= QtGui.QFileDialog()
input = QtGui.QFileDialog.getOpenFileName(dl, 'Open File')
if input.isEmpty() == False:
cvfilename = input.toLocal8Bit().data() # convert Qstring to char*
img = cv2.imread(cvfilename)
average_color_per_row = np.average(img, axis=0)
average_color = np.average(average_color_per_row, axis=0)
# Dominant RGB values
average_color = np.uint8(average_color)
average_color_img = np.array([[average_color] * 250] * 250, np.uint8)
height, width, bytesPerComponent = average_color_img.shape
bytesPerLine = 3 * width
average_color_img = cv2.cvtColor(average_color_img, cv2.COLOR_BGR2RGB)
qImg = QtGui.QImage(average_color_img.data, width, height, bytesPerLine, QImage.Format_RGB888)
self.learnimg.setPixmap(QtGui.QPixmap.fromImage(qImg))
global rgbvaluefromimage
rgbvaluefromimage = average_color.tolist()
Ripfromimage = str(rgbvaluefromimage[2])
Gipfromimage = str(rgbvaluefromimage[1])
Bipfromimage = str(rgbvaluefromimage[0])
self.Rinputfromimage.setText(Ripfromimage)
self.Ginputfromimage.setText(Gipfromimage)
self.Binputfromimage.setText(Bipfromimage)
self.learnbutton.clicked.connect(self.imagelearn)
#--------------- Learning through Human Interaction ---------------------#
def imagelearn(self):
color_entered = str(self.learncolorinput.toPlainText())
color_entered = color_entered.lower()
def kmeans(self):
# ------------- creating kmeans cluster for the 1298 dataset ---------#
kmeans = KMeans(n_clusters=len(arr), random_state=0).fit(arr)
centroids = kmeans.cluster_centers_
labels = kmeans.labels_
# ------ gets RGB values from image ----------#
testpt = rgbvaluefromimage
# --------- user input of colorname ----------#
colorinput = color_entered
# loop checks whether color name already exist or not
#for x in names:
#if (x == colorinput):
# print('Color Already Exist')
# nametest = 0
#break
#else:
# nametest = 1
# ----------- loop checks whether RGB already exist or not------------#
for x in arr:
if (x == testpt):
print('RGB Already Exist')
rgbtest = 0
break
else:
rgbtest = 1
# appends new colorname to the list
#if (nametest == 1 and rgbtest == 1):
if (rgbtest == 1):
# predicts the closest color
print ('Predicting!')
pred = kmeans.predict(np.array(testpt).reshape(1, -1))
predictedrgb = []
# loop for plotting the predicted and the original color data
for i in range(len(arr)):
# plots the graph in red for predefined color and blue for new color as x
if (labels[i] == pred):
predictedrgb = arr[i]
# gets the index value for the predicted color
# predictedcolor = arr.index([predictedrgb[0], predictedrgb[1], predictedrgb[2]])
# matches the name for the predicted color
# names[predictedcolor]
# ---------- updating the list -------------#
names.append(colorinput)
red.append(predictedrgb[0])
green.append(predictedrgb[1])
blue.append(predictedrgb[2])
# ----------writes the new list to the csv file--------#
df = pd.DataFrame({'Name': names, 'R': red, 'G': green, 'B': blue})
df.to_csv('color_datasetapril26.csv', index=False)
print('New color name learnt!')
