Upload 16 files

app.py

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+from flask import Flask, render_template, request, jsonify
+import os
+import cv2
+import numpy as np
+import pandas as pd
+from datetime import datetime
+import base64
+
+app = Flask(__name__)
+
+# Setup
+face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
+dataset_path = "./face_dataset/"
+os.makedirs(dataset_path, exist_ok=True)
+
+# KNN distance
+def distance(v1, v2):
+    return np.sqrt(((v1 - v2) ** 2).sum())
+
+def knn(train, test, k=5):
+    dist = []
+    for i in range(train.shape[0]):
+        ix = train[i, :-1]
+        iy = train[i, -1]
+        d = distance(test, ix)
+        dist.append([d, iy])
+    dk = sorted(dist, key=lambda x: x[0])[:k]
+    labels = np.array(dk)[:, -1]
+    return np.unique(labels, return_counts=True)[0][0]
+
+# Attendance system
+class AttendanceSystem:
+    def __init__(self):
+        self.file = "attendance.csv"
+        self.columns = ["Name", "Date", "Time"]
+        if not os.path.exists(self.file):
+            pd.DataFrame(columns=self.columns).to_csv(self.file, index=False)
+
+    def mark(self, name):
+        today = datetime.now().strftime("%Y-%m-%d")
+        now = datetime.now().strftime("%H:%M:%S")
+        df = pd.read_csv(self.file)
+        existing = df[(df["Name"] == name) & (df["Date"] == today)]
+        if existing.empty:
+            new_entry = pd.DataFrame([[name, today, now]], columns=self.columns)
+            df = pd.concat([df, new_entry], ignore_index=True)
+            df.to_csv(self.file, index=False)
+            return True
+        return False
+
+attendance = AttendanceSystem()
+
+# Home page
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/register')
+def register():
+    return render_template('register.html')
+
+@app.route('/mark')
+def mark():
+    return render_template('mark.html')
+
+# API to save face during registration
+@app.route('/api/register_face', methods=['POST'])
+def register_face():
+    data = request.json
+    name = data['name']
+    images = data['images']  # List of base64 images
+
+    face_data = []
+
+    for img_data in images:
+        img_bytes = base64.b64decode(img_data.split(",")[1])
+        np_arr = np.frombuffer(img_bytes, np.uint8)
+        img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
+
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+
+        for (x, y, w, h) in faces[:1]:
+            face = img[y:y+h, x:x+w]
+            face = cv2.resize(face, (100, 100))
+            face_data.append(face.flatten())
+
+    if face_data:
+        face_data = np.array(face_data)
+        np.save(os.path.join(dataset_path, f"{name}.npy"), face_data)
+        return jsonify({"status": "success", "message": f"{len(face_data)} faces saved"})
+    else:
+        return jsonify({"status": "fail", "message": "No faces detected"})
+
+# API to mark attendance
+@app.route('/api/mark_attendance', methods=['POST'])
+def mark_attendance():
+    img_data = request.json['image']
+    img_bytes = base64.b64decode(img_data.split(",")[1])
+    np_arr = np.frombuffer(img_bytes, np.uint8)
+    img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
+
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+
+    # Load training data
+    face_data = []
+    labels = []
+    names = {}
+    class_id = 0
+
+    for file in os.listdir(dataset_path):
+        if file.endswith('.npy'):
+            data = np.load(os.path.join(dataset_path, file))
+            face_data.append(data)
+            names[class_id] = file[:-4]
+            labels.extend([class_id] * data.shape[0])
+            class_id += 1
+
+    if not face_data:
+        return jsonify({"status": "fail", "message": "No trained data found"})
+
+    X_train = np.concatenate(face_data, axis=0)
+    y_train = np.array(labels).reshape(-1, 1)
+    trainset = np.hstack((X_train, y_train))
+
+    for (x, y, w, h) in faces[:1]:
+        face = img[y:y+h, x:x+w]
+        face = cv2.resize(face, (100, 100)).flatten()
+        pred_id = knn(trainset, face)
+        name = names.get(pred_id, "Unknown")
+
+        if name != "Unknown":
+            marked = attendance.mark(name)
+            msg = "Attendance marked" if marked else "Already marked today"
+            return jsonify({"status": "success", "name": name, "message": msg})
+
+    return jsonify({"status": "fail", "message": "No known face detected"})
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=5000, debug=True)

