WEBSITE

flaskblog/__init__.py

@@ -0,0 +1,16 @@
+from flask import Flask
+from flask_sqlalchemy import SQLAlchemy
+from flask_bcrypt import Bcrypt
+from flask_login import LoginManager
+from google.oauth2.credentials import Credentials
+from google_auth_oauthlib.flow import Flow
+
+app = Flask(__name__, template_folder='templates/', static_folder='templates/static/')
+app.config['SECRET_KEY']= 'd7ffffeda6d2eee20b6678d783312c7b'
+app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///site.db'
+db = SQLAlchemy(app)
+bcrypt = Bcrypt(app)
+login_manager = LoginManager(app)
+# app.config['OPTIONS'] = {'index_files': []}
+
+from flaskblog import routes

flaskblog/forms.py

@@ -0,0 +1,25 @@
+from flask_wtf import FlaskForm
+from wtforms import StringField, PasswordField, SubmitField, BooleanField
+from wtforms.validators import DataRequired, Length, Email, EqualTo, ValidationError
+from flaskblog.models import User
+
+
+class RegistrationForm(FlaskForm):
+    email = StringField('Email',
+                        validators=[DataRequired(), Email()])
+    password = PasswordField('Password', validators=[DataRequired()])
+    confirm_password = PasswordField('Confirm Password',
+                                     validators=[DataRequired(), EqualTo('password')])
+    submit = SubmitField('Sign Up')
+    def validate_email(self, email):
+
+        user = User.query.filter_by(email=email.data).first()
+        if user:
+            raise ValidationError('That email is already exsist')
+
+class LoginForm(FlaskForm):
+    email = StringField('Email',
+                        validators=[DataRequired(), Email()])
+    password = PasswordField('Password', validators=[DataRequired()])
+    remember = BooleanField('Remember Me')
+    submit = SubmitField('Login')

flaskblog/models.py

@@ -0,0 +1,27 @@
+from datetime import datetime
+from flaskblog import db, login_manager
+from flask_login import UserMixin
+
+@login_manager.user_loader
+def load_user(user_id):
+    return User.query.get(int(user_id))
+
+
+class User(db.Model, UserMixin):
+    id = db.Column(db.Integer, primary_key=True)
+    email = db.Column(db.String(120), unique=True, nullable=False)
+    password = db.Column(db.String(60), nullable=False)
+    posts = db.relationship('Post', backref='author', lazy=True)
+
+    def __repr__(self):
+        return f"User('{self.email}')"
+
+
+class Post(db.Model):
+    id = db.Column(db.Integer, primary_key=True)
+    path = db.Column(db.String(100), nullable=False)
+    date_posted = db.Column(db.DateTime, nullable=False, default=datetime.utcnow)
+    user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
+
+    def __repr__(self):
+        return f"Post('{self.path}', '{self.date_posted}')"

