connect_error) { die("Connection failed: " . $conn->connect_error); } ?> نظام حضور طلاب جامعة الملك عبدالعزيز

نظام حضور طلاب جامعة الملك عبدالعزيز

تحضير الطالب كشف الحضور

تحضير الطالب

نتيجة التحضير

اسم الطالب:

نسبة التشابه: %

وقت التعرف: ثانية

سرعة التعرف: RPS

تم التحضير بنجاح

connect_error) { die("Connection failed: " . $conn->connect_error); } // Get attendance records $sql = "SELECT * FROM attendance_records ORDER BY date DESC, time DESC"; $result = $conn->query($sql); ?> كشف الحضور

كشف الحضور

num_rows > 0): ?> fetch_assoc()): ?>

اسم الطالب	التاريخ	الوقت	نسبة التشابه	وقت التعرف	سرعة التعرف
			%	ثانية	RPS
لا توجد سجلات حضور

تصدير إلى CSV

close(); ?> 5000000) { $_SESSION['upload_error'] = "حجم الصورة كبير جداً. الحد الأقصى 5MB."; header("Location: prepare.php"); exit(); } // Allow certain file formats if ($imageFileType != "jpg" && $imageFileType != "png" && $imageFileType != "jpeg") { $_SESSION['upload_error'] = "نوع الملف غير مدعوم. يرجى رفع صورة بصيغة JPG, JPEG أو PNG."; header("Location: prepare.php"); exit(); } // Upload file if (move_uploaded_file($_FILES["student_image"]["tmp_name"], $target_file)) { // Call Python face recognition API $python_api_url = "http://localhost:5000/recognize"; $post_data = [ 'image_path' => $target_file ]; $ch = curl_init($python_api_url); curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); curl_setopt($ch, CURLOPT_POSTFIELDS, $post_data); $response = curl_exec($ch); curl_close($ch); $result = json_decode($response, true); if ($result && $result['status'] === 'success') { // Save to database $db_host = 'localhost'; $db_user = 'root'; $db_pass = ''; $db_name = 'kau_attendance'; $conn = new mysqli($db_host, $db_user, $db_pass, $db_name); if ($conn->connect_error) { die("Connection failed: " . $conn->connect_error); } $stmt = $conn->prepare("INSERT INTO attendance_records (student_name, date, time, confidence, recognition_time, rps) VALUES (?, CURDATE(), CURTIME(), ?, ?, ?)"); $stmt->bind_param("sddd", $result['student_name'], $result['confidence'], $result['recognition_time'], $result['rps']); $stmt->execute(); $stmt->close(); $conn->close(); // Store result in session $_SESSION['attendance_result'] = $result; header("Location: prepare.php"); exit(); } else { $_SESSION['upload_error'] = "فشل التعرف على الوجه. يرجى المحاولة مرة أخرى."; header("Location: prepare.php"); exit(); } } else { $_SESSION['upload_error'] = "حدث خطأ أثناء رفع الملف."; header("Location: prepare.php"); exit(); } } ?> body { font-family: 'Arial', sans-serif; background-color: #f5f5f5; margin: 0; padding: 0; color: #333; } .container { max-width: 1200px; margin: 0 auto; padding: 20px; } header { text-align: center; margin-bottom: 30px; } .logo { height: 100px; margin-bottom: 20px; } h1 { color: #1a5276; margin-bottom: 30px; } .options { display: flex; justify-content: center; gap: 20px; margin-bottom: 30px; } .btn { display: inline-block; padding: 10px 20px; background-color: #1a5276; color: white; text-decoration: none; border-radius: 5px; font-size: 16px; transition: background-color 0.3s; } .btn:hover { background-color: #154360; } .camera-container { text-align: center; margin-bottom: 30px; } video, canvas { border: 2px solid #1a5276; border-radius: 5px; margin-bottom: 15px; } #capture-btn { margin-bottom: 20px; } .result-container { background-color: white; padding: 20px; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); margin-bottom: 20px; } .success { color: #27ae60; font-weight: bold; } .attendance-table { overflow-x: auto; margin-bottom: 30px; } table { width: 100%; border-collapse: collapse; margin-bottom: 20px; } th, td { padding: 12px; text-align: center; border-bottom: 1px solid #ddd; } th { background-color: #1a5276; color: white; } tr:hover { background-color: #f5f5f5; } .export-btn { text-align: center; margin-bottom: 30px; } footer { text-align: center; margin-top: 30px; } document.addEventListener('DOMContentLoaded', function() { const video = document.getElementById('video'); const canvas = document.getElementById('canvas'); const captureBtn = document.getElementById('capture-btn'); const resultDiv = document.getElementById('result'); // Access camera if (navigator.mediaDevices && navigator.mediaDevices.getUserMedia) { navigator.mediaDevices.getUserMedia({ video: true }) .then(function(stream) { video.srcObject = stream; }) .catch(function(error) { console.error("Error accessing camera: ", error); }); } // Capture image captureBtn.addEventListener('click', function() { canvas.getContext('2d').drawImage(video, 0, 0, canvas.width, canvas.height); const imageData = canvas.toDataURL('image/jpeg'); // Send image to server for processing fetch('upload.php', { method: 'POST', headers: { 'Content-Type': 'application/x-www-form-urlencoded', }, body: 'image_data=' + encodeURIComponent(imageData) }) .then(response => response.json()) .then(data => { if (data.status === 'success') { // Display result resultDiv.innerHTML = `

