all added

README.md

-womens-diabetics-prediction-system
+
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+**Members:**
+
+Member 1: Haque, Syed Wassi Ul  22108223
+<br/><br/>
+Member 2: Mahir, Wasik , 00817406
+
+<br/><br/>
+
+
+**Title:**  Women Diabetes Prediction System
+
+<br/><br/>
+
+**MyGit Repository Link: https://mygit.th-deg.de/sh13223/womens-diabetics-prediction-system**
+
+**MyGit Wiki Repository Link:__**
+
+<br/><br/>
+
+
+**Project description:** 
+
+A machine learning model designed to predict diabetes in female patients. 
+This project uses SVM(Support Vector Machine) Algorithm  to train on a given dataset. 
+Interactive GUI is developed using PyQt6 and css.
+
+
+**Prerequisites:** 
+
+1. Pycharm or Vscode or any types of  IDE.
+
+2.  Creating a virtual environment.
+
+3. Libraries to be installed in virtual environment:
+    - PyQt6 = 6.6.1   
+    - Pyqtgraph = 0.13.3   
+    - Python = 3.11.7  
+    - Numpy = 1.26.3 
+    - Matplotlib = 3.8.2  
+    - Pandas = 2.1.4  
+    - Scikit-learn = 1.3.2
+
+4. Diabetes Dataset(Source: Kaggle):
+Link to download the data:    (https://www.kaggle.com/code/sandragracenelson/diabetes-prediction/input)
+
+**Installation:**
+
+  - Create and run  a virtual environment
+  
+  - Clone the git repository with the dataset file.
+  
+  - Install necessary packages from requirement.txt file.
+  
+  - Run  main_diabetics.py.
+
+**Basic Usage:**
+
+1. Run the main_diabetics.py in any IDE.
+2. Upon execution, a window will prompt the user to input their Glucose level, Blood Pressure, Age, Insulin, BMI, and Pregnancy status using sliding buttons. For Pregnancy status, use a tick button to indicate if applicable.
+3. After inputting all details, click the "Predict" button to determine diabetic status."
+4. To exit the widget, simply press the cross button in the top right corner of the widget.
+
+
+
+**Implementation of the Requests:**
+1. A Desktop App with PyQT6 has been developed.
+2. A requirements.txt file is added with the necessary python libraries.
+3. A README.md file is created with the structure description.
+4. Virtual environment (venv) is created and used.
+5. A free data source has been from  Kaggle(Link has given above).
+6. Data has been imported using csv format. (File name: diabetes_clean_03042021.csv) and  can be seen from the terminal after running the app.
+7. The data must be analyzed with Pandas methods, so that a user gets an overview.
+8. The following functions have been used to get the overview of the data: dataframe.info(), dataframe.describe(),dataframe.corr(), dataframe.head(), dataframe.tail().
+9. Three input widgets have been created.
+10. Model has been trained using Scikit training model algorithm.( for our case we used SVM model algorithm)
+11. Two output canvas have been for data visualization.
+12. The app is reacting interactively according to the change of input parameter with a new prediction.
+
+<br/><br/>
+
+**Contribution List:** 
+
+
+1. Syed Wassi Ul Haque:
+     - Worked on Collection and Preprocessing of Dataset using Pandas.
+     - Modifying and Preparing Data with use of numpy arrays.
+     - Bug solving and creating Main window Graph to visualize the data on  app using matplotlib.pyplot.
+     - Creating  Histogram window Interface using PyQt6.
+     - Designing the app using css stylesheet.
+ 
+2. Wasik Mahir:
+     - Creating a GUI Interface using PyQt6( Main window, Plot graph window)
+     - Getting User-Inputs using different GUI elements or creating widgets.
+     - Training and working Scikit-learn SVM Model.
+     - Integrating or connecting Scikit learn model with pyqt6 in order to get predictions in the app.
+     - Designing the app using css stylesheet.