kmeans(self)
# ----------- Predicting Color through from the user uploaded file----------#
def file_open2(self):
rrdl = QtGui.QFileDialog()
rrinput = QtGui.QFileDialog.getOpenFileName(rrdl, 'Open File')
if rrinput.isEmpty() == False:
rrcvfilename = rrinput.toLocal8Bit().data() # convert Qstring to char*
rrimg = cv2.imread(rrcvfilename)
rraverage_color_per_row = np.average(rrimg, axis=0)
rraverage_color = np.average(rraverage_color_per_row, axis=0)
# ----------- Dominant RGB values----------#
rraverage_color = np.uint8(rraverage_color)
global dominantrgb
dominantrgb = rraverage_color
print ("R = %d") % dominantrgb[2]
print ("G = %d") % dominantrgb[1]
print ("B = %d") % dominantrgb[0]
rraverage_color_img = np.array([[rraverage_color] * 250] * 250, np.uint8)
rrheight, rrwidth, rrbytesPerComponent = rraverage_color_img.shape
rrbytesPerLine = 3 * rrwidth
rraverage_color_img = cv2.cvtColor(rraverage_color_img, cv2.COLOR_BGR2RGB)
rrqImg = QtGui.QImage(rraverage_color_img.data, rrwidth, rrheight, rrbytesPerLine, QImage.Format_RGB888)
self.rrimageoutput.setPixmap(QtGui.QPixmap.fromImage(rrqImg))
# ---------- Recognition-- rr (from image)-----------#
def rrkmeans(self):
# creating kmeans cluster for the 1298 dataset
kmeans = KMeans(n_clusters=len(arr), random_state=0).fit(arr)
centroids = kmeans.cluster_centers_
labels = kmeans.labels_
# -----gets RGB values from image---------#
testpt = []
testpt.append(dominantrgb[2])
testpt.append(dominantrgb[1])
testpt.append(dominantrgb[0])
# ------loop checks whether RGB already exist or not---------#
for x in arr:
if (x == testpt):
print('RGB Already Exist')
rgbtest = 0
break
else:
rgbtest = 1
# ---------- predicts the colorname from the list --------------#
if (rgbtest == 1):
# predicts the closest color
pred = kmeans.predict(np.array(testpt).reshape(1, -1))
predictedrgb = []
# ---------- loop for plotting the predicted and the original color data----------#
for i in range(len(arr)):
# plots the graph in red for predefined color and blue for new color as x
if (labels[i] == pred):
predictedrgb = arr[i]
# --------- gets the index value for the predicted color ----------#
predictedcolor = arr.index([predictedrgb[0], predictedrgb[1], predictedrgb[2]])
# ---------- matches the name for the predicted color------------- #
nn = names[predictedcolor]
self.rrcoloroutput.setText(nn)
# ------------- finds the name from the database ------------------#
if (rgbtest == 0):
tt = 0 # tt gets the column number of the colorname
for x in arr:
tt = tt + 1
if (x == testpt):
rgbtest = 0
break
else:
rgbtest = 1
tt = tt - 1
nn = str(names[tt])
self.rrcoloroutput.setText(nn)
rrkmeans(self)
#Retrieval-- R
def Rkmeans(self):
# user input of colorname
colorinput = str(self.rrcolorinput.toPlainText())
yy = 0 #yy has the column number of the colorname
for x in names:
yy = yy+1
if (x.lower() == colorinput.lower()):
nametest = 0
break
else:
nametest = 1
if nametest == 1:
print('Entered Color not in Database')
if nametest == 0:
yy = yy - 1
testpt = arr[yy]
rraverage_color_img = np.array([[testpt] * 250] * 250, np.uint8)
rrheight, rrwidth, rrbytesPerComponent = rraverage_color_img.shape
rrbytesPerLine = 3 * rrwidth
#rraverage_color_img = cv2.cvtColor(rraverage_color_img, cv2.COLOR_BGR2RGB)
rrqImg = QtGui.QImage(rraverage_color_img.data, rrwidth, rrheight, rrbytesPerLine, QImage.Format_RGB888)
self.rrimageoutput.setPixmap(QtGui.QPixmap.fromImage(rrqImg))
print ("R = %d") % testpt[0]
print ("G = %d") % testpt[1]
print ("B = %d") % testpt[2]
# -------------------- Main Function --------------------- #
def main():
global average_color
average_color = []
global rraverage_color
rraverage_color = []
# ------- creating list from data frame------ #
global red
global green
global blue
global names
global arr
df = pd.read_csv('color_datasetapril26.csv')
red = df.reset_index()['R'].values.tolist()
green = df.reset_index()['G'].values.tolist()
blue = df.reset_index()['B'].values.tolist()
names = df.reset_index()['Name'].values.tolist()
arr = df.reset_index()[['R', 'G', 'B']].values.tolist()
#print isinstance(arr, list)
app = QtGui.QApplication(sys.argv)
MainWindow = QtGui.QMainWindow()
ui = Ui_MainWindow()
ui.setupUi(MainWindow)
MainWindow.show()
sys.exit(app.exec_())
if __name__ == "__main__":
main()