attendance.csv

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+Name,Date,Time
+DSA,4/6/2025,15:27:56
+Harshvardhan Dhane,4/6/2025,15:35:33
+Ravi,4/6/2025,15:42:07
+Harsh,4/6/2025,15:43:47
+harshvardhan,4/6/2025,15:47:15
+Ravi,4/7/2025,12:49:02
+Harsh,4/7/2025,12:50:14
+Yashodhan,2025-04-08,02:06:00
+Ravi,2025-04-08,02:06:21
+Harsh,2025-04-08,02:08:18
+Sudhir,2025-04-08,02:11:00
+Tulasi ,2025-04-08,13:39:34
+Aman,2025-04-08,15:00:46

face_dataset/Aman.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8325e3cc868993eb7a85782c47913e5cbf163ae12900e9159233ad5c156b0d91
+size 450128

face_dataset/Harsh.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9e94abd225bedded2ef763ffc097fb0b67ba4ac6003083ac1ca0cdc0ab7bede8
+size 450128

face_dataset/Ravi.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:efa7e14a321cd913118bd25ea983379b29aa27e82e847a70dddf58371342702b
+size 420128

face_dataset/Sudhir.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:53af27e7af2c2eaf629b423594eddb8988d3656f984f204701fc25a0276850a8
+size 690128

face_dataset/Tulasi .npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e23b8fc46e01a4ce67ba7d017505aff046df28ca9fa1f78418924aad75f8c87e
+size 330128

face_dataset/Yashodhan.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f9fdca318514deacf6bbaf1a7392557e0fa86e0c59f4b804a7b02092fc6dbeef
+size 6480128

static/js/webcam.js

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+function initWebcam(videoId) {
+    const video = document.getElementById(videoId);
+    navigator.mediaDevices.getUserMedia({ video: true }).then(stream => {
+        video.srcObject = stream;
+    });
+}
+
+function captureFrame(frameArray, single = false) {
+    return new Promise((resolve) => {
+        const video = document.getElementById("video");
+        const canvas = document.createElement("canvas");
+        canvas.width = video.videoWidth;
+        canvas.height = video.videoHeight;
+        const ctx = canvas.getContext("2d");
+        ctx.drawImage(video, 0, 0);
+        const image = canvas.toDataURL("image/jpeg");
+        if (!single) {
+            frameArray.push(image);
+            resolve();
+        } else {
+            resolve(image);
+        }
+    });
+}

templates/index.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Face Attendance</title>
+    <style>
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            margin: 0;
+            padding: 0;
+            background-color: #f5f5f5;
+            color: #333;
+            line-height: 1.6;
+        }
+        .container {
+            width: 80%;
+            max-width: 800px;
+            margin: 50px auto;
+            padding: 30px;
+            background-color: #fff;
+            border-radius: 8px;
+            box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
+            text-align: center;
+        }
+        h2 {
+            color: #2c3e50;
+            margin-bottom: 30px;
+            font-size: 32px;
+        }
+        .nav-links {
+            display: flex;
+            flex-direction: column;
+            gap: 15px;
+            margin-top: 25px;
+        }
+        .btn {
+            display: inline-block;
+            padding: 12px 24px;
+            background-color: #3498db;
+            color: white;
+            text-decoration: none;
+            border-radius: 5px;
+            font-weight: 500;
+            transition: background-color 0.3s;
+            border: none;
+            font-size: 16px;
+            cursor: pointer;
+        }
+        .btn:hover {
+            background-color: #2980b9;
+        }
+        .logo {
+            font-size: 36px;
+            color: #3498db;
+            margin-bottom: 15px;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <div class="logo">
+            <i class="fas fa-user-check"></i>
+        </div>
+        <h2>Welcome to Face Attendance System</h2>
+        <div class="nav-links">
+            <a href="/register" class="btn">Register Face</a>
+            <a href="/mark" class="btn">Mark Attendance</a>
+        </div>
+    </div>
+    <!-- Add Font Awesome for icons -->
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.4/js/all.min.js"></script>
+</body>
+</html>