main_diabetics.py

+import sys
+from PyQt6 import QtWidgets,QtGui
+from pyqtgraph import PlotWidget, plot
+import pyqtgraph as pg
+
+from PyQt6.QtWidgets import QWidget,QHBoxLayout, QApplication,QSlider, QMainWindow,QLabel, QPushButton,QHBoxLayout, QVBoxLayout, QGridLayout, QCheckBox
+from PyQt6.QtCore import Qt
+from PyQt6.QtGui import QAction, QIcon,QPalette, QColor
+
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+
+
+import matplotlib
+import matplotlib.pyplot as plt
+from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg as FigureCanvas
+from matplotlib.figure import Figure
+matplotlib.use('Qt5Agg')
+
+from sklearn.preprocessing import StandardScaler
+from sklearn.model_selection import train_test_split
+from sklearn import svm
+from sklearn.metrics import accuracy_score
+
+from PyQt6 import QtGui
+
+
+diabetes = pd.read_csv('diabetes_clean_03042021.csv')
+
+
+# highest correlation ----   x=age y=blood pressure
+
+
+class MplCanvas(FigureCanvas):
+
+    def __init__(self, parent=None, width=5, height=2, dpi=100):
+        self.figure = Figure(figsize=(width, height), dpi=dpi)
+        self.axes = self.figure.add_subplot(111)
+        super(MplCanvas, self).__init__(self.figure)
+
+class secondWindow(QMainWindow):
+    def __init__(self):
+        super().__init__()
+        # use global data
+
+        global diabetes
+        
+        widget_histogram = QWidget()
+
+        # Vertical Layout
+        histogram_layout = QVBoxLayout()
+        
+        # Create a new Canvas
+        self.histogram_screen = MplCanvas(self, width=5, height=2, dpi=100)
+
+        diabetes.hist(ax=self.histogram_screen.axes)
+ 
+        histogram_layout.addWidget(self.histogram_screen)
+        self.setCentralWidget(widget_histogram)
+        widget_histogram.setLayout(histogram_layout)
+        self.setMinimumSize(1500, 1000)
+
+
+class thirdWindow(QMainWindow):
+
+    def __init__(self):
+        super().__init__()
+
+        global diabetes
+
+        self.graphWidget = pg.PlotWidget()
+        self.setCentralWidget(self.graphWidget)
+
+        self.x = diabetes["BMI"]
+        self.y = diabetes["Outcome"]
+
+
+        self.graphWidget.setBackground('w')
+        self.graphWidget.setLabel("left", "Diabetic Or Not Diabetic")
+        self.graphWidget.setLabel("bottom", "BMI")
+
+        pen = pg.mkPen(color=(255, 0, 0))
+        self.data_line =  self.graphWidget.plot(self.x, self.y, pen=pen)
+        self.setMinimumSize(800, 400)
+
+
+class MainWindow(QMainWindow):
+
+    def design(self):
+
+        layout3 = QHBoxLayout()
+        MainLayout = QHBoxLayout()
+        leftVerticalLayout = QVBoxLayout()
+        RightVerticalLayout = QVBoxLayout()
+        
+         
+        # setting window icon
+        self.setWindowIcon(QtGui.QIcon('health.png'))
+        #setting screen min size
+        self.setMinimumSize(1200, 800)
+
+        mainLabel = QLabel(" Women Diabetics Prediction System")
+        leftVerticalLayout.addWidget(mainLabel)
+
+        
+        
+        # checkbox button pregnancies
+        pregnanciesLabel = QLabel("Pregnancies", alignment=Qt.AlignmentFlag.AlignCenter)
+        pregnant_instruction = QLabel("Please click the box if Pregnant.", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(pregnanciesLabel)
+        leftVerticalLayout.addWidget(pregnant_instruction)
+        self.pregnancies_checkbox = QCheckBox(text="Not Pregnant")
+        leftVerticalLayout.addWidget(self.pregnancies_checkbox)
+        self.pregnancies_checkbox.stateChanged.connect(self.Pregnancies_onStateChanged)
+
+        # Silder button  glucose 
+        self.Glucose = QSlider(Qt.Orientation.Horizontal)
+        self.Glucose.setMinimum(30)
+        self.Glucose.setMaximum(200)
+        self.Glucose.valueChanged.connect(self.updateSlider_Glucose)
+        self.Glucose.setGeometry(5, 3, 20, 20)
+        self.selectedValue_glucose = QLabel(self)
+        self.selectedValue_glucose.setText(str(30))
+        glocoseLabel = QLabel("Glucose [30 - 200]", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(glocoseLabel)
+        leftVerticalLayout.addWidget(self.Glucose)
+        leftVerticalLayout.addWidget(self.selectedValue_glucose)
+
+
+        # Silder button  blood pressure 
+        self.BloodPressure = QSlider(Qt.Orientation.Horizontal)
+        self.BloodPressure.setMinimum(30)
+        self.BloodPressure.setMaximum(120)
+        self.BloodPressure.valueChanged.connect(self.updateSlider_BloodPressure)
