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+version https://git-lfs.github.com/spec/v1
+oid sha256:1c62d3a897c351b45bab8ee31d415da79d673e3ebb81f136c1ea3473ae5442d0
+size 2453704
diff --git a/MODELS/sports equipment model/keras_model.h5 b/MODELS/sports equipment model/keras_model.h5
new file mode 100644
index 0000000000000000000000000000000000000000..430b15da0da9be299c368986efd1cad3adb02d04
--- /dev/null
+++ b/MODELS/sports equipment model/keras_model.h5	
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6fbbc961fc700790c95ef0e346432efadbb1652b9a11cd2d81071e882393ce35
+size 2453440
diff --git a/MODELS/sports equipment model/labels.txt b/MODELS/sports equipment model/labels.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8b6a4c94604c38f107c983138ddf1e7c8d2be2d1
--- /dev/null
+++ b/MODELS/sports equipment model/labels.txt	
@@ -0,0 +1,2 @@
+0 Sports Equipment
+1 not Sports Equipment
diff --git a/MODELS/tpo model/keras_model.h5 b/MODELS/tpo model/keras_model.h5
new file mode 100644
index 0000000000000000000000000000000000000000..4020626fd2ad10de3a2811012f44caf0166269e5
--- /dev/null
+++ b/MODELS/tpo model/keras_model.h5	
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08101bd29f74eb5fa518a582293a122fde788d370d8369b52b54ba62f344af96
+size 2453440
diff --git a/MODELS/tpo model/labels.txt b/MODELS/tpo model/labels.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f716dd56946ec0883db8e250135692b74c45731f
--- /dev/null
+++ b/MODELS/tpo model/labels.txt	
@@ -0,0 +1,2 @@
+0 TPO
+1 Not TPO
diff --git a/app.py b/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..f1576f8aac51bd58a9fe5b79dae84f7f1fd64511
--- /dev/null
+++ b/app.py
@@ -0,0 +1,472 @@
+from flask import Flask, render_template, request, jsonify
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
+import PyPDF2
+from keras.models import load_model
+from PIL import Image, ImageOps
+import numpy as np
+import pandas as pd
+from inference_sdk import InferenceHTTPClient
+import cv2
+import base64
+import io
+from flask import send_file
+from reportlab.pdfgen import canvas
+from io import BytesIO
+
+EXCEL_FILE = "Book2.xlsx"
+
+# Initialize the Roboflow clients for different models
+CLIENTS = {
+    'classroom': InferenceHTTPClient(
+        api_url="https://detect.roboflow.com",
+        api_key="bNLTnCBq5hIm7R0O3hU4"
+    ),
+    'chemical_lab': InferenceHTTPClient(
+        api_url="https://detect.roboflow.com",
+        api_key="bNLTnCBq5hIm7R0O3hU4"
+    ),
+    'mechanical_workshop': InferenceHTTPClient(
+        api_url="https://detect.roboflow.com",
+        api_key="bNLTnCBq5hIm7R0O3hU4"
+    ),
+    'computer_lab': InferenceHTTPClient(
+        api_url="https://detect.roboflow.com",
+        api_key="bNLTnCBq5hIm7R0O3hU4"
+    ),
+    'cctv' :InferenceHTTPClient(
+    api_url="https://detect.roboflow.com",
+    api_key="bNLTnCBq5hIm7R0O3hU4"
+),
+    'notice_board' :InferenceHTTPClient(
+    api_url="https://detect.roboflow.com",
+    api_key="bNLTnCBq5hIm7R0O3hU4"
+    ),
+    'bench': InferenceHTTPClient(
+        api_url="https://detect.roboflow.com",
+        api_key="IkQtIl5NGRTc0llwyIMo"
+    )
+
+}
+# Model IDs for each environment
+MODEL_IDS = {
+    'classroom': "sih-object-detection/1",
+    'chemical_lab': "chem-dz924/1",
+    'mechanical_workshop': "mech-npugl/1",
+    'computer_lab': "sih-object-detection/1",
+    'cctv' : "bench-bcvxh/2",
+    'notice_board' : "cctv-cofid/2",
+    'bench' : "bench-bcvxh/2",
+}
+app = Flask(__name__)
+app.secret_key = 'super_secret_key'
+
+# Configuration
+app.config['UPLOAD_FOLDER'] = os.path.abspath('uploads/')
+os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
+
+FACILITIES = [
+    # Essential Academic and Safety Facilities
+    "Classroom model",
+    "Library model",
+    "Computer lab model",
+    "elearning model",
+
+    "Drawing Halls model",
+    "Fire extinguisher model",
+
+    # Faculty and Administrative Needs
+    "Faculty cabin model",
+    "Server Room model",
+    "TPO model",
+
+    # Recreational and Co-curricular Support
+    "Ground model",
+    "Sports equipment model",
+    "Workshop model",
+    "Seminar hall model",
+    "Conference Halls model",
+
+    # Comfort and Utility Facilities
+    "Canteen model",
+
+    "Medical Room Model",
+    "Parking model",
+
+    # Backup and Miscellaneous
+    "Generator model",
+    "Audi model",
+
+]
+
+
+# Mapping for PDFs (names might differ from model names)
+PDF_NAMES = {
+    "Audi model": "Audi.pdf",
+    "Canteen model": "Canteen.pdf",
+    "Classroom model": "Classroom.pdf",
+    "Computer lab model": "Computer Lab.pdf",
+    "Conference Halls model": "Conference Hall.pdf",
+    "Drawing Halls model": "Drawing Halls.pdf",
+    "Faculty cabin model": "Faculty Cabin.pdf",
+    "Fire extinguisher model": "Fire Extinguishers.pdf",
+    "Generator model": "Generator.pdf",
+    "Ground model": "Grounds.pdf",
+    "Library model": "Library.pdf",
+    "Medical Room Model": "Medical Room.pdf",
+    "Parking model": "Parking.pdf",
+    "Restroom Model": "Restroom.pdf",
+    "Seminar hall model": "Seminar Hall.pdf",
+    "Server Room model": "Server Room.pdf",
+    "Sports equipment model": "Sports Equipment.pdf",
+    "TPO model": "TPO (Training and Placement Office).pdf",
+    "Workshop model": "Workshop.pdf",
+    "elearning model": "elearning.pdf",
+}
+
+# Paths
+MODEL_PATHS = {
+    facility: {
+        "model": f"MODELS/{facility}/keras_model.h5",
+        "labels": f"MODELS/{facility}/labels.txt",
+    }
+    for facility in FACILITIES
+}
+
+PDF_PATHS = {
+    facility: f"pdfs/{PDF_NAMES[facility]}"
+    for facility in FACILITIES
+}
+
+# Routes
+@app.route('/')
+def index():
+    # Extract questions from PDFs for each facility
+    questions = {facility: extract_questions(PDF_PATHS.get(facility, "")) for facility in FACILITIES}
+    return render_template('index.html', facilities=FACILITIES, questions=questions)
+
+
+@app.route('/calculate', methods=['POST'])
+def calculate():
+    data = request.json
+    num_students = int(data.get('num_students', 0))
+    num_divisions = int(data.get('num_divisions', 0))
+    num_courses = int(data.get('num_courses', 0))
+    course_duration = int(data.get('course_duration', 0))
+
+    calculated_facilities = calculate_required_facilities(num_students, num_divisions, num_courses, course_duration)
+    return jsonify(calculated_facilities)
+
+
+
+
+@app.route('/upload/<facility>', methods=['POST'])
+def upload(facility):
+    facility = facility.strip()
+
+    # Check if facility exists in MODEL_PATHS
+    normalized_facility = next(
+        (key for key in MODEL_PATHS if key.lower() == facility.lower()), None
+    )
+    if not normalized_facility:
+        return jsonify({"error": f"Facility '{facility}' not found in MODEL_PATHS"}), 400
+
+    if 'images' not in request.files:
+        return jsonify({"error": "No files uploaded"}), 400
+
+    files = request.files.getlist('images')
+    if not files:
+        return jsonify({"error": "No files selected"}), 400
+
+    results = []
+    for file in files:
+        try:
+            filepath = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
+            file.save(filepath)
+
+            # Perform verification using the model
+            model_path = MODEL_PATHS[normalized_facility]["model"]
+            labels_path = MODEL_PATHS[normalized_facility]["labels"]
+
+            result = verify_image(filepath, model_path, labels_path)
+            result["file_name"] = file.filename
+            result["facility"] = normalized_facility
+
+            # Log to Excel if verified
+            if result["confidence"] >= 0.8:
+                log_to_excel(result)
+
+            results.append(result)
+
+        except Exception as e:
+            print(f"Error during file upload: {e}")
+            results.append({"error": str(e), "file": file.filename})
+
+    return jsonify(results)
+
+def log_to_excel(data):
+    """
+    Logs verified image data to an Excel file.
+    :param data: Dictionary containing facility, file name, label, and confidence score.