templates/index.html.bak

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+<!-- index.html -->
+
+
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Face Attendance</title>
+</head>
+<body>
+    <h2>Welcome to Face Attendance System</h2>
+    <a href="/register">Register Face</a><br>
+    <a href="/mark">Mark Attendance</a>
+</body>
+</html>

templates/mark.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Mark Attendance</title>
+    <style>
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            margin: 0;
+            padding: 0;
+            background-color: #f5f5f5;
+            color: #333;
+            line-height: 1.6;
+        }
+        .container {
+            width: 80%;
+            max-width: 800px;
+            margin: 30px auto;
+            padding: 30px;
+            background-color: #fff;
+            border-radius: 8px;
+            box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
+            text-align: center;
+        }
+        h2 {
+            color: #2c3e50;
+            margin-bottom: 25px;
+            font-size: 28px;
+        }
+        .btn {
+            display: inline-block;
+            padding: 12px 24px;
+            background-color: #27ae60;
+            color: white;
+            text-decoration: none;
+            border-radius: 5px;
+            font-weight: 500;
+            transition: background-color 0.3s;
+            border: none;
+            font-size: 16px;
+            cursor: pointer;
+            margin: 15px 0;
+        }
+        .btn:hover {
+            background-color: #219653;
+        }
+        video {
+            margin: 20px auto;
+            border-radius: 8px;
+            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+            background-color: #eee;
+            max-width: 100%;
+        }
+        #status {
+            margin-top: 20px;
+            font-size: 18px;
+            padding: 15px;
+            border-radius: 5px;
+            background-color: #f8f9fa;
+            display: inline-block;
+            min-width: 60%;
+        }
+        .success {
+            color: #27ae60;
+            font-weight: 600;
+        }
+        .error {
+            color: #e74c3c;
+            font-weight: 600;
+        }
+        .header {
+            display: flex;
+            justify-content: space-between;
+            align-items: center;
+            margin-bottom: 20px;
+        }
+        .back-link {
+            color: #3498db;
+            text-decoration: none;
+            display: flex;
+            align-items: center;
+            font-weight: 500;
+        }
+        .back-link:hover {
+            text-decoration: underline;
+        }
+        .video-container {
+            position: relative;
+            margin: 0 auto;
+            width: 320px;
+            max-width: 100%;
+        }
+        .camera-overlay {
+            position: absolute;
+            top: 0;
+            left: 0;
+            right: 0;
+            bottom: 0;
+            border: 2px solid rgba(52, 152, 219, 0.5);
+            border-radius: 8px;
+            pointer-events: none;
+        }
+        .loading {
+            display: none;
+            margin: 20px auto;
+            border: 5px solid #f3f3f3;
+            border-radius: 50%;
+            border-top: 5px solid #3498db;
+            width: 40px;
+            height: 40px;
+            animation: spin 1s linear infinite;
+        }
+        @keyframes spin {
+            0% { transform: rotate(0deg); }
+            100% { transform: rotate(360deg); }
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <div class="header">
+            <a href="/" class="back-link">
+                <i class="fas fa-arrow-left"></i> &nbsp;Back to Home
+            </a>
+            <h2>Mark Attendance</h2>
+        </div>
+        
+        <div class="video-container">
+            <video id="video" width="300" autoplay></video>
+            <div class="camera-overlay"></div>
+        </div>
+        
+        <button onclick="markAttendance()" class="btn">
+            <i class="fas fa-user-check"></i> Mark Attendance
+        </button>
+        
+        <div class="loading" id="loading"></div>
+        <p id="status">Position your face in the camera and click the button</p>
+    </div>
+
+    <script src="/static/js/webcam.js"></script>
+    <script>
+        async function markAttendance() {
+            document.getElementById("loading").style.display = "block";
+            document.getElementById("status").innerText = "Processing...";
+            
+            captureFrame([], true).then(image => {
+                fetch('/api/mark_attendance', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ image: image })
+                })
+                .then(res => res.json())
+                .then(data => {
+                    document.getElementById("loading").style.display = "none";
+                    
+                    const statusElem = document.getElementById("status");
+                    if (data.name) {
+                        statusElem.innerHTML = `<span class="success">Welcome, ${data.name}!</span><br>${data.message}`;
+                    } else {
+                        statusElem.innerHTML = `<span class="error">Face not recognized</span><br>${data.message}`;
+                    }
+                })
+                .catch(err => {
+                    document.getElementById("loading").style.display = "none";
+                    document.getElementById("status").innerHTML = `<span class="error">Error: ${err.message}</span>`;
+                });
+            });
+        }
+        initWebcam("video");
+    </script>
+    
+    <!-- Add Font Awesome for icons -->
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.4/js/all.min.js"></script>
+</body>
+</html>