flaskblog/routes.py

@@ -0,0 +1,114 @@
+from flask import Flask , request, jsonify, render_template , url_for , redirect , flash 
+from flaskblog import app, db, bcrypt
+from flaskblog.forms import RegistrationForm, LoginForm
+from flaskblog.models import User, Post
+from flask_login import login_user, current_user, logout_user, login_required
+import tensorflow as tf
+import numpy as np
+from PIL import Image,  UnidentifiedImageError
+
+
+
+# Load the trained model
+model = tf.keras.models.load_model('model_2 (3).h5')
+
+# Define function to preprocess image for model input
+def predict_category(file):
+    categories = ['glioma_tumor', 'meningioma_tumor', 'pituitary_tumor', 'no_tumor']
+    img = Image.open(file)
+    img = img.resize((224, 224))
+
+    # Convert image to 3-channel format if necessary
+    if img.mode != 'RGB':
+        img = img.convert('RGB')
+
+    i = np.array(img, dtype='float32')
+    i /= 255.0 # normalize image
+    arr_reshaped = i.reshape((-1, 224, 224, 3))
+    output = model.predict(arr_reshaped)
+    result = categories[np.argmax(output)]
+    return result
+
+@app.route('/' , methods=['GET'])
+def home():
+    return render_template('index.html')
+
+
+
+@app.route("/login", methods=['GET', 'POST'])
+def login():
+    if current_user.is_authenticated:
+        return redirect(url_for('prediction'))
+    form = LoginForm()
+    if form.validate_on_submit():
+        user = User.query.filter_by(email=form.email.data).first()
+        if user and bcrypt.check_password_hash(user.password , form.password.data) :
+            login_user(user, remember=form.remember.data)
+            return redirect(url_for('prediction'))
+        else : 
+            flash('Login Unsuccessful. Please check email and password', 'danger')
+    return render_template('login.html', title='Login', form=form)
+
+
+
+@app.route("/Signup", methods=['GET', 'POST'])
+def Signup():
+    if current_user.is_authenticated:
+        return redirect(url_for('prediction'))
+    form = RegistrationForm()
+    if form.validate_on_submit():
+        hashed_password = bcrypt.generate_password_hash(form.password.data).decode('utf_8')
+        user = User(email=form.email.data, password=hashed_password)
+        db.session.add(user)
+        db.session.commit()
+        #to query all users
+        # u=User.query.all()
+        # for uu in u :
+        #     print(uu)
+        flash(f'Your account has been created! Please login', 'success')
+        return redirect(url_for('login'))
+    return render_template('Signup.html', title='Signup', form=form)
+
+
+@app.route("/supervisors")
+def super():
+
+    return render_template('super.html')
+
+
+
+@app.route("/logout")
+def logout():
+    logout_user()
+    return redirect(url_for('home'))
+
+
+
+
+
+
+@app.route('/prediction' , methods=['GET'])
+def prediction():
+    return render_template('Prediction.html')
+
+
+
+
+
+
+
+@app.route('/predict', methods=['POST'])
+def predict_image():
+    # Get image file path from request
+    file = request.files['image']
+    if file.filename == '':
+         return jsonify({'error': 'No file selected'})
+
+
+    # Make prediction with model
+    predicted_category = predict_category(file)
+    # Return predicted category as JSON response
+    return jsonify({'category': predicted_category})
+
+
+