+    """
+    # Prepare a DataFrame row
+    row = {
+        "Facility": data["facility"],
+        "Name of Image": data["file_name"],
+        "Class of Prediction": data["label"],
+        "Confidence Score": data["confidence"]
+    }
+
+    # Convert row to DataFrame
+    df_row = pd.DataFrame([row])
+
+    # If the file exists, append; otherwise, create a new file
+    if os.path.exists(EXCEL_FILE):
+        df_existing = pd.read_excel(EXCEL_FILE)
+        df_updated = pd.concat([df_existing, df_row], ignore_index=True)
+        df_updated.to_excel(EXCEL_FILE, index=False)
+    else:
+        df_row.to_excel(EXCEL_FILE, index=False)
+
+
+
+@app.route('/submit_answers', methods=['POST'])
+def submit_answers():
+    data = request.json
+    # Process submitted answers (if needed, save or process them)
+    return jsonify({"message": "Answers submitted successfully!"})
+
+
+# Utility Functions
+def calculate_required_facilities(num_students, num_divisions, num_courses, course_duration):
+    """
+    Calculate required facilities based on student population and institutional parameters.
+
+    Args:
+    - num_students: Total number of students
+    - num_divisions: Number of student divisions
+    - num_courses: Number of courses
+    - course_duration: Duration of courses
+
+    Returns:
+    - Dictionary of required facilities with their quantities
+    """
+    results = {
+        # Classroom Calculation: Based on divisions, course duration, and utilization
+        "Classroom model": max(1, int(num_divisions * course_duration * 0.5)),
+        # Computer Lab Calculation: Considering courses, student density
+        "Computer lab model": max(1, int((num_courses * course_duration + num_students / 400) * 0.75)),
+        # Facilities typically singular in a college
+        "Audi model": 1,  # One main auditorium
+        "TPO model": 1,  # One Training and Placement Office
+        "Medical Room Model": 1,  # One central medical room
+        "Server Room model": 1,  # One central server room
+        "Conference Halls model": 1,  # One main conference hall
+        "Seminar hall model": 1,  # One primary seminar hall
+        # Facilities with more variable allocation
+        "Workshop model": max(1, num_students // 600),
+        "Sports equipment model": 1,
+        # Canteen Calculation: Scaled with student population
+        "Canteen model": 1,
+        # Additional facilities with minimum allocation
+        "Drawing Halls model": 1,
+        "Faculty cabin model": max(1, num_students//20),
+        "Fire extinguisher model": max(1, num_divisions)+20,
+        "Generator model": 1,
+        "Ground model": 1,
+        "Library model": 1,  # Typically one main library
+        "Parking model": 1,
+        "Restroom Model": max(2, num_students // 500),
+    }
+
+    return results
+
+def verify_image(image_path, model_path, labels_path):
+    try:
+        print(f"Loading model from: {model_path}")
+        model = load_model(model_path)
+    except Exception as e:
+        print(f"Error loading model: {e}")
+        raise
+
+    try:
+        with open(labels_path, 'r') as f:
+            labels = [line.strip() for line in f.readlines()]
+        print(f"Labels loaded: {labels}")
+    except Exception as e:
+        print(f"Error loading labels: {e}")
+        raise
+
+    try:
+        image = Image.open(image_path).convert('RGB')
+        image = ImageOps.fit(image, (224, 224), Image.Resampling.LANCZOS)
+        image_array = np.asarray(image)
+        normalized_image_array = (image_array.astype(np.float32) / 127.5) - 1
+        data = np.expand_dims(normalized_image_array, axis=0)
+
+        print("Running prediction...")
+        prediction = model.predict(data)
+        index = np.argmax(prediction)
+        confidence_score = prediction[0][index]
+
+        # Convert numpy.float32 to Python float for JSON serialization
+        return {"label": labels[index], "confidence": float(confidence_score)}
+    except Exception as e:
+        print(f"Error during prediction: {e}")
+        raise
+
+
+def extract_questions(pdf_path):
+    """Extracts questions from a given PDF file."""
+    if not os.path.exists(pdf_path):
+        return []
+
+    questions = []
+    try:
+        with open(pdf_path, 'rb') as pdf_file:
+            reader = PyPDF2.PdfReader(pdf_file)
+            for page in reader.pages:
+                text = page.extract_text()
+                # Extract lines ending with "?" (assuming questions end with "?")
+                questions.extend([line.strip() for line in text.split('\n') if line.strip().endswith('?')])
+    except Exception as e:
+        print(f"Error extracting questions from {pdf_path}: {e}")
+
+    return questions
+
+
+def process_single_image(file, environment):
+    """Helper function to process a single image"""
+    if file.filename == '':
+        raise ValueError('No selected file')
+
+    # Validate file type
+    allowed_extensions = {'png', 'jpg', 'jpeg'}
+    if not file.filename.lower().endswith(tuple(allowed_extensions)):
+        raise ValueError('Invalid file type. Please upload a PNG or JPEG image.')
+
+    # Read and process image
+    image_bytes = file.read()
+    img = Image.open(io.BytesIO(image_bytes))
+    if img.mode == 'RGBA':
+        img = img.convert('RGB')
+
+    # Save image temporarily
+    temp_path = f"temp_image_{environment}.jpg"
+    img.save(temp_path)
+
+    # Keep a copy for drawing
+    img_draw = np.array(img)
+    img_draw = cv2.cvtColor(img_draw, cv2.COLOR_RGB2BGR)
+
+    # Perform detection
+    results = CLIENTS[environment].infer(temp_path, model_id=MODEL_IDS[environment])
+    detections = []
+
+    # Process results
+    for i, prediction in enumerate(results.get('predictions', [])):
+        x1 = int(prediction['x'] - prediction['width'] / 2)
+        y1 = int(prediction['y'] - prediction['height'] / 2)
+        x2 = int(prediction['x'] + prediction['width'] / 2)
+        y2 = int(prediction['y'] + prediction['height'] / 2)
+
+        class_name = prediction['class']
+        confidence = prediction['confidence']
+
+        detections.append({
+            'bbox': [x1, y1, x2, y2],
+            'class': class_name,
+            'confidence': round(confidence, 2),
+            'id': f'{environment}-detection-{i}'
+        })
+
+        # Draw bounding box
+        cv2.rectangle(img_draw, (x1, y1), (x2, y2), (0, 255, 0), 1)
+        cv2.putText(img_draw, f'{class_name} {confidence:.2f}', (x1, y1 - 10),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)
+
+    # Clean up temporary file
+    if os.path.exists(temp_path):
+        os.remove(temp_path)
+
+    # Convert the image to base64
+    _, buffer = cv2.imencode('.jpg', img_draw)
+    img_str = base64.b64encode(buffer).decode()
+
+    return {
+        'image': f'data:image/jpeg;base64,{img_str}',
+        'detections': detections
+    }
+
+
+@app.route('/detect', methods=['POST'])
+def detect():
+    try:
+        required_environments = ['classroom', 'chemical_lab', 'mechanical_workshop', 
+                               'computer_lab', 'cctv', 'notice_board', 'bench']
+        results = {}
+
+        # Check if all required images are provided
+        for env in required_environments:
+            if f'image_{env}' not in request.files:
+                return jsonify({
+                    'success': False,
+                    'error': f'No image file provided for {env}'
+                }), 400
+
+        # Process each image
+        for env in required_environments:
+            try:
+                file = request.files[f'image_{env}']
+                results[env] = process_single_image(file, env)
+            except Exception as e:
+                return jsonify({
+                    'success': False,
+                    'error': f'Error processing {env} image: {str(e)}'
+                }), 400
+
+        return jsonify({
+            'success': True,
+            'results': results
+        })
+
+    except Exception as e:
+        app.logger.error(f"Error in detect route: {str(e)}")
+        return jsonify({
+            'success': False,
+            'error': f'Server error: {str(e)}'
+        }), 500
+
+@app.route('/download_report', methods=['GET'])
+def download_report():
+    # Generate PDF report
+    buffer = BytesIO()
+    pdf = canvas.Canvas(buffer)
+
+    # Write content to PDF (example content)
+    pdf.drawString(100, 800, "Facility Management System Report")
+    pdf.drawString(100, 780, "This is an auto-generated report.")