+        self.BloodPressure.setGeometry(5, 3, 20, 20)
+        self.selectedValue_blood = QLabel(self)
+        self.selectedValue_blood.setText(str(30))
+        bloodpressureLabel = QLabel("Blood Pressure [30 - 120]", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(bloodpressureLabel)
+        leftVerticalLayout.addWidget(self.BloodPressure)
+        leftVerticalLayout.addWidget(self.selectedValue_blood)
+
+
+        # Silder button  skin thickness 
+        self.SkinThickness = QSlider(Qt.Orientation.Horizontal)
+        self.SkinThickness.setMinimum(0)
+        self.SkinThickness.setMaximum(100)
+        self.SkinThickness.valueChanged.connect(self.updateSlider_skinThickness)
+        self.SkinThickness.setGeometry(5, 3, 20, 20)
+        self.selectedValue_skin = QLabel(self)
+        self.selectedValue_skin.setText(str(0))
+        skinThicknessLabel = QLabel("Skin Thickness[0 - 100]", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(skinThicknessLabel)
+        leftVerticalLayout.addWidget(self.SkinThickness)
+        leftVerticalLayout.addWidget(self.selectedValue_skin)
+
+
+        # Silder button  Insulin 
+        self.Insulin = QSlider(Qt.Orientation.Horizontal)
+        self.Insulin.setMinimum(5)
+        self.Insulin.setMaximum(700)
+        self.Insulin.valueChanged.connect(self.updateSlider_insulin)
+        self.Insulin.setGeometry(5, 3, 20, 20)
+        self.selectedValue_insulin = QLabel(self)
+        self.selectedValue_insulin.setText(str(5))
+        insulinLabel = QLabel("Insulin [5 - 700]", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(insulinLabel)
+        leftVerticalLayout.addWidget(self.Insulin)
+        leftVerticalLayout.addWidget(self.selectedValue_insulin)
+
+
+
+
+        # Silder button  BMI
+        self.BMI = QSlider(Qt.Orientation.Horizontal)
+        self.BMI.setMinimum(10)
+        self.BMI.setMaximum(80)
+        self.BMI.valueChanged.connect(self.updateSlider_BMI)
+        self.BMI.setGeometry(5, 3, 20, 20)
+        self.selectedValue_BMI = QLabel(self)
+        self.selectedValue_BMI.setText(str(10))
+        bmiLabel = QLabel("BMI [10 - 80]", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(bmiLabel)
+        leftVerticalLayout.addWidget(self.BMI)
+        leftVerticalLayout.addWidget(self.selectedValue_BMI)
+
+
+        # Silder button  DiabetesPredegreeFunction
+        self.DiabetesPredegreeFunction = QSlider(Qt.Orientation.Horizontal)
+        self.DiabetesPredegreeFunction.setMinimum(0)
+        self.DiabetesPredegreeFunction.setMaximum(4)
+        self.DiabetesPredegreeFunction.setTickInterval(4)
+        self.DiabetesPredegreeFunction.valueChanged.connect(self.updateSlider_dibeticsPredegree)
+        self.DiabetesPredegreeFunction.setGeometry(5, 3, 20, 20)
+        self.selectedValue_predegree = QLabel(self)
+        self.selectedValue_predegree.setText(str(0))
+        label7 = QLabel("Diabetes Predegree Func [0 - 4]", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(label7)
+        leftVerticalLayout.addWidget(self.DiabetesPredegreeFunction)
+        leftVerticalLayout.addWidget(self.selectedValue_predegree)
+
+
+
+        # Silder button  Age
+        self.age = QSlider(Qt.Orientation.Horizontal)
+        self.age.setMinimum(18)
+        self.age.setMaximum(150)
+        self.age.valueChanged.connect(self.updateSlider_Age)
+        self.age.setGeometry(5, 3, 20, 20)
+        self.selectedValue_age = QLabel(self)
+        self.selectedValue_age.setText(str(18))
+        label8 = QLabel("Age [18 - 150]", alignment=Qt.AlignmentFlag.AlignCenter)
+        leftVerticalLayout.addWidget(label8)
+        leftVerticalLayout.addWidget(self.age)
+        leftVerticalLayout.addWidget(self.selectedValue_age)
+
+
+        # Push button  Predict
+        self.predict = QPushButton("Predict")
+        leftVerticalLayout.addWidget(self.predict)
+        self.predict.clicked.connect(self.predictiveSystem)
+        self.predictedValue = QLabel(" Prediction: None", self)
+        leftVerticalLayout.addWidget(self.predictedValue)
+
+
+        ####----------------Main Window Graph ------------
+    
+        self.setWindowTitle('Women Diabetics Prediction')
+
+        x = diabetes["Age"]
+        y = diabetes["Glucose"]
+        
+
+        fig = Figure()
+        ax =fig.add_subplot(111)
+     
+        ax.set_title('Glucose Levels Across Age:Predicting Diabetes Risk.')