flaskblog/templates/Prediction.html

@@ -0,0 +1,184 @@
+<!DOCTYPE html>
+  <html lang="en">
+<html>
+<head>
+  <meta charset="UTF-8">
+  <meta http-equiv="X-UA-Compatible" content="IE=edge">
+  <meta name="viewport" content="width=device-width, initial-scale=1.0">
+  <link href="static/css/bootstrap.min.css" rel="stylesheet">
+  <link rel="stylesheet" href="static/style.css">
+  <title>RadioShash</title>
+  <script src="{{ url_for('static', filename='js/particles.min.js') }}"></script>
+  <link rel="icon" href="static/img/5801748.jpg " height="35px" width="40px" class="rounded-circle">
+  <script>
+    var message = "right click is disabled";
+
+    function rtclickcheck(keyp) {
+      if (navigator.appName == "Netscape" && keyp.which == 3) {
+        alert(message);
+        return false;
+      }
+      if (navigator.appVersion.indexOf("MSIE") != -1 && event.button == 2) {
+        alert(message);
+        return false;
+      }
+    }
+
+    document.onmousedown = rtclickcheck;
+  </script>
+   <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
+   <script>
+       $(document).ready(function() {
+           // Capture form submission event
+           $('form').submit(function(event) {
+               event.preventDefault(); // Prevent default form submission behavior
+
+               // Create FormData object to capture form data
+               var formData = new FormData(this);
+
+               // Make AJAX request to /predict endpoint
+               $.ajax({
+                   url: '/predict',
+                   type: 'POST',
+                   data: formData,
+                   contentType: false,
+                   processData: false,
+                   success: function(response) {
+                       // Update the predicted category in the <div> element
+                       $('#predicted-category').html('<h2>Result: ' + response.category + '</h2>');
+                   },
+                   error: function() {
+                       console.log('Error occurred during prediction request.');
+                   }
+               });
+           });
+       });
+   </script>
+</head>
+
+<body>
+  <!-- navbar -->
+  <nav class="navbar navbar-expand-lg bg-dark navbar-dark fixed-top">
+    <div class="container">
+      <!-- <a href="Prediction.html" class="navbar-brand">RadioShash_WebSite</a>  -->
+      <a href="{{ url_for('home') }}" class="navbar-brand"><img src="static/img/5801748.jpg" alt="" height="35px" width="40px" class="rounded-circle">RadioShash</a>
+      <button class="navbar-toggler" type="button"data-bs-toggle="collapse"data-bs-target="#navmenu">
+        <span class="navbar-toggler-icon"></span>  
+      </button>
+      <div class="collapse navbar-collapse" id="navmenu">
+        <ul class="navbar-nav ms-auto">
+          <li class="nav-item">
+            <a href="{{ url_for('home') }}" class="nav-link">Home</a>
+          </li>
+          <li class="nav-item">
+            <!-- <a href="index.html" class="nav-link">Logout</a> -->
+            <a href="{{ url_for('logout') }}" class="nav-link">Logout</a>
+          </li>
+        </ul>
+      </div>
+    </div> 
+  </nav>
+
+
+
+  <section id="particles-js" class=" bg-dark vh-50">
+
+
+
+     <!-- AI model -->
+     <main>
+      <h2 class="my py-5 my-5">Upload Image</h2>
+      <form action="/predict" method="POST" enctype="multipart/form-data" class="p-3 text-center">
+          <input class="form-control" type="file" name="image">
+          <br><br>
+          <input class="btn btn-primary mt-3" type="submit" value="Submit">
+      </form>
+      <div id="predicted-category" style="color: grey;">
+        {% if category %}
+            <h2>Your Result is: {{ category }}</h2>
+        {% endif %}
+      </div>
+
+
+      <div id="predicted-category" style="color: grey;">
+        {% if error %}
+            <h2> {{ error }}</h2>
+        {% endif %}
+      </div>
+    </main>
+
+
+
+
+
+
+
+  </section>
+
+
+
+
+
+ <!-- footer -->
+ <footer class="p-5 bg-dark text-white text-center position-relative">
+  <div class="container">
+    <p class="leadd">Copy &copy; RadioShash</p>
+
+    <a href="#" class="position-absolute bottom-0 end-0 p-5">
+      <i class="bi bi-arrow-up-circle h1"></i>
+    </a>
+  </div>
+</footer>
+
+
+
+
+  <!-- <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js" integrity="sha384-MrcW6ZMFYlzcLA8Nl+NtUVF0sA7MsXsP1UyJoMp4YLEuNSfAP+JcXn/tWtIaxVXM" crossorigin="anonymous">
+
+  </script> -->
+
+  <script src="static/js/bootstrap.min.js"></script>
+
+
+
+<script>
+  particlesJS.load('particles-js', "{{ url_for('static', filename='js/particles.json') }}");
+</script>
+
+<script>
+  var navbar = document.querySelector('.navbar');
+  var body = document.querySelector('body');
+  var lastScroll = 0;
+
+  window.addEventListener('scroll', function() {
+    var currentScroll = window.pageYOffset || document.documentElement.scrollTop;
+    var bodyColor = window.getComputedStyle(body).backgroundColor;
+
+    if (currentScroll > lastScroll) {
+      navbar.style.backgroundColor = bodyColor;
+    } else {
+      navbar.style.backgroundColor = 'transparent';
+    }
+
+    if (currentScroll > 0) {
+      navbar.classList.add('navbar-scrolled');
+    } else {
+      navbar.classList.remove('navbar-scrolled');
+    }
+
+    lastScroll = currentScroll;
+  });
+
+
+
+
+
+
+</script>
+
+</body>
+
+</html>
+
+
+