+
+    # Sample table (adjust as per your needs)
+    y = 750
+    for facility in FACILITIES:
+        pdf.drawString(100, y, f"Facility: {facility}")
+        y -= 20  # Move to next line
+
+    pdf.save()
+    buffer.seek(0)
+
+    return send_file(buffer, as_attachment=True, download_name="facility_report.pdf", mimetype='application/pdf')
+
+
+@app.route('/download_excel', methods=['GET'])
+def download_excel():
+    if os.path.exists(EXCEL_FILE):
+        return send_file(EXCEL_FILE, as_attachment=True, download_name="facility_data.xlsx",
+                         mimetype='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet')
+    else:
+        return jsonify({"error": "Excel file not found"}), 404
+
+
+if __name__ == '__main__':
+    app.run(debug=True)
diff --git a/download.jpeg b/download.jpeg
new file mode 100644
index 0000000000000000000000000000000000000000..078b050efd2abf53d5e1f393ec86476bd94b1957
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diff --git a/main.py b/main.py
new file mode 100644
index 0000000000000000000000000000000000000000..9d2246334b34b5fd9b999714fa465586dc4766d7
--- /dev/null
+++ b/main.py
@@ -0,0 +1,10 @@
+import os
+from flask import Flask
+
+app = Flask(__name__)
+
+# Get the secret key from the environment variable, or use a default for development
+app.secret_key = os.getenv('FLASK_SECRET_KEY', os.urandom(24))
+
+# Print the secret key for debugging purposes (not recommended in production)
+print("Secret Key:", app.secret_key)
diff --git a/pdfs/Audi.pdf b/pdfs/Audi.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..68cae41efaf3ce4cb3478188ef836f8335b6a1e9
--- /dev/null
+++ b/pdfs/Audi.pdf
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diff --git a/pdfs/Canteen.pdf b/pdfs/Canteen.pdf
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diff --git a/pdfs/Classroom.pdf b/pdfs/Classroom.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..81fbdb70f6a872827fcd5a34c9797ed932ba970b
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+version https://git-lfs.github.com/spec/v1
+oid sha256:931d964f2434988751bd6b72725997892d5e5c9dd9a3722bb30140b37d3176fd
+size 921299
diff --git a/requirements.txt b/requirements.txt
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+Flask==2.2.3
+Werkzeug==2.2.3
+keras==2.14.0
+numpy==1.23.4
+Pillow==9.4.0
+cvzone==1.5.2
diff --git a/roufgh b/roufgh
new file mode 100644
index 0000000000000000000000000000000000000000..f88611eaa301ccf5bd9ad0bd608e2fffd0b6b916
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+FACILITIES = [
+    {
+        "name": "Audi",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\audi model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\audi model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Audi.pdf"
+    },
+    {
+        "name": "Canteen",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\canteen model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\canteen model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Canteen.pdf"
+    },
+    {
+        "name": "Classroom",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\classroom model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\classroom model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Classroom.pdf"
+    },
+    {
+        "name": "Computer Lab",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\computer lab model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\computer lab model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Computer Lab.pdf"
+    },
+    {
+        "name": "Conference Hall",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\conference hall model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\conference hall model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Conference Hall.pdf"
+    },
+    {
+        "name": "Drawing Halls",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\drawing halls model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\drawing halls model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Drawing Halls.pdf"
+    },
+    {
+        "name": "Faculty Cabin",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\faculty cabin model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\faculty cabin model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Faculty Cabin.pdf"
+    },
+    {
+        "name": "Fire Extinguishers",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\fire extinguishers model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\fire extinguishers model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Fire Extinguishers.pdf"
+    },
+    {
+        "name": "Generator",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\generator model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\generator model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Generator.pdf"
+    },
+    {
+        "name": "Grounds",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\grounds model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\grounds model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Grounds.pdf"
+    },
+    {
+        "name": "Library",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\library model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\library model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Library.pdf"
+    },
+    {
+        "name": "Medical Room",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\medical room model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\medical room model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Medical Room.pdf"
+    },
+    {
+        "name": "Parking",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\parking model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\parking model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Parking.pdf"
+    },
+    {
+        "name": "Pothole Management",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\pothole management model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\pothole management model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Pothole Management.pdf"
+    },
+    {
+        "name": "Restroom",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\restroom model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\restroom model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Restroom.pdf"
+    },
+    {
+        "name": "Seminar Hall",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\seminar hall model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\seminar hall model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Seminar Hall.pdf"
+    },
+    {
+        "name": "Server Room",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\server room model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\server room model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Server Room.pdf"
+    },
+    {
+        "name": "Sports Equipment",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\sports equipment model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\sports equipment model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Sports Equipment.pdf"
+    },
+    {
+        "name": "TPO (Training and Placement Office)",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\tpo model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\tpo model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\TPO (Training and Placement Office).pdf"
+    },
+    {
+        "name": "Workshop",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\workshop model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\workshop model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Workshop.pdf"
+    }
+]
diff --git a/roufgh2 b/roufgh2
new file mode 100644
index 0000000000000000000000000000000000000000..80dd57337b4797c1e08fcb737dfb06d3719dcbee
--- /dev/null
+++ b/roufgh2
@@ -0,0 +1,298 @@
+from flask import Flask, render_template, request, flash
+import os
+from werkzeug.utils import secure_filename
+from keras.models import load_model
+from keras.layers import DepthwiseConv2D
+from PIL import Image, ImageOps
+import numpy as np
+
+app = Flask(__name__)
+app.secret_key = 'secret-key'
+
+UPLOAD_FOLDER = os.path.abspath('uploads/')
+app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+FACILITIES = [
+    {
+        "name": "Audi",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\audi model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\audi model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Audi.pdf"
+    },
+    {
+        "name": "Canteen",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\canteen model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\canteen model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Canteen.pdf"
+    },
+    {
+        "name": "Classroom",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\classroom model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\classroom model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Classroom.pdf"
+    },
+    {
+        "name": "Computer Lab",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\computer lab model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\computer lab model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Computer Lab.pdf"
+    },
+    {
+        "name": "Conference Hall",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\conference hall model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\conference hall model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Conference Hall.pdf"
+    },
+    {
+        "name": "Drawing Halls",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\drawing halls model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\drawing halls model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Drawing Halls.pdf"
+    },
+    {
+        "name": "Faculty Cabin",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\faculty cabin model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\faculty cabin model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Faculty Cabin.pdf"
+    },
+    {
+        "name": "Fire Extinguishers",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\fire extinguishers model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\fire extinguishers model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Fire Extinguishers.pdf"
+    },
+    {
+        "name": "Generator",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\generator model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\generator model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Generator.pdf"
+    },
+    {
+        "name": "Grounds",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\grounds model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\grounds model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Grounds.pdf"
+    },
+    {
+        "name": "Library",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\library model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\library model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Library.pdf"
+    },
+    {
+        "name": "Medical Room",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\medical room model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\medical room model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Medical Room.pdf"
+    },
+    {
+        "name": "Parking",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\parking model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\parking model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Parking.pdf"