نتيجة التحضير

اسم الطالب: ${data.student_name}

نسبة التشابه: ${data.confidence}%

وقت التعرف: ${data.recognition_time} ثانية

سرعة التعرف: ${data.rps} RPS

تم التحضير بنجاح

`; } else { resultDiv.innerHTML = `

${data.message}

`; } }) .catch(error => { console.error('Error:', error); resultDiv.innerHTML = '

حدث خطأ أثناء معالجة الصورة

'; }); }); }); from flask import Flask, request, jsonify import face_recognition import os import time import mysql.connector from datetime import datetime app = Flask(__name__) # Database configuration db_config = { 'host': 'localhost', 'user': 'root', 'password': '', 'database': 'kau_attendance' } # Load known faces from database def load_known_faces(): known_faces = [] known_names = [] try: conn = mysql.connector.connect(**db_config) cursor = conn.cursor() cursor.execute("SELECT student_id, student_name, face_encoding FROM students") results = cursor.fetchall() for row in results: student_id, student_name, face_encoding = row # Convert binary face encoding back to numpy array encoding = face_recognition.face_encodings(face_recognition.load_image_file(face_encoding))[0] known_faces.append(encoding) known_names.append(student_name) cursor.close() conn.close() except Exception as e: print(f"Error loading known faces: {e}") return known_faces, known_names @app.route('/recognize', methods=['POST']) def recognize_face(): start_time = time.time() if 'image_path' not in request.form: return jsonify({'status': 'error', 'message': 'No image provided'}), 400 image_path = request.form['image_path'] try: # Load the uploaded image unknown_image = face_recognition.load_image_file(image_path) # Find all face locations and encodings in the unknown image face_locations = face_recognition.face_locations(unknown_image) face_encodings = face_recognition.face_encodings(unknown_image, face_locations) if len(face_encodings) == 0: return jsonify({'status': 'error', 'message': 'No faces found in the image'}), 400 # Load known faces known_faces, known_names = load_known_faces() # Compare faces recognition_results = [] for face_encoding in face_encodings: matches = face_recognition.compare_faces(known_faces, face_encoding, tolerance=0.6) face_distances = face_recognition.face_distance(known_faces, face_encoding) best_match_index = face_distances.argmin() confidence = (1 - face_distances[best_match_index]) * 100 if matches[best_match_index]: recognition_results.append({ 'student_name': known_names[best_match_index], 'confidence': round(confidence, 2), 'recognition_time': round(time.time() - start_time, 2), 'rps': round(1 / (time.time() - start_time), 2) if (time.time() - start_time) > 0 else 0 }) if recognition_results: return jsonify({'status': 'success', 'message': 'Face recognized', 'result': recognition_result[0]}) else: return jsonify({'status': 'error', 'message': 'No match found'}) else: return jsonify({'status': 'error', 'message': 'No face detected'}) except Exception as e: return jsonify({'status': 'error', 'message': str(e)}) else: return jsonify({'status': 'error', 'message': 'Invalid request method'}) if __name__ == '__main__': app.run(debug=True) Flask==2.0.1 face-recognition==1.3.0 numpy==1.21.2 mysql-connector-python==8.0.26 CREATE DATABASE IF NOT EXISTS `kau_attendance` DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci; USE `kau_attendance`; CREATE TABLE IF NOT EXISTS `student` ( `student_id` int(11) NOT NULL AUTO_INCREMENT, `student_name` varchar(255) NOT NULL, `face_encoding` longtext NOT NULL, PRIMARY KEY (`student_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4; CREATE TABLE IF NOT EXISTS `attendance_record` ( `record