+        x_label= ax.set_xlabel('Age')
+        y_label = ax.set_ylabel('Glucose')
+        
+        #ax.bar(x,y)
+        ax.bar(x,y)
+        graph =FigureCanvas(fig)
+
+
+        ###--------Connecting (all the buttons to left vertical layout) & (graph to the right vertical layout)
+        RightVerticalLayout.addWidget(graph)
+        MainLayout.addLayout(leftVerticalLayout) 
+        MainLayout.addLayout(RightVerticalLayout)
+        
+       
+        mainWidget = QWidget()
+        mainWidget.setLayout(MainLayout)
+        self.setCentralWidget(mainWidget)
+
+
+
+
+       
+
+        # menu
+
+        # action 1 from menu
+        self.window2 = None 
+        histogram_action = QAction(QIcon("chart-medium.png"), "Histogram", self)
+        histogram_action.setStatusTip("View Histogram.")
+        histogram_action.triggered.connect(self.show_hist_window)
+
+        # action 2 from menu
+        self.window3 = None 
+        plot_action = QAction(QIcon("plot.png"), "Plot Graph", self)
+        plot_action.setStatusTip("Real Time Graph")
+        plot_action.triggered.connect(self.show_realTime_window)
+
+        menu = self.menuBar()
+        file_menu = menu.addMenu("&Menu")
+        file_menu.addAction(histogram_action)
+        file_menu.addAction(plot_action)
+
+
+
+
+    def Pregnancies_onStateChanged(self):
+        if self.pregnancies_checkbox.isChecked():
+            self.pregnancies_checkbox.setText("Pregnant")
+        else:
+            self.pregnancies_checkbox.setText("Not Pregnant") 
+
+    def updateSlider_pregnancies(self):
+        val = self.pregnancies.value()
+        self.selectedValue_preg.setText(str(val))
+    def updateSlider_Glucose(self):
+        val = self.Glucose.value()
+        self.selectedValue_glucose.setText(str(val))
+    def updateSlider_BloodPressure(self):
+        val = self.BloodPressure.value()
+        self.selectedValue_blood.setText(str(val))
+    def updateSlider_skinThickness(self):
+        val = self.SkinThickness.value()
+        self.selectedValue_skin.setText(str(val))
+    def updateSlider_insulin(self):
+        val = self.Insulin.value()
+        self.selectedValue_insulin.setText(str(val))
+    def updateSlider_BMI(self):
+        val = self.BMI.value()
+        self.selectedValue_BMI.setText(str(val))
+    def updateSlider_dibeticsPredegree(self):
+        val = self.DiabetesPredegreeFunction.value()
+        self.selectedValue_predegree.setText(str(val))
+    def updateSlider_Age(self):
+        val = self.age.value()
+        self.selectedValue_age.setText(str(val))
+
+    def show_hist_window(self):
+        if self.window2 is None:
+            self.window2 = secondWindow()
+        self.window2.show()
+
+    def show_realTime_window(self):
+        if self.window3 is None:
+            self.window3 = thirdWindow()
+        self.window3.show()
+
+    def generateData(self):
+        global diabetes
+        self.diabetes = pd.read_csv('diabetes_clean_03042021.csv')
+        print("self.diabetes.head(8):")
+        print(self.diabetes.head(10))
+        print("self.diabetes.tail(5): ")
+        print(self.diabetes.tail(5))
+        print("self.diabetes.info():")
+        print(self.diabetes.info())
+
+        # number of rows and columns
+        print("Rows: ", self.diabetes.shape[0])
+        print("Columns: ", self.diabetes.shape[1])
+        print("self.diabetes.describe(): ")
+        print(self.diabetes.describe())
+        print("Total Diabetic(1) and Non-diabetic(0) patient:", self.diabetes['Outcome'].value_counts())
+        print("[Mean] grouped by diabetic(1) and Non-diabetic(0) patient: ")
+        print(self.diabetes.groupby('Outcome').mean())
+
+        # ----------- Machine learning ------
+        print("-----Training data-----")
+        x = self.diabetes.drop(columns='Outcome', axis=1)  # data
+        y = self.diabetes['Outcome']  # model
+
+        # Data Standardization
+        self.scaler = StandardScaler()
+        self.scaler.fit(x)
+        standardized_data = self.scaler.transform(x)
+        # print(standardized_data)
+
+        x = standardized_data  # data
+        y = self.diabetes['Outcome']  # model
+
+        # Train Test Split
+        x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.20, random_state=42)
+        # test_size = 0.20 means 20% test data  and 80% train data
+
+        # print(x.shape, x_train.shape, x_test.shape)