+    },
+    {
+        "name": "Pothole Management",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\pothole management model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\pothole management model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Pothole Management.pdf"
+    },
+    {
+        "name": "Restroom",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\restroom model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\restroom model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Restroom.pdf"
+    },
+    {
+        "name": "Seminar Hall",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\seminar hall model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\seminar hall model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Seminar Hall.pdf"
+    },
+    {
+        "name": "Server Room",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\server room model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\server room model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Server Room.pdf"
+    },
+    {
+        "name": "Sports Equipment",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\sports equipment model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\sports equipment model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Sports Equipment.pdf"
+    },
+    {
+        "name": "TPO (Training and Placement Office)",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\tpo model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\tpo model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\TPO (Training and Placement Office).pdf"
+    },
+    {
+        "name": "Workshop",
+        "type": "image_processing",
+        "model": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\workshop model\keras_model.h5",
+        "labels": r"C:\Users\Pranit\PycharmProjects\infrastructure\MODELS\workshop model\labels.txt",
+        "pdf": r"C:\Users\Pranit\PycharmProjects\infrastructure\pdfs\Workshop.pdf"
+    }
+]
+
+def calculate_required_facilities(num_students, num_divisions, num_courses, course_duration):
+    # 1. Classrooms Required
+    classrooms_required = num_divisions * course_duration * 0.5
+
+    # 2. Total Labs Required
+    base_labs = 2 * num_courses * course_duration
+    if num_students > 180 * num_courses:
+        extra_students_per_course = (num_students - (180 * num_courses)) // 50
+        base_labs += extra_students_per_course
+    additional_labs = (num_students - 600) // 150 if num_students > 600 else 0
+    total_labs = base_labs + additional_labs
+
+    # 3. Workshops Required
+    workshops_required = 1 if num_students <= 600 else 1 + (num_students - 600) // 600
+
+    # 4. CAD Centres Required
+    cad_centres_required = 1 if num_students <= 600 else 1 + (num_students - 600) // 600
+
+    # 5. Computer Centres Required
+    computer_centres_required = 1 if num_students <= 600 else 1 + (num_students - 600) // 600
+
+    # 6. Seminar Halls Required
+    seminar_halls_required = 1
+
+    # 7. Library Required
+    library_required = 1
+
+    # 8. Language Labs Required
+    language_labs_required = 1
+
+    # 9. PCs/Laptops Required
+    pcs_laptops_required = max(20, num_students // 10)
+
+    # 10. Additional Facilities (Single Requirement)
+    auditorium_required = 1
+    faculty_cabins_required = 1
+    medical_room_required = 1
+    sports_facilities_required = 1
+    canteen_required = 1
+    generator_required = 1
+    bicycle_stand_required = 1
+    bus_transport_required = 1
+
+    # 11. Other Derived Formulas
+    dispensers_required = 1
+    fire_extinguishers_required = 1
+    grounds_required = 1
+    parking_areas_required = 1
+    road_condition_check = 1
+
+    # Returning the required facilities as a dictionary
+    return {
+        "classrooms_required": int(classrooms_required),
+        "labs_required": int(total_labs),
+        "workshops_required": int(workshops_required),
+        "cad_centres_required": int(cad_centres_required),
+        "computer_centres_required": int(computer_centres_required),
+        "seminar_halls_required": int(seminar_halls_required),
+        "library_required": int(library_required),
+        "language_labs_required": int(language_labs_required),
+        "pcs_laptops_required": int(pcs_laptops_required),
+        "auditorium_required": int(auditorium_required),
+        "faculty_cabins_required": int(faculty_cabins_required),
+        "medical_room_required": int(medical_room_required),
+        "sports_facilities_required": int(sports_facilities_required),
+        "canteen_required": int(canteen_required),
+        "generator_required": int(generator_required),
+        "bicycle_stand_required": int(bicycle_stand_required),
+        "bus_transport_required": int(bus_transport_required),
+        "dispensers_required": int(dispensers_required),
+        "fire_extinguishers_required": int(fire_extinguishers_required),
+        "grounds_required": int(grounds_required),
+        "parking_areas_required": int(parking_areas_required),
+        "road_condition_check": int(road_condition_check),
+    }
+
+
+def process_image_with_model(model_path, labels_path, image_path):
+    try:
+        model = load_model(model_path, compile=False)
+        with open(labels_path, "r") as file:
+            class_names = file.readlines()
+        image = Image.open(image_path).convert("RGB")
+        image = ImageOps.fit(image, (224, 224), Image.Resampling.LANCZOS)
+        image_array = np.asarray(image).astype(np.float32) / 127.5 - 1
+        data = np.expand_dims(image_array, axis=0)
+        prediction = model.predict(data)
+        index = np.argmax(prediction)
+        class_name = class_names[index].strip()
+        confidence_score = prediction[0][index]
+        return {"class": class_name, "confidence": round(confidence_score * 100, 2)}
+    except Exception as e:
+        return {"error": f"Failed to process image. Reason: {str(e)}"}
+
+@app.route('/', methods=['GET', 'POST'])
+def home():
+    required_facilities = {}
+
+    if request.method == 'POST' and 'calculate_facilities' in request.form:
+        # Fetch inputs for calculation
+        num_students = int(request.form['num_students'])
+        num_divisions = int(request.form['num_divisions'])
+        num_courses = int(request.form['num_courses'])
+        course_duration = int(request.form['course_duration'])
+
+        # Calculate facilities
+        required_facilities = calculate_required_facilities(
+            num_students, num_divisions, num_courses, course_duration
+        )
+
+    # Handle verification for each facility
+    elif request.method == 'POST' and 'facility' in request.form:
+        selected_facility = request.form.get('facility')
+        facility = next((f for f in FACILITIES if f['name'] == selected_facility), None)
+
+        if facility:
+            files = request.files.getlist("files")
+            if files:
+                save_dir = os.path.join(app.config['UPLOAD_FOLDER'], selected_facility)
+                os.makedirs(save_dir, exist_ok=True)
+                for file in files:
+                    if file.filename == "":
+                        flash("No file selected for uploading.", "warning")
+                        continue
+                    filename = secure_filename(file.filename)
+                    file_path = os.path.join(save_dir, filename)
+                    file.save(file_path)
+                    result = process_image_with_model(facility["model"], facility["labels"], file_path)
+                    if 'error' in result:
+                        flash(result['error'], "danger")
+                    else:
+                        flash(f"{result['class']} detected with {result['confidence']}% confidence.", "success")
+
+    return render_template(
+        'index.html',
+        facilities=FACILITIES,
+        required_facilities=required_facilities
+    )
+
+if __name__ == '__main__':
+    app.run(debug=True)
diff --git a/templates/index.html b/templates/index.html
new file mode 100644
index 0000000000000000000000000000000000000000..f59702666a465bfbd5aef9f3ecae21e3e0c15ea1
--- /dev/null
+++ b/templates/index.html
@@ -0,0 +1,1306 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Facility Management System</title>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha1/dist/css/bootstrap.min.css">
+    <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
+    <style>
+        :root {
+            --primary-color: #2563eb;          /* Royal Blue */
+            --secondary-color: #4b5563;        /* Dark Gray */
+            --success-color: #059669;          /* Emerald */
+            --warning-color: #d97706;          /* Dark Amber */
+            --danger-color: #dc2626;           /* Red */
+            --background-color: #1e293b;       /* Dark Blue Gray */
+            --card-background: #334155;        /* Lighter Blue Gray */
+            --sidebar-background: #0f172a;     /* Darkest Blue */
+            --text-primary: #f8fafc;           /* Almost White */
+            --text-secondary: #cbd5e1;         /* Light Gray */
+            --input-background: #475569;       /* Medium Gray Blue */
+            --border-color: #64748b;           /* Border Gray */
+            --hover-color: #1d4ed8;            /* Darker Blue */
+            --border-radius: 0.75rem;
+        }
+    
+        body {
+            font-family: 'Inter', sans-serif;
+            background-color: var(--background-color);
+            color: var(--text-primary);
+            line-height: 1.6;
+        }
+    
+        .navbar {
+            background-color: var(--card-background);
+            box-shadow: 0 1px 3px rgba(0,0,0,0.1);
+            padding: 1rem 0;
+        }
+    
+        .navbar-brand {
+            font-weight: 700;
+            color: var(--primary-color);
+        }
+    
+        .main-container {
+            max-width: 1400px;
+            margin: 2rem auto;
+            padding: 0 1rem;
+        }
+    
+        .sidebar {
+            background-color: var(--sidebar-background);
+            border-radius: var(--border-radius);
+            padding: 1.5rem;
+            box-shadow: 0 4px 6px -1px rgba(0,0,0,0.1);
+        }
+    
+        .form-control {
+            background-color: #d2dae8;
+            color: var(--text-primary);
+            border-radius: 0.5rem;
+            border: 1px solid var(--border-color);
+            padding: 0.75rem;
+            transition: all 0.3s ease;
+        }
+    
+        .form-control:focus {
+            background-color: var(--input-background);
+            color: var(--text-primary);
+            border-color: var(--primary-color);
+            box-shadow: 0 0 0 3px rgba(37, 99, 235, 0.2);
+        }
+    
+        .btn {
+            padding: 0.75rem 1.5rem;
+            border-radius: 0.5rem;
+            font-weight: 600;
+            transition: all 0.3s ease;
+        }
+    
+        .btn-primary {
+            background-color: var(--primary-color);
+            border: none;
+        }
+    
+        .btn-primary:hover {
+            background-color: var(--hover-color);
+            transform: translateY(-1px);
+        }
+    
+        .facility-card {
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+            border: none;
+            box-shadow: 0 4px 6px -1px rgba(0,0,0,0.1);
+            margin-bottom: 1.5rem;
