BrainTumorPP

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LovnishVerma commited on Dec 17, 2024

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ec882da

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1 Parent(s): e5df06f

Update main.py

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main.py +140 -228

main.py CHANGED Viewed

@@ -1,230 +1,142 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <!-- Required meta tags -->
-    <meta charset="utf-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1">
-    <!-- Bootstrap CSS -->
-    <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet"
-        integrity="sha384-eOJMYsd53ii+scO/bJGFsiCZc+5NDVN2yr8+0RDqr0Ql0h+rP48ckxlpbzKgwra6" crossorigin="anonymous">
-    <!-- Custom Styles -->
-    <style type="text/css">
-        body {
-            background-image: url(static/bt.png);
-            background-position: center;
-            background-size: cover;
-            font-family: 'Roboto', sans-serif;
-            margin-top: 40px;
-            color: #fff;
-        }
-        .navbar {
-            background-color: #212121 !important;
-        }
-        .navbar-brand {
-            font-weight: bold;
-            font-size: 1.5rem;
-        }
-        .regform {
-            background-color: rgba(0, 0, 0, 0.6);
-            padding: 20px;
-            text-align: center;
-            border-radius: 15px 15px 0 0;
-            box-shadow: 0 10px 15px rgba(0, 0, 0, 0.5);
-            margin-top: 20px;
-        }
-        .regform h1 {
-            font-size: 2rem;
-            font-weight: bold;
-        }
-        .main-form {
-            background-color: rgba(0, 0, 0, 0.7);
-            margin: 20px auto;
-            padding: 30px;
-            border-radius: 10px;
-            max-width: 900px;
-        }
-        .form-group label {
-            font-size: 1rem;
-            font-weight: 500;
-        }
-        .form-control {
-            border-radius: 5px;
-            box-shadow: none;
-            border: 2px solid #bbb;
-            margin-bottom: 15px;
-        }
-        .form-control:focus {
-            border-color: #5cb85c;
-        }
-        .btn-submit {
-            background-color: #28a745;
-            color: white;
-            font-size: 1.1rem;
-            padding: 15px 30px;
-            border-radius: 5px;
-            border: none;
-            transition: background-color 0.3s ease;
-        }
-        .btn-submit:hover {
-            background-color: #218838;
-        }
-        .form-text {
-            font-size: 0.85rem;
-        }
-        .col-md-6 {
-            margin-bottom: 15px;
-        }
-        .col-md-6 label,
-        .col-md-6 input,
-        .col-md-6 select {
-            font-size: 1rem;
-        }
-        .footer {
-            text-align: center;
-            margin-top: 30px;
-            font-size: 0.9rem;
-            color: #ccc;
-        }
-        /* Responsive design */
-        @media (max-width: 767px) {
-            .regform h1 {
-                font-size: 1.6rem;
             }
-            .main-form {
-                padding: 20px;
-            }
-        }
-    </style>
-    <title>Brain Tumor Detection</title>
-</head>
-<body>
-    <nav class="navbar navbar-expand-lg navbar-dark bg-dark">
-        <div class="container-fluid">
-            <a class="navbar-brand" href="/">CNN Brain Tumor Detection</a>
-            <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarNav"
-                aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
-                <span class="navbar-toggler-icon"></span>
-            </button>
-            <div class="collapse navbar-collapse" id="navbarNav">
-                <ul class="navbar-nav ms-auto">
-                    <li class="nav-item">
-                        <a class="nav-link" href="/dbresults">View MongoDB Results</a>