templates/mark.html.bak

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+<!-- mark.html -->
+
+
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Face Attendance</title>
+</head>
+<body>
+    <h2>Welcome to Face Attendance System</h2>
+    <a href="/register">Register Face</a><br>
+    <a href="/mark">Mark Attendance</a>
+</body>
+</html>
+
+
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Mark Attendance</title>
+</head>
+<body>
+    <h2>Mark Attendance</h2>
+    <button onclick="markAttendance()">Mark</button>
+    <video id="video" width="300" autoplay></video>
+    <p id="status"></p>
+
+    <script src="/static/js/webcam.js"></script>
+    <script>
+        async function markAttendance() {
+            captureFrame([], true).then(image => {
+                fetch('/api/mark_attendance', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ image: image })
+                })
+                .then(res => res.json())
+                .then(data => {
+                    document.getElementById("status").innerText = data.name + ": " + data.message;
+                });
+            });
+        }
+
+        initWebcam("video");
+    </script>
+</body>
+</html>

templates/register.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Register Face</title>
+    <style>
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            margin: 0;
+            padding: 0;
+            background-color: #f5f5f5;
+            color: #333;
+            line-height: 1.6;
+        }
+        .container {
+            width: 80%;
+            max-width: 800px;
+            margin: 30px auto;
+            padding: 30px;
+            background-color: #fff;
+            border-radius: 8px;
+            box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
+            text-align: center;
+        }
+        h2 {
+            color: #2c3e50;
+            margin-bottom: 25px;
+            font-size: 28px;
+        }
+        .btn {
+            display: inline-block;
+            padding: 12px 24px;
+            background-color: #3498db;
+            color: white;
+            text-decoration: none;
+            border-radius: 5px;
+            font-weight: 500;
+            transition: background-color 0.3s;
+            border: none;
+            font-size: 16px;
+            cursor: pointer;
+            margin-top: 15px;
+        }
+        .btn:hover {
+            background-color: #2980b9;
+        }
+        input[type="text"] {
+            width: 100%;
+            padding: 12px;
+            margin: 10px 0;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            box-sizing: border-box;
+            font-size: 16px;
+        }
+        video {
+            margin: 20px auto;
+            border-radius: 8px;
+            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+            background-color: #eee;
+            max-width: 100%;
+        }
+        #status {
+            margin-top: 15px;
+            font-weight: 500;
+            color: #2c3e50;
+        }
+        .header {
+            display: flex;
+            justify-content: space-between;
+            align-items: center;
+            margin-bottom: 20px;
+        }
+        .back-link {
+            color: #3498db;
+            text-decoration: none;
+            display: flex;
+            align-items: center;
+            font-weight: 500;
+        }
+        .back-link:hover {
+            text-decoration: underline;
+        }
+        .form-container {
+            margin-top: 20px;
+        }
+        .progress {
+            margin-top: 10px;
+            height: 10px;
+            background-color: #eee;
+            border-radius: 5px;
+            overflow: hidden;
+            position: relative;
+            margin-bottom: 15px;
+        }
+        .progress-bar {
+            height: 100%;
+            background-color: #3498db;
+            width: 0%;
+            transition: width 0.5s ease;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <div class="header">
+            <a href="/" class="back-link">
+                <i class="fas fa-arrow-left"></i> &nbsp;Back to Home
+            </a>