+            overflow: hidden;
+        }
+    
+        .facility-card .card-header {
+            background-color: var(--sidebar-background);
+            color: var(--text-primary);
+            padding: 1rem;
+            font-weight: 600;
+            border-bottom: none;
+        }
+    
+        .facility-card .card-body {
+            padding: 1.5rem;
+        }
+    
+        .upload-section {
+            background-color: var(--card-background);
+            border: 2px dashed var(--border-color);
+            border-radius: 0.5rem;
+            padding: 1.5rem;
+            text-align: center;
+            transition: all 0.3s ease;
+        }
+    
+        .upload-section:hover {
+            border-color: var(--primary-color);
+        }
+    
+        .grade-container {
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+            padding: 2rem;
+            text-align: center;
+            margin-top: 2rem;
+        }
+    
+        .grade-display {
+            font-size: 3rem;
+            font-weight: 700;
+            margin: 1rem 0;
+            color: var(--primary-color);
+        }
+    
+        .stats-card {
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+            padding: 1.5rem;
+            margin-bottom: 1rem;
+        }
+    
+        .stats-value {
+            font-size: 1.5rem;
+            font-weight: 700;
+            color: var(--primary-color);
+        }
+    
+        /* Add more modern styling for tables */
+        .table {
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+            overflow: hidden;
+            color: var(--text-primary);
+        }
+    
+        .table thead th {
+            background-color: var(--sidebar-background);
+            border-bottom: 2px solid #e2e8f0;
+            color: var(--text-secondary);
+            font-weight: 600;
+            text-transform: uppercase;
+            font-size: 0.875rem;
+            border-bottom-color: #475569;
+        }
+    
+        /* Toast notifications */
+        .toast {
+            position: fixed;
+            top: 1rem;
+            right: 1rem;
+            padding: 1rem 1.5rem;
+            border-radius: 0.5rem;
+            background-color: var(--card-background);
+            box-shadow: 0 4px 6px -1px rgba(0,0,0,0.1);
+            z-index: 1000;
+            color: var(--text-primary);
+        }
+    
+        /* Loading animation */
+        .loading-spinner {
+            width: 2.5rem;
+            height: 2.5rem;
+            border: 3px solid #f3f3f3;
+            border-top: 3px solid var(--primary-color);
+            border-radius: 50%;
+            animation: spin 1s linear infinite;
+        }
+    
+        @keyframes spin {
+            0% { transform: rotate(0deg); }
+            100% { transform: rotate(360deg); }
+        }
+
+        .container {
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+            padding: 20px;
+            margin-top: 20px;
+        }
+
+        input[type="text"], textarea {
+            background-color: #cbd5e1;
+            color: var(--text-primary);
+            border: 3px solid #141111;
+        }
+
+        button {
+            background-color: #4a4a4a;
+            color: #ffffff;
+            border: none;
+            padding: 8px 16px;
+            border-radius: 4px;
+        }
+
+        button:hover {
+            background-color: #5a5a5a;
+        }
+
+        .card {
+            background-color: var(--card-background);
+            border: 1px solid var(--border-color);
+            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.05);
+            color: var(--text-primary);
+        }
+
+        .card-header {
+            background-color: var(--sidebar-background);
+            color: white;
+            border-bottom: none;
+            font-weight: 600;
+        }
+
+        .card-body {
+            background-color: var(--card-background);
+            color: var(--text-primary);
+        }
+
+        /* Update input styles */
+        input[type="number"] {
+            background-color: var(--input-background);
+            color: var(--text-primary);
+            border-color: #475569;
+        }
+
+        input[type="number"]:focus {
+            background-color: var(--input-background);
+            color: var(--text-primary);
+            border-color: var(--primary-color);
+            box-shadow: 0 0 0 3px rgba(99, 102, 241, 0.2);
+        }
+
+        /* Update button styles to match theme */
+        button {
+            background-color: var(--primary-color);
+            color: var(--text-primary);
+            border: none;
+            padding: 8px 16px;
+            border-radius: var(--border-radius);
+            transition: all 0.3s ease;
+        }
+
+        button:hover {
+            background-color: var(--hover-color);
+            transform: translateY(-1px);
+        }
+
+        /* Update input group styling */
+        .input-group-text {
+            background-color: var(--input-background);
+            color: var(--text-secondary);
+            border: 1px solid var(--border-color);
+        }
+
+        /* Update verification result styling */
+        .uploaded-image {
+            background-color: var(--card-background);
+            border: 1px solid var(--border-color);
+            border-radius: var(--border-radius);
+            padding: 1rem;
+            margin-bottom: 1rem;
+        }
+
+        .img-thumbnail {
+            background-color: var(--input-background);
+            border-color: #475569;
+        }
+
+        /* Update form label color */
+        .form-label {
+            color: var(--text-primary);
+            font-weight: 500;
+        }
+
+        /* Add styles for grade colors with better visibility */
+        .grade-a { color: #34d399; }  /* Light Green */
+        .grade-b { color: #60a5fa; }  /* Light Blue */
+        .grade-c { color: #fbbf24; }  /* Light Yellow */
+        .grade-d { color: #fb923c; }  /* Light Orange */
+        .grade-f { color: #f87171; }  /* Light Red */
+
+        /* Update table borders */
+        .table-bordered > :not(caption) > * {
+            border-color: #475569;
+        }
+
+        .table-hover tbody tr:hover {
+            background-color: var(--input-background);
+        }
+
+        /* Add these styles for the facility cards */
+        .facility-type-cards {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
+            gap: 1.5rem;
+            margin-bottom: 2rem;
+        }
+
+        .facility-type-card {
+            background-color: var(--card-background);
+            border: 1px solid var(--border-color);
+            border-radius: var(--border-radius);
+            padding: 1.5rem;
+            transition: all 0.3s ease;
+        }
+
+        .facility-type-card:hover {
+            transform: translateY(-2px);
+            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+        }
+
+        .facility-type-card h3 {
+            color: var(--text-primary);
+            margin-bottom: 1rem;
+            font-size: 1.25rem;
+        }
+
+        .facility-type-card .icon {
+            font-size: 2rem;
+            margin-bottom: 1rem;
+            color: var(--primary-color);
+        }
+
+        .model-info {
+            color: var(--text-secondary);
+            font-size: 0.875rem;
+            margin-bottom: 1rem;
+            padding: 0.5rem;
+            background-color: var(--input-background);
+            border-radius: var(--border-radius);
+            text-align: center;
+        }
+
+        /* Add/update these styles */
+        .upload-grid {
+            display: flex;
+            flex-direction: column;
+            gap: 1.5rem;
+            width: 100%;
+            max-width: 800px;
+            margin: 0 auto;
+        }
+
+        .upload-card {
+            background-color: var(--card-background);
+            border: 1px solid var(--border-color);
+            border-radius: var(--border-radius);
+            padding: 1.5rem;
+            width: 100%;
+        }
+
+        .results-grid {
+            display: flex;
+            flex-direction: column;
+            gap: 1.5rem;
+            width: 100%;
+        }
+
+        .result-card {
+            background-color: var(--card-background);
+            border: 1px solid var(--border-color);
+            border-radius: var(--border-radius);
+            padding: 1.5rem;
+            width: 100%;
+        }
+
+        .detections-list {
+            margin-top: 1rem;
+            border: 1px solid var(--border-color);
+            border-radius: var(--border-radius);
+            overflow: hidden;
+        }
+
+        .detection-item {
+            display: flex;
+            justify-content: space-between;
+            align-items: center;
+            padding: 0.75rem 1rem;
+            border-bottom: 1px solid var(--border-color);
+        }
+
+        .detection-item:last-child {
+            border-bottom: none;
+        }
+
+        /* Add these styles for improved object detection UI */
+        .detection-section {
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+            padding: 2rem;
+            margin-bottom: 2rem;
+        }
+
+        .detection-header {
+            text-align: center;
+            margin-bottom: 2rem;
+            color: var(--text-primary);
+        }
+
+        .detection-header h2 {
+            font-size: 2rem;
+            margin-bottom: 1rem;
+        }
+
+        .upload-grid {
+            display: flex;
+            flex-direction: column;
+            gap: 2rem;
+        }
+
+        .upload-card {
+            background-color: var(--sidebar-background);
+            border: 1px solid var(--border-color);
+            border-radius: var(--border-radius);
+            padding: 2rem;
+            transition: all 0.3s ease;
+        }
+
+        .upload-card:hover {
+            transform: translateY(-2px);
+            box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
+        }
+
+        .upload-card h3 {
+            color: var(--text-primary);
+            font-size: 1.5rem;
+            margin-bottom: 1rem;
+            display: flex;
+            align-items: center;
+            gap: 0.5rem;
+        }
+
+        .upload-card h3 i {
+            color: var(--primary-color);
+        }
+
+        .custom-file-upload {
+            background-color: var(--input-background);
+            border: 2px dashed var(--border-color);
+            border-radius: var(--border-radius);
+            padding: 2rem;
+            text-align: center;
+            cursor: pointer;
+            transition: all 0.3s ease;
+            display: block;
+            margin-bottom: 1rem;
+        }
+
+        .custom-file-upload:hover {
+            border-color: var(--primary-color);
+            background-color: rgba(99, 102, 241, 0.1);
+        }
+
+        .custom-file-upload i {
+            font-size: 2rem;
+            color: var(--primary-color);
+            margin-bottom: 1rem;
+            display: block;
+        }
+
+        .detection-results {
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+            padding: 1.5rem;
+            margin-top: 2rem;
+        }
+
+        .detection-results h4 {
+            color: var(--text-primary);
+            margin-bottom: 1rem;
+            padding-bottom: 0.5rem;
+            border-bottom: 1px solid var(--border-color);
+        }
+
+        .table {
+            margin-bottom: 0;
+        }
+