-                    </li>
-                </ul>
-            </div>
-        </div>
-    </nav>
-    <div class="regform">
-        <h1>Brain Tumor Detection Form</h1>
-    </div>
-    <div class="container">
-        <form action="resultbt" class="main-form needs-validation" method="POST" enctype="multipart/form-data" novalidate>
-            <div class="row">
-                <div class="col-md-6">
-                    <div class="form-group">
-                        <label for="firstname">First Name</label>
-                        <input type="text" name="firstname" id="firstname" class="form-control" required>
-                    </div>
-                </div>
-                <div class="col-md-6">
-                    <div class="form-group">
-                        <label for="lastname">Last Name</label>
-                        <input type="text" name="lastname" id="lastname" class="form-control" required>
-                    </div>
-                </div>
-            </div>
-            <div class="form-group">
-                <label for="phone">Phone Number</label>
-                <input type="tel" name="phone" id="phone" class="form-control" required>
-                <small class="form-text">* Include your area code</small>
-            </div>
-            <div class="form-group">
-                <label for="email">Email Address</label>
-                <input type="email" name="email" id="email" class="form-control" required>
-            </div>
-            <div class="row">
-                <div class="col-md-6">
-                    <div class="form-group">
-                        <label for="gender">Gender</label>
-                        <select name="gender" id="gender" class="form-control" required>
-                            <option value="male">Male</option>
-                            <option value="female">Female</option>
-                        </select>
-                    </div>
-                </div>
-                <div class="col-md-6">
-                    <div class="form-group">
-                        <label for="age">Age</label>
-                        <input type="number" name="age" id="age" class="form-control" required>
-                    </div>
-                </div>
-            </div>
-            <div class="form-group">
-                <label for="file">Upload Your Brain MRI</label>
-                <input type="file" class="form-control" id="file" name="file" required>
-            </div>
-            <div class="text-center">
-                <button type="submit" class="btn-submit">Submit</button>
-            </div>
-        </form>
-    </div>
-    <div class="footer">
-        <p>&copy; 2024 Brain Tumor Detection - All Rights Reserved</p>
-    </div>
-    <!-- Bootstrap Bundle with Popper -->
-    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js"
-        integrity="sha384-JEW9xMcG8R+pH31jmWH6WWP0WintQrMb4s7ZOdauHnUtxwoG2vI5DkLtS3qm9Ekf"
-        crossorigin="anonymous"></script>
-    <!-- Enable Bootstrap validation -->
-    <script>
-        (function () {
-            'use strict'
-            // Fetch all the forms we want to apply custom Bootstrap validation styles to
-            var forms = document.querySelectorAll('.needs-validation')
-            // Loop over them and prevent submission
-            Array.prototype.slice.call(forms)
-                .forEach(function (form) {
-                    form.addEventListener('submit', function (event) {
-                        if (!form.checkValidity()) {
-                            event.preventDefault()
-                            event.stopPropagation()
-                        }
-                        form.classList.add('was-validated')
-                    }, false)
-                })
-        })()
-    </script>
-</body>
-</html>