+            <h2>Register Face</h2>
+        </div>
+        
+        <div class="form-container">
+            <input type="text" id="name" placeholder="Enter your name" required>
+            <button onclick="startCapture()" class="btn">
+                <i class="fas fa-camera"></i> Start Capture
+            </button>
+            
+            <div class="video-container">
+                <video id="video" width="300" autoplay></video>
+            </div>
+            
+            <div class="progress">
+                <div class="progress-bar" id="progress-bar"></div>
+            </div>
+            
+            <p id="status">Enter your name and click "Start Capture"</p>
+        </div>
+    </div>
+
+    <script src="/static/js/webcam.js"></script>
+    <script>
+        let frames = [];
+        let interval;
+        async function startCapture() {
+            frames = [];
+            const name = document.getElementById("name").value;
+            if (!name) return alert("Please enter your name");
+            
+            document.getElementById("status").innerText = "Capturing...";
+            const progressBar = document.getElementById("progress-bar");
+            progressBar.style.width = "0%";
+            
+            interval = setInterval(() => {
+                captureFrame(frames);
+                const progress = (frames.length / 15) * 100;
+                progressBar.style.width = progress + "%";
+                
+                if (frames.length >= 15) {
+                    clearInterval(interval);
+                    document.getElementById("status").innerText = "Processing...";
+                    
+                    fetch('/api/register_face', {
+                        method: 'POST',
+                        headers: { 'Content-Type': 'application/json' },
+                        body: JSON.stringify({ name: name, images: frames })
+                    })
+                    .then(res => res.json())
+                    .then(data => {
+                        document.getElementById("status").innerText = data.message;
+                    });
+                }
+            }, 500);
+        }
+        initWebcam("video");
+    </script>
+    
+    <!-- Add Font Awesome for icons -->
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.4/js/all.min.js"></script>
+</body>
+</html>

templates/register.html.bak

@@ -0,0 +1,59 @@
+<!-- register.html -->
+
+
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Face Attendance</title>
+</head>
+<body>
+    <h2>Welcome to Face Attendance System</h2>
+    <a href="/register">Register Face</a><br>
+    <a href="/mark">Mark Attendance</a>
+</body>
+</html>
+
+
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Register Face</title>
+</head>
+<body>
+    <h2>Register Face</h2>
+    <input type="text" id="name" placeholder="Enter name" required>
+    <button onclick="startCapture()">Start Capture</button>
+    <video id="video" width="300" autoplay></video>
+    <p id="status"></p>
+
+    <script src="/static/js/webcam.js"></script>
+    <script>
+        let frames = [];
+        let interval;
+        async function startCapture() {
+            frames = [];
+            const name = document.getElementById("name").value;
+            if (!name) return alert("Please enter name");
+            document.getElementById("status").innerText = "Capturing...";
+
+            interval = setInterval(() => {
+                captureFrame(frames);
+                if (frames.length >= 15) {
+                    clearInterval(interval);
+                    fetch('/api/register_face', {
+                        method: 'POST',
+                        headers: { 'Content-Type': 'application/json' },
+                        body: JSON.stringify({ name: name, images: frames })
+                    })
+                    .then(res => res.json())
+                    .then(data => {
+                        document.getElementById("status").innerText = data.message;
+                    });
+                }
+            }, 500);
+        }
+
+        initWebcam("video");
+    </script>
+</body>
+</html>