+        .table thead th {
+            background-color: var(--input-background);
+            color: var(--text-primary);
+            font-weight: 600;
+            padding: 1rem;
+        }
+
+        .table tbody td {
+            padding: 1rem;
+            color: var(--text-secondary);
+        }
+
+        .confidence-badge {
+            background-color: var(--primary-color);
+            color: white;
+            padding: 0.25rem 0.75rem;
+            border-radius: 9999px;
+            font-size: 0.875rem;
+        }
+
+        #detect-all {
+            background-color: var(--primary-color);
+            color: white;
+            padding: 1rem 2rem;
+            font-size: 1.1rem;
+            font-weight: 600;
+            margin-top: 2rem;
+            transition: all 0.3s ease;
+        }
+
+        #detect-all:hover {
+            background-color: var(--hover-color);
+            transform: translateY(-2px);
+        }
+
+        .loading {
+            text-align: center;
+            padding: 2rem;
+        }
+
+        .loading-spinner {
+            margin: 0 auto 1rem;
+        }
+
+        .stats-panel {
+            background-color: var(--sidebar-background);
+            border-radius: var(--border-radius);
+            padding: 2rem;
+            margin-top: 2rem;
+        }
+
+        .stats-grid {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+            gap: 1.5rem;
+        }
+
+        .stats-item {
+            text-align: center;
+            padding: 1.5rem;
+            background-color: var(--card-background);
+            border-radius: var(--border-radius);
+        }
+
+        .stats-value {
+            font-size: 2rem;
+            font-weight: 700;
+            color: var(--primary-color);
+            display: block;
+            margin-top: 0.5rem;
+        }
+        </style>
+</head>
+<body>
+<div class="container mt-5">
+    <h1 class="text-center mb-4">Facility Management System</h1>
+
+    <div class="row">
+        <!-- Sidebar -->
+        <div class="col-md-4 sidebar">
+            <h4>Input Form</h4>
+            <form id="facility-form">
+                <div class="mb-3">
+                    <label for="num_students" class="form-label">Number of Students:</label>
+                    <input type="number" id="num_students" class="form-control" required>
+                </div>
+                <div class="mb-3">
+                    <label for="num_divisions" class="form-label">Number of Divisions:</label>
+                    <input type="number" id="num_divisions" class="form-control" required>
+                </div>
+                <div class="mb-3">
+                    <label for="num_courses" class="form-label">Number of Courses:</label>
+                    <input type="number" id="num_courses" class="form-control" required>
+                </div>
+                <div class="mb-3">
+                    <label for="course_duration" class="form-label">Course Duration (Years):</label>
+                    <input type="number" id="course_duration" class="form-control" required>
+                </div>
+                <button type="submit" class="btn btn-primary w-100">Calculate</button>
+            </form>
+        </div>
+        <!-- Facilities Section -->
+        <div class="col-md-8">
+            <div id="facilities-section">
+                {% for facility in facilities %}
+                <div class="card">
+                    <div class="card-header">{{ facility }}</div>
+                    <div class="card-body">
+                        <!-- Facility Requirements -->
+                       <div class="card-body">
+    <!-- Facility Requirements -->
+    <h5>Requirements:</h5>
+    <div class="input-group mb-3">
+        <input
+            type="text"
+            id="requirement-{{ facility | replace(' ', '_') | lower }}"
+            class="form-control text-center"
+            value="0"
+            readonly>
+        <span class="input-group-text">/</span>
+        <input
+            type="number"
+            id="actual-{{ facility | replace(' ', '_') | lower }}"
+            class="form-control text-center"
+            placeholder="Enter Actual Count">
+    </div>
+</div>
+
+
+                        <!-- Upload Images -->
+                        <h5 class="mt-4">Upload Images:</h5>
+                        <form enctype="multipart/form-data">
+                            <div class="input-group">
+                                <input type="file" class="form-control" id="files-{{ facility | replace(' ', '_') | lower }}" name="images" multiple>
+                                <button type="button" class="btn btn-success upload-btn" data-facility="{{ facility | replace(' ', '_') | lower }}">Verify Images</button>
+                            </div>
+                            <div id="verification-result-{{ facility | replace(' ', '_') | lower }}" class="mt-3">
+                                <!-- Uploaded images and verification results will be displayed here -->
+                            </div>
+                        </form>
+                    </div>
+                </div>
+                {% endfor %}
+            </div>
+        </div>
+    </div>
+</div>
+<div class="container">
+        <div class="header">
+            <h1>Object Detection</h1>
+        </div>
+
+        <div class="toast" id="toast"></div>
+        <div class="debug-panel" id="debug-panel">
+            <div class="debug-content"></div>
+        </div>
+
+        <div class="main-content">
+            <div class="detection-section">
+                <div class="detection-header">
+                    <h2>Object Detection</h2>
+                    <p>Upload images for each facility to detect and count objects</p>
+                </div>
+                
+                <form id="upload-form">
+                    <div class="upload-grid">
+                        <!-- Classroom Section -->
+                        <div class="upload-card">
+                            <h3><i class="fas fa-chalkboard"></i> Classroom</h3>
+                            <label class="custom-file-upload">
+                                <input type="file" id="image-classroom" name="image_classroom" accept="image/*" style="display: none;">
+                                <i class="fas fa-cloud-upload-alt"></i>
+                                <span>Drop classroom image here or click to upload</span>
+                            </label>
+                            <p id="file-name-classroom" class="file-name"></p>
+                            <div class="detection-results">
+                                <h4>Detected Objects</h4>
+                                <table class="table">
+                                    <thead>
+                                        <tr>
+                                            <th>Object</th>
+                                            <th>Confidence</th>
+                                            <th>Count</th>
+                                        </tr>
+                                    </thead>
+                                    <tbody id="classroom-detections"></tbody>
+                                </table>
+                            </div>
+                        </div>
+
+                        <!-- Chemical Lab Section -->
+                        <div class="upload-card">
+                            <h3><i class="fas fa-flask"></i> Chemical Lab</h3>
+                            <label class="custom-file-upload">
+                                <input type="file" id="image-chemical-lab" name="image_chemical_lab" accept="image/*" style="display: none;">
+                                <i class="fas fa-cloud-upload-alt"></i>
+                                <span>Drop lab image here or click to upload</span>
+                            </label>
+                            <p id="file-name-chemical-lab" class="file-name"></p>
+                            <div class="detection-results">
+                                <h4>Detected Objects</h4>
+                                <table class="table">
+                                    <thead>
+                                        <tr>
+                                            <th>Object</th>
+                                            <th>Confidence</th>
+                                            <th>Count</th>
+                                        </tr>
+                                    </thead>
+                                    <tbody id="chemical-lab-detections"></tbody>
+                                </table>
+                            </div>
+                        </div>
+
+                        <!-- Mechanical Workshop Section -->
+                        <div class="upload-card">
+                            <h3><i class="fas fa-tools"></i> Mechanical Workshop</h3>
+                            <label class="custom-file-upload">
+                                <input type="file" id="image-mechanical-workshop" name="image_mechanical_workshop" accept="image/*" style="display: none;">
+                                <i class="fas fa-cloud-upload-alt"></i>
+                                <span>Drop workshop image here or click to upload</span>
+                            </label>
+                            <p id="file-name-mechanical-workshop" class="file-name"></p>
+                            <div class="detection-results">
+                                <h4>Detected Objects</h4>
+                                <table class="table">
+                                    <thead>
+                                        <tr>
+                                            <th>Object</th>
+                                            <th>Confidence</th>
+                                            <th>Count</th>
+                                        </tr>
+                                    </thead>
+                                    <tbody id="mechanical-workshop-detections"></tbody>
+                                </table>
+                            </div>
+                        </div>
+
+                        <!-- Computer Lab Section -->
+                        <div class="upload-card">
+                            <h3><i class="fas fa-desktop"></i> Computer Lab</h3>
+                            <label class="custom-file-upload">
+                                <input type="file" id="image-computer-lab" name="image_computer_lab" accept="image/*" style="display: none;">
+                                <i class="fas fa-cloud-upload-alt"></i>
+                                <span>Drop computer lab image here or click to upload</span>
+                            </label>
+                            <p id="file-name-computer-lab" class="file-name"></p>
+                            <div class="detection-results">
+                                <h4>Detected Objects</h4>
+                                <table class="table">
+                                    <thead>
+                                        <tr>
+                                            <th>Object</th>
+                                            <th>Confidence</th>
+                                            <th>Count</th>
+                                        </tr>
+                                    </thead>
+                                    <tbody id="computer-lab-detections"></tbody>
+                                </table>