+from flask import Flask, flash, request, redirect, render_template
+import os
+import cv2
+import imutils
+import numpy as np
+from tensorflow.keras.models import load_model
+from werkzeug.utils import secure_filename
+import tempfile
+from pymongo import MongoClient
+from datetime import datetime
+# Load the Brain Tumor CNN Model
+braintumor_model = load_model('models/braintumor.h5')
+# Configuring Flask application
+app = Flask(__name__)
+app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 0  # Disable caching for images
+app.secret_key = "nielitchandigarhpunjabpolice"  # Secret key for session management
+# Allowed image file extensions
+ALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg'])
+# Connect to MongoDB Atlas
+client = MongoClient("mongodb+srv://test:test@cluster0.sxci1.mongodb.net/?retryWrites=true&w=majority")
+db = client['brain_tumor_detection']  # Database name
+collection = db['predictions']  # Collection name
+def allowed_file(filename):
+    """Check if the file is a valid image format (png, jpg, jpeg)."""
+    return '.' in filename and filename.rsplit('.', 1)[1] in ALLOWED_EXTENSIONS
+def preprocess_imgs(set_name, img_size):
+    """
+    Preprocess images by resizing them to the target size (224x224 for VGG16)
+    and applying appropriate resizing techniques.
+    """
+    set_new = []
+    for img in set_name:
+        img = cv2.resize(img, dsize=img_size, interpolation=cv2.INTER_CUBIC)  # Resize image
+        set_new.append(img)
+    return np.array(set_new)
+def crop_imgs(set_name, add_pixels_value=0):
+    """
+    Crop the region of interest (ROI) in the image for brain tumor detection.
+    """
+    set_new = []
+    for img in set_name:
+        gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+        gray = cv2.GaussianBlur(gray, (5, 5), 0)
+        thresh = cv2.threshold(gray, 45, 255, cv2.THRESH_BINARY)[1]
+        thresh = cv2.erode(thresh, None, iterations=2)
+        thresh = cv2.dilate(thresh, None, iterations=2)
+        cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        cnts = imutils.grab_contours(cnts)
+        c = max(cnts, key=cv2.contourArea)
+        extLeft = tuple(c[c[:, :, 0].argmin()][0])
+        extRight = tuple(c[c[:, :, 0].argmax()][0])
+        extTop = tuple(c[c[:, :, 1].argmin()][0])
+        extBot = tuple(c[c[:, :, 1].argmax()][0])
+        ADD_PIXELS = add_pixels_value
+        new_img = img[extTop[1]-ADD_PIXELS:extBot[1]+ADD_PIXELS,
+                      extLeft[0]-ADD_PIXELS:extRight[0]+ADD_PIXELS].copy()
+        set_new.append(new_img)
+    return np.array(set_new)
+@app.route('/')
+def brain_tumor():
+    """Render the HTML form for the user to upload an image."""
+    return render_template('braintumor.html')
+@app.route('/resultbt', methods=['POST'])
+def resultbt():
+    """Process the uploaded image and save prediction results to MongoDB."""
+    if request.method == 'POST':
+        firstname = request.form['firstname']
+        lastname = request.form['lastname']
+        email = request.form['email']
+        phone = request.form['phone']
+        gender = request.form['gender']
+        age = request.form['age']
+        file = request.files['file']
+        if file and allowed_file(file.filename):
+            temp_file = tempfile.NamedTemporaryFile(delete=False)
+            filename = secure_filename(file.filename)
+            file.save(temp_file.name)
+            flash('Image successfully uploaded and displayed below')
+            # Process the image
+            img = cv2.imread(temp_file.name)
+            img = crop_imgs([img])
+            img = img.reshape(img.shape[1:])
+            img = preprocess_imgs([img], (224, 224))
+            # Make prediction
+            pred = braintumor_model.predict(img)
+            prediction = 'Tumor Detected' if pred[0][0] >= 0.5 else 'No Tumor Detected'
+            confidence_score = float(pred[0][0])
+            # Prepare data for MongoDB
+            result = {
+                "firstname": firstname,
+                "lastname": lastname,
+                "email": email,
+                "phone": phone,
+                "gender": gender,
+                "age": age,
+                "image_name": filename,
+                "prediction": prediction,
+                "confidence_score": confidence_score,
+                "timestamp": datetime.utcnow()
             }
+            # Insert data into MongoDB
+            collection.insert_one(result)
+            # Return the result to the user
+            return render_template('resultbt.html', filename=filename, fn=firstname, ln=lastname, age=age, r=prediction, gender=gender)
+        else:
+            flash('Allowed image types are - png, jpg, jpeg')
+            return redirect(request.url)
+@app.route('/dbresults')
+def dbresults():
+    """Fetch all results from MongoDB and render them in a template."""
+    # Fetch all documents from the MongoDB collection
+    all_results = collection.find()  # Returns a cursor
+    # Convert cursor to a list of dictionaries
+    results_list = []
+    for result in all_results:
+        result['_id'] = str(result['_id'])  # Convert ObjectId to string for JSON serialization
+        results_list.append(result)
+    # Pass the results to the HTML template
+    return render_template('dbresults.html', results=results_list)
+if __name__ == '__main__':
+    app.run(debug=True) it is saving oposite in database when user had tumor its saving no tumor and vise versa