+
+        # Training The Model with SVM Algorithm
+        self. svm_classifier = svm.SVC(kernel='linear')
+        # training the support vector machine classifier
+        self.svm_classifier.fit(x_train, y_train)
+
+        # Accuracy Check
+        # Train Data
+        x_train_prediction = self.svm_classifier.predict(x_train)
+        training_data_accuracy = accuracy_score(x_train_prediction, y_train)
+        print("Accuracy Score of the training data: ", training_data_accuracy)
+
+        # Test data
+        x_test_prediction = self.svm_classifier.predict(x_test)
+        test_data_accuracy = accuracy_score(x_test_prediction, y_test)
+        print("Accuracy Score of the testing data: ", test_data_accuracy)
+
+
+        # correlation ---- highest  x=age y=blood pressure
+        corr_matrix = self.diabetes.corr()
+        print("self.diabetes.corr(): ", corr_matrix)
+        
+        if (x_test_prediction[0] == 0):
+            result = print("The person is not diabetic. ")
+        else:
+            result = print("The person is diabetic. ")
+
+    # calculating the values for the predictive System
+    def predictiveSystem(self):
+        global result
+        from random import randint
+        count = randint(0, 767)
+        
+        # converting checkbox value into  0 or 1
+        if self.pregnancies_checkbox.isChecked() == True:
+            pregnancies_checkbox = 1
+        else:
+            pregnancies_checkbox = 0
+
+        Glucose = self.Glucose.value()
+        BloodPressure =self.BloodPressure.value()
+        SkinThickness = self.SkinThickness.value()
+        Insulin = self.Insulin.value()
+        bmi = self.BMI.value()
+        DiabetesPedigreeFunction = self.DiabetesPredegreeFunction.value()
+        Age = self.age.value()
+
+        # inputData = [value,1, 110, 92, 0, 0, 37.6,0.191, 30]
+        sampleData = [count, pregnancies_checkbox, Glucose, BloodPressure, SkinThickness, Insulin, bmi, DiabetesPedigreeFunction,
+                      Age]
+
+        # change the input data to numpy array
+        sampleData_numpy = np.asarray(sampleData)
+
+        # reshaping array as we are predicting for one instance
+        reshaping = sampleData_numpy.reshape(1, -1)
+
+        # standardize the input data
+        standardize_sampleData = self.scaler.transform(reshaping)
+        # print(std_data)
+
+        prediction = self.svm_classifier.predict(standardize_sampleData)
+        print(prediction)
+        if (prediction[0] == 0):
+            
+            self.predictedValue.setText("Prediction: The person is not diabetic. ")
+        else:
+            
+            self.predictedValue.setText("Prediction: The person is  diabetic. ")
+
+
+
+
+if __name__ == '__main__':
+        app = QApplication(sys.argv)
+        
+        with open("style.css", "r") as file:
+            app.setStyleSheet(file.read())
+            
+        window = MainWindow()
+        #window.setFixedSize(1200,800)
+        
+   
+        window.design()
+        window.generateData()
+
+        window.show()
+
+        sys.exit(app.exec())

style.css

+QMainWindow {
+    background-color: #1e1f22;
+    border-radius: 5px;
+    background-image: url('image.jpg'); /* set the path to your image */
+    background-repeat: no-repeat; /* prevent the image from repeating */
+    background-position: center; /* position the image in the center */
+    
+}
+
+QSlider::handle:horizontal {
+    background: #13fcec;
+    width: 10px;
+    margin: -5px -1px;
+    border-radius: 5px;
+    border: 1px solid #2a2a2a;
+}
+QSlider::groove:horizontal {
+    background: #ffffff6a;
+    height:2px;
+    border: 1px solid #2a2a2a;
+}
+
+QPushButton {
+    background-color: #1ffcd3; /* set the background color */
+    color: #0f3f33; /* set the text color */
+    border: 1px solid #0fe6b490; /* add a border */
+    padding: 5px 10px; /* add padding */
+    border-radius: 5px;
+}
+QLabel {
+    color: #ffffff; /* set the text color for labels */
+    font-size: 14px; /* set the font size for labels */
+    font-family: 'Courier New', Monospace; /* set the font family for labels */
+    font-weight: bold;
+}
+
+QCheckBox {
+    color: #ffffff; /* set the text color for labels */
+    font-size: 18px; /* set the font size for labels */
+    font-family: 'Courier New', Monospace; /* set the font family for labels */
+    font-weight: bold;
+}