+                            </div>
+                        </div>
+
+                        <!-- CCTV Section -->
+                        <div class="upload-card">
+                            <h3><i class="fas fa-video"></i> CCTV Detection</h3>
+                            <label class="custom-file-upload">
+                                <input type="file" id="image-cctv" name="image_cctv" accept="image/*" style="display: none;">
+                                <i class="fas fa-cloud-upload-alt"></i>
+                                <span>Drop CCTV image here or click to upload</span>
+                            </label>
+                            <p id="file-name-cctv" class="file-name"></p>
+                            <div class="detection-results">
+                                <h4>Detected Objects</h4>
+                                <table class="table">
+                                    <thead>
+                                        <tr>
+                                            <th>Object</th>
+                                            <th>Confidence</th>
+                                            <th>Count</th>
+                                        </tr>
+                                    </thead>
+                                    <tbody id="cctv-detections"></tbody>
+                                </table>
+                            </div>
+                        </div>
+
+                        <!-- Notice Board Section -->
+                        <div class="upload-card">
+                            <h3><i class="fas fa-clipboard"></i> Notice Board Detection</h3>
+                            <label class="custom-file-upload">
+                                <input type="file" id="image-notice-board" name="image_notice_board" accept="image/*" style="display: none;">
+                                <i class="fas fa-cloud-upload-alt"></i>
+                                <span>Drop notice board image here or click to upload</span>
+                            </label>
+                            <p id="file-name-notice-board" class="file-name"></p>
+                            <div class="detection-results">
+                                <h4>Detected Objects</h4>
+                                <table class="table">
+                                    <thead>
+                                        <tr>
+                                            <th>Object</th>
+                                            <th>Confidence</th>
+                                            <th>Count</th>
+                                        </tr>
+                                    </thead>
+                                    <tbody id="notice-board-detections"></tbody>
+                                </table>
+                            </div>
+                        </div>
+
+                        <!-- Bench Section -->
+                        <div class="upload-card">
+                            <h3><i class="fas fa-chair"></i> Bench Detection</h3>
+                            <label class="custom-file-upload">
+                                <input type="file" id="image-bench" name="image_bench" accept="image/*" style="display: none;">
+                                <i class="fas fa-cloud-upload-alt"></i>
+                                <span>Drop bench image here or click to upload</span>
+                            </label>
+                            <p id="file-name-bench" class="file-name"></p>
+                            <div class="detection-results">
+                                <h4>Detected Objects</h4>
+                                <table class="table">
+                                    <thead>
+                                        <tr>
+                                            <th>Object</th>
+                                            <th>Confidence</th>
+                                            <th>Count</th>
+                                        </tr>
+                                    </thead>
+                                    <tbody id="bench-detections"></tbody>
+                                </table>
+                            </div>
+                        </div>
+                    </div>
+
+                    <button type="submit" class="btn btn-primary w-100" id="detect-all">
+                        <i class="fas fa-search"></i>
+                        Detect Objects in All Images
+                    </button>
+                </form>
+            </div>
+
+            <div class="error-message" id="error-message"></div>
+
+            <div class="loading" id="loading">
+                <div class="loading-spinner"></div>
+                <p>Analyzing image...</p>
+            </div>
+
+            <div class="stats-panel" id="stats-panel" style="display: none;">
+                <h3>Analysis Summary</h3>
+                <div class="stats-grid">
+                    <div class="stats-item">
+                        <span>Total Objects Detected</span>
+                        <span id="total-detections" class="stats-value">0</span>
+                    </div>
+                    <div class="stats-item">
+                        <span>Processing Duration</span>
+                        <span id="processing-time" class="stats-value">0ms</span>
+                    </div>
+                </div>
+            </div>
+
+            <div class="image-container">
+                <div id="result">
+                    <img id="result-image" alt="Detection result">
+                    <div class="detection-count" id="detection-count" style="display: none;"></div>
+                </div>
+            </div>
+        </div>
+
+        <div class="sidebar">
+            <h2 class="detections-title">Detected Objects</h2>
+            <div id="detections"></div>
+        </div>
+    </div>
+
+
+
+<div class="card mt-5">
+    <div class="card-header">
+        Deficiency Table
+    </div>
+    <div class="card-body">
+        <table class="table table-bordered table-hover text-center" id="deficiency-table">
+            <thead class="table-primary">
+                <tr>
+                    <th>Facility Name</th>
+                    <th>Required Count</th>
+                    <th>Actual Count</th>
+                    <th>Number of Images Verified</th>
+                    <th>Status</th>
+                </tr>
+            </thead>
+            <tbody id="deficiency-table-body">
+                <!-- Dynamic rows will be added here -->
+            </tbody>
+        </table>
+    </div>
+</div>
+<div class="grade-display-section text-center mt-4">
+    <h3>Your Grade:</h3>
+    <div id="grade-display" class="grade-display"></div>
+</div>
+<div class="text-center mt-4">
+    <h3>Download Reports</h3>
+    <button id="download-pdf" class="btn btn-primary">Download PDF Report</button>
+    <button id="download-excel" class="btn btn-success">Download Excel Report</button>
+</div>
+
+<script>
+    $('#facility-form').on('submit', function (e) {
+    e.preventDefault();
+    const data = {
+        num_students: $('#num_students').val(),
+        num_divisions: $('#num_divisions').val(),
+        num_courses: $('#num_courses').val(),
+        course_duration: $('#course_duration').val(),
+    };
+
+    $.ajax({
+        url: '/calculate',
+        type: 'POST',
+        contentType: 'application/json',
+        data: JSON.stringify(data),
+        success: function (response) {
+            for (const [facility, value] of Object.entries(response)) {
+                const facilityId = facility.replace(/ /g, '_').toLowerCase();
+                $(`#requirement-${facilityId}`).val(value);
+
+                // Optionally, clear or prefill the "Actual Count" input box
+                $(`#actual-${facilityId}`).val('');
+            }
+        },
+        error: function () {
+            alert('Failed to calculate facilities. Please try again.');
+        }
+    });
+});
+
+// Capture "Actual Count" values for further processing
+function getActualCounts() {
+    const actualCounts = {};
+    $('.card').each(function () {
+        const facility = $(this).find('.card-header').text().trim();
+        const facilityId = facility.replace(/ /g, '_').toLowerCase();
+        const actualCount = $(`#actual-${facilityId}`).val();
+        actualCounts[facility] = actualCount ? parseInt(actualCount, 10) : 0;
+    });
+    console.log(actualCounts);
+    // Perform additional processing with `actualCounts` as needed
+}
+
+    // Handle Multiple File Upload
+    $('.upload-btn').on('click', function () {
+        const facility = $(this).data('facility');
+        const fileInput = $(`#files-${facility}`)[0];
+        const files = fileInput.files;
+
+        if (files.length === 0) {
+            alert('Please select at least one image.');
+            return;
+        }
+
+        const formData = new FormData();
+        Array.from(files).forEach((file) => {
+            formData.append('images', file);
+        });
+
+        $.ajax({
+            url: `/upload/${facility.replace(/_/g, ' ')}`,
+            type: 'POST',
+            processData: false,
+            contentType: false,
+            data: formData,
+            success: function (response) {
+                let resultsHtml = '';
+                response.forEach((result, index) => {
+                    const fileReader = new FileReader();
+
+                    // Render each image
+                    fileReader.onload = function (e) {
+                        resultsHtml += `
+                            <div class="uploaded-image">
+                                <img src="${e.target.result}" alt="Uploaded Image" class="img-thumbnail" style="max-width: 200px;">
+                                <p class="text-center mt-2">
+                                    <strong>Label:</strong> ${result.label}<br>
+                                    <strong>Confidence:</strong> ${result.confidence.toFixed(2)}
+                                </p>
+                                <p class="text-center ${result.confidence >= 0.8 ? 'text-success' : 'text-danger'}">
+                                    ${result.confidence >= 0.8 ? 'Verified' : 'Not Verified'}
+                                </p>
+                            </div>
+                        `;
+
+                        // Update the results section for the facility after all images are processed
+                        if (index === response.length - 1) {
+                            $(`#verification-result-${facility}`).html(resultsHtml);
+                        }
+                    };
+
+                    // Read the file to get its data URL
+                    fileReader.readAsDataURL(files[index]);
+                });
+            },
+            error: function () {
+                $(`#verification-result-${facility}`).html(`
+                    <div class="alert alert-danger">Failed to verify images.</div>
+                `);
+            }
+        });
+    });
+
+    // Handle Answer Submission
+    $('.submit-answers').on('click', function () {
+        const facility = $(this).data('facility');
+        const answers = [];
+        $(this).closest('.question-form').find('.answer-box').each(function () {
+            answers.push({
+                question: $(this).data('question'),
+                answer: $(this).val()
+            });
+        });
+
+        $.ajax({
+            url: '/submit_answers',
