Upload app.py

app.py

@@ -0,0 +1,175 @@
+import streamlit as st
+import cv2
+import face_recognition
+import os
+from datetime import datetime
+import sqlite3
+import pandas as pd
+import numpy as np
+from PIL import Image
+
+# --- App Configuration ---
+st.set_page_config(
+    page_title="Face Recognition Attendance",
+    page_icon="✅",
+    layout="wide"
+)
+
+# --- Database Connection ---
+conn = sqlite3.connect('attendance.db')
+cursor = conn.cursor()
+
+# --- Create Attendance Table (if not exists) ---
+cursor.execute('''
+    CREATE TABLE IF NOT EXISTS attendance (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        name TEXT,
+        roll_no TEXT,
+        date TEXT,
+        time TEXT,
+        status TEXT 
+    )
+''')
+conn.commit()
+
+# --- Load Known Faces ---
+def load_known_faces():
+    """Loads known faces from the 'Photos' directory."""
+    images = []
+    classnames = []
+    directory = "Photos"
+
+    for cls in os.listdir(directory):
+        if os.path.splitext(cls)[1] in [".jpg", ".jpeg"]:
+            img_path = os.path.join(directory, cls)
+            curImg = cv2.imread(img_path)
+            images.append(curImg)
+            classnames.append(os.path.splitext(cls)[0])
+
+    return images, classnames
+
+# --- Encode Known Faces ---
+def find_encodings(images):
+    """Encodes the given images."""
+    encodeList = []
+    for img in images:
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        encode = face_recognition.face_encodings(img)[0]
+        encodeList.append(encode)
+    return encodeList
+
+# --- Load and Encode Known Faces ---
+Images, classnames = load_known_faces()
+encodeListKnown = find_encodings(Images)
+
+# --- Add New Face ---
+def add_new_face():
+    """Adds a new face to the system."""
+    new_name = st.text_input("Enter your name:")
+    roll_no = st.text_input("Enter your roll number:")
+
+    img_file_buffer = st.camera_input("Take a picture")
+    if img_file_buffer is not None and new_name and roll_no:
+        image = np.array(Image.open(img_file_buffer))  # Convert to numpy array
+        img_path = os.path.join("Photos", f"{new_name}_{roll_no}.jpg")
+        cv2.imwrite(img_path, image)
+
+        # Update known faces and encodings
+        global Images, classnames, encodeListKnown
+        Images, classnames = load_known_faces()
+        encodeListKnown = find_encodings(Images)
+
+        # Add to database (without updating attendance)
+        date = datetime.now().strftime('%Y-%m-%d')
+        time = datetime.now().strftime('%H:%M:%S')
+        cursor.execute("INSERT INTO attendance (name, roll_no, date, time, status) VALUES (?, ?, ?, ?, 'Registered')", 
+                       (new_name, roll_no, date, time))
+        conn.commit()
+
+        st.success(f"New face added for {new_name} ({roll_no}).")
+
+# --- Face Recognition ---
+def recognize_face():
+    """Performs face recognition and updates attendance."""
+    img_file_buffer = st.camera_input("Take a picture")
+    if img_file_buffer is not None:
+        with st.spinner("Recognizing face..."):
+            image = np.array(Image.open(img_file_buffer))  # Convert to numpy array
+            imgS = cv2.resize(image, (0, 0), None, 0.25, 0.25)
+            imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
+            facesCurFrame = face_recognition.face_locations(imgS)
+            encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)
+
+            name = "Unknown"
+            roll_no = "Unknown"
+
+            if len(encodesCurFrame) > 0:
+                for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
+                    matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
+                    faceDis = face_recognition.face_distance(encodeListKnown, encodeFace)
+                    matchIndex = np.argmin(faceDis)
+
+                    if matches[matchIndex]:
+                        name = classnames[matchIndex].split("_")[0]
+                        roll_no = classnames[matchIndex].split("_")[1]
+
+                    y1, x2, y2, x1 = faceLoc
+                    y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
+                    cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2)
+                    cv2.rectangle(image, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
+                    cv2.putText(image, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
+
+                    # Check for duplicate attendance entries
+                    date = datetime.now().strftime('%Y-%m-%d')
+                    time = datetime.now().strftime('%H:%M:%S')
+                    cursor.execute("SELECT * FROM attendance WHERE name=? AND date=? AND time=?", (name, date, time))
+                    existing_attendance = cursor.fetchone()
+
+                    if existing_attendance:
+                        st.info(f"Attendance already recorded for {name} at {time}.")
+                    else:
+                        # Allow manual marking of attendance
+                        status = st.radio("Mark Attendance:", ("Present", "Absent"))
+                        cursor.execute("INSERT INTO attendance (name, roll_no, date, time, status) VALUES (?, ?, ?, ?, ?)", 
+                                       (name, roll_no, date, time, status))
+                        conn.commit()
+                        st.success(f"Attendance updated for {name} at {time} ({status}).")
+
+            st.image(image, caption="Detected Face", use_container_width=True)
+            if name == "Unknown":
+                st.info("Face not recognized.")
+
+# --- View Attendance Records ---
+def view_attendance_records():
+    """Displays attendance records."""
+    st.subheader("Attendance Records")
+    cursor.execute("SELECT * FROM attendance ORDER BY date DESC, time DESC")
+    records = cursor.fetchall()
+
+    if records:
+        df = pd.DataFrame(records, columns=["ID", "Name", "Roll No", "Date", "Time", "Status"])
+        st.table(df)
+    else:
+        st.info("No attendance records available.")
+
+# --- Main App Logic ---
+if __name__ == "__main__":
+    st.title("Face Recognition Attendance")
+
+    # --- Password Protection (Optional) ---
+    password = st.text_input("Enter password", type="password")
+    if password != "123":
+        st.stop()
+
+    # --- App Sections ---
+    app_mode = st.sidebar.selectbox("Select Mode", ["Recognize", "Add New Face", "View Records"])
+
+    if app_mode == "Recognize":
+        recognize_face()
+    elif app_mode == "Add New Face":
+        add_new_face()
+    elif app_mode == "View Records":
+        view_attendance_records()
+
+# --- Close Database Connection ---
+conn.close()