+            type: 'POST',
+            contentType: 'application/json',
+            data: JSON.stringify({ facility: facility, answers: answers }),
+            success: function (response) {
+                alert(response.message);
+            },
+            error: function () {
+                alert('Failed to submit answers.');
+            }
+        });
+    });
+ const loadingDiv = document.getElementById('loading');
+        const errorMessage = document.getElementById('error-message');
+        const form = document.getElementById('upload-form');
+        const detectButton = form.querySelector('button[type="submit"]');
+        const imageInputs = {
+            classroom: document.getElementById('image-classroom'),
+            chemical_lab: document.getElementById('image-chemical-lab'),
+            mechanical_workshop: document.getElementById('image-mechanical-workshop'),
+            computer_lab: document.getElementById('image-computer-lab'),
+            cctv: document.getElementById('image-cctv'),
+            notice_board: document.getElementById('image-notice-board'),
+            bench: document.getElementById('image-bench')
+        };
+
+        // Handle file selection for each input
+        Object.entries(imageInputs).forEach(([key, input]) => {
+            input.addEventListener('change', (e) => {
+                const file = e.target.files[0];
+                const fileNameElement = document.getElementById(`file-name-${key.replace('_', '-')}`);
+                if (file) {
+                    fileNameElement.textContent = `Selected: ${file.name}`;
+                    updateDetectButton();
+                } else {
+                    fileNameElement.textContent = '';
+                }
+                // Clear previous results when new file is selected
+                clearResults();
+            });
+        });
+
+        function clearResults() {
+            const resultContainer = document.getElementById('result');
+            resultContainer.innerHTML = '<img id="result-image" alt="Detection result" style="display: none;">';
+            document.getElementById('stats-panel').style.display = 'none';
+            errorMessage.style.display = 'none';
+        }
+
+        function updateDetectButton() {
+            const allFilesSelected = Object.values(imageInputs).every(input => input.files.length > 0);
+            detectButton.disabled = !allFilesSelected;
+        }
+
+        form.addEventListener('submit', async (e) => {
+            e.preventDefault();
+
+            const formData = new FormData();
+            let allFilesValid = true;
+
+            // Clear previous results
+            clearResults();
+
+            Object.entries(imageInputs).forEach(([key, input]) => {
+                const file = input.files[0];
+                if (!file) {
+                    showToast(`Please select an image for ${key.replace('_', ' ')}`, 'error');
+                    allFilesValid = false;
+                    return;
+                }
+                formData.append(`image_${key}`, file);
+            });
+
+            if (!allFilesValid) return;
+
+            const startTime = performance.now();
+            loadingDiv.style.display = 'block';
+            detectButton.disabled = true;
+            errorMessage.style.display = 'none';
+
+            try {
+                const response = await fetch('/detect', {
+                    method: 'POST',
+                    body: formData
+                });
+
+                const data = await response.json();
+
+                if (data.success) {
+                    const processingTime = Math.round(performance.now() - startTime);
+                    displayResults(data.results, processingTime);
+                } else {
+                    errorMessage.textContent = data.error || 'Error processing images';
+                    errorMessage.style.display = 'block';
+                    showToast(data.error || 'Error processing images', 'error');
+                }
+            } catch (error) {
+                errorMessage.textContent = 'Network error or server not responding';
+                errorMessage.style.display = 'block';
+                showToast('Network error or server not responding', 'error');
+                console.error('Error:', error);
+            } finally {
+                loadingDiv.style.display = 'none';
+                detectButton.disabled = false;
+            }
+        });
+
+        function displayResults(results, processingTime) {
+            const resultContainer = document.getElementById('result');
+            resultContainer.innerHTML = '<div class="results-grid"></div>';
+            const grid = resultContainer.querySelector('.results-grid');
+            let totalDetections = 0;
+
+            Object.entries(results).forEach(([environment, data]) => {
+                const card = document.createElement('div');
+                card.className = 'result-card';
+
+                // Format the environment name for display
+                const envName = environment.split('_')
+                    .map(word => word.charAt(0).toUpperCase() + word.slice(1))
+                    .join(' ');
+
+                card.innerHTML = `
+                    <h3>${envName}</h3>
+                    <img src="${data.image}" alt="${environment}" style="width: 100%">
+                    <div class="detections-count">${data.detections.length} objects detected</div>
+                    <div class="detections-list">
+                        ${data.detections.map(det => `
+                            <div class="detection-item">
+                                <span>${det.class}</span>
+                                <span class="confidence-badge">${(det.confidence * 100).toFixed(1)}%</span>
+                            </div>
+                        `).join('')}
+                    </div>
+                `;
+                grid.appendChild(card);
+                totalDetections += data.detections.length;
+            });
+
+            // Update stats panel
+            document.getElementById('total-detections').textContent = totalDetections;
+            document.getElementById('processing-time').textContent = `${processingTime}ms`;
+            document.getElementById('stats-panel').style.display = 'block';
+
+            showToast(`Processing completed in ${processingTime}ms`);
+        }
+
+        function showToast(message, type = 'success') {
+            const toast = document.getElementById('toast');
+            toast.textContent = message;
+            toast.className = `toast ${type}`;
+            toast.style.display = 'block';
+
+            setTimeout(() => {
+                toast.style.display = 'none';
+            }, 3000);
+        }
+
+        function debugLog(message) {
+            const debugPanel = document.getElementById('debug-panel');
+            const content = debugPanel.querySelector('.debug-content');
+            const timestamp = new Date().toLocaleTimeString();
+            content.innerHTML += `[${timestamp}] ${message}<br>`;
+            content.scrollTop = content.scrollHeight;
+        }
+
+        // Handle window resize
+        let resizeTimeout;
+        window.addEventListener('resize', () => {
+            clearTimeout(resizeTimeout);
+            resizeTimeout = setTimeout(() => {
+                const highlightBoxes = document.querySelectorAll('.highlight-box');
+                const labels = document.querySelectorAll('.detection-label');
+                highlightBoxes.forEach(box => box.style.display = 'none');
+                labels.forEach(label => label.style.display = 'none');
+            }, 250);
+        });
+
+        // Add debug panel toggle
+        document.addEventListener('keypress', (e) => {
+            if (e.key === 'd') {
+                const debugPanel = document.getElementById('debug-panel');
+                debugPanel.classList.toggle('show');
+            }
+        });
+
+
+function updateDeficiencyTableAndGrade() {
+    const tableBody = $('#deficiency-table-body');
+    tableBody.empty(); // Clear existing rows
+
+    let totalDeficiencies = 0;
+    let totalVerifiedImages = 0;
+    const totalFacilities = $('.card').length;
+
+    $('.card').each(function () {
+        const facilityName = $(this).find('.card-header').text().trim();
+        const facilityId = facilityName.replace(/ /g, '_').toLowerCase();
+        const requiredCount = parseInt($(`#requirement-${facilityId}`).val(), 10) || 0;
+        const actualCount = parseInt($(`#actual-${facilityId}`).val(), 10) || 0;
+
+        // Count verified images
+        const verifiedImages = $(`#verification-result-${facilityId} .uploaded-image .text-success`).length;
+        totalVerifiedImages += verifiedImages;
+
+        // Determine deficiency
+        const deficiency = requiredCount > actualCount;
+        if (deficiency) totalDeficiencies++;
+
+        const status = deficiency
+            ? `<span class="text-danger">&#10008; Deficiency</span>`
+            : `<span class="text-success">&#10004; No Deficiency</span>`;
+
+        // Add a new row to the table
+        tableBody.append(`
+            <tr>
+                <td>${facilityName}</td>
+                <td>${requiredCount}</td>
+                <td>${actualCount}</td>
+                <td>${verifiedImages}</td>
+                <td>${status}</td>
+            </tr>
+        `);
+    });
+
+    // Calculate grade
+    const grade = calculateGrade(totalDeficiencies, totalVerifiedImages, totalFacilities);
+
+    // Update grade display
+    const gradeDisplay = $('#grade-display');
+    gradeDisplay
+        .removeClass('grade-a grade-b grade-c grade-d grade-f')
+        .addClass(`grade-${grade.toLowerCase()}`)
+        .text(grade);
+}
+
+function calculateGrade(totalDeficiencies, totalVerifiedImages, totalFacilities) {
+    const deficiencyRate = totalDeficiencies / totalFacilities;
+    const verificationBonus = totalVerifiedImages / totalFacilities;
+
+    if (deficiencyRate <= 0.1 && verificationBonus >= 0.8) return 'A';
+    if (deficiencyRate <= 0.2 && verificationBonus >= 0.6) return 'B';
+    if (deficiencyRate <= 0.3 && verificationBonus >= 0.4) return 'C';
+    if (deficiencyRate <= 0.4 && verificationBonus >= 0.2) return 'D';
+    return 'F';
+}
+
+// Attach event listeners
+$('#facility-form').on('submit', function (e) {
+    e.preventDefault();
+    updateDeficiencyTableAndGrade();
+});
+
+$('.form-control').on('input', function () {
+    updateDeficiencyTableAndGrade();
+});
+
+$('.upload-btn').on('click', function () {
+    setTimeout(() => {
+        updateDeficiencyTableAndGrade();
+    }, 1000); // Allow time for verification results to render
+});
+
+// Handle PDF download
+$('#download-pdf').on('click', function () {
+    window.location.href = '/download_report';
+});
+
+// Handle Excel download
+$('#download-excel').on('click', function () {
+    window.location.href = '/download_excel';
+});
+
+// Add FontAwesome for icons
+document.head.innerHTML += '<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.4/css/all.min.css">';
+
+</script>
+</body>
+</html>
diff --git a/yolov8n.pt b/yolov8n.pt
new file mode 100644
index 0000000000000000000000000000000000000000..719e6f1dbdfe7c560e5933fc8b0c5a7e857d0234
--- /dev/null
+++ b/yolov8n.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f59b3d833e2ff32e194b5bb8e08d211dc7c5bdf144b90d2c8412c47ccfc83b36
+size 6549796