Update app.py

app.py

@@ -6,7 +6,7 @@ import face_recognition
 import os
 from datetime import datetime
 import streamlit as st
-from streamlit_webrtc import VideoTransformerBase, webrtc_streamer
+import sqlite3
 
 # Set page title and description
 st.set_page_config(
@@ -16,7 +16,21 @@ st.set_page_config(
     initial_sidebar_state="collapsed"
 )
 st.title("Attendance System Using Face Recognition 📷")
-st.markdown("This app recognizes faces in a live camera feed, verifies Aadhaar card details, and updates attendance records with the current timestamp & Location.")
+st.markdown("This app recognizes faces in an image, verifies Aadhaar card details, and updates attendance records with the current timestamp & Location.")
+
+# Create or connect to the SQLite database
+conn = sqlite3.connect("attendance_database.db")
+cursor = conn.cursor()
+
+# Check if the 'faces' table exists, create it if not
+cursor.execute('''
+    CREATE TABLE IF NOT EXISTS faces (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        aadhaar TEXT,
+        encoding BLOB
+    )
+''')
+conn.commit()
 
 # Load images for face recognition
 Images = []
@@ -48,23 +62,16 @@ def validate_aadhaar(aadhaar):
     # For simplicity, let's assume any 4-digit number is a valid Aadhaar card
     return len(aadhaar) == 4 and aadhaar.isdigit()
 
-# Create a Streamlit component to capture images from the camera
-webrtc_ctx = webrtc_streamer(
-    key="example",
-    video_transformer_factory=None,  # No need for video transformation for this example
-    async_transform=True
-)
-
-# Main Streamlit app logic
-if webrtc_ctx.video_transformer:
-    st.sidebar.markdown("# Capture Image")
-    aadhaar_number = st.sidebar.text_input("Enter Aadhaar Number:")
-
-    # Use the camera feed to capture images
-    frame = webrtc_ctx.video_transformer.get_frame()
+# Take picture using the camera and input Aadhaar card details
+img_file_buffer = st.file_uploader("Upload an image", type=["jpg", "jpeg"])
+aadhaar_number = st.text_input("Enter Aadhaar Number:")
 
-    if frame is not None:
-        image = np.array(frame.to_image())
+# Face recognition code...
+if img_file_buffer is not None:
+    # Validate Aadhaar card number
+    if validate_aadhaar(aadhaar_number):
+        test_image = Image.open(img_file_buffer)
+        image = np.asarray(test_image)
 
         imgS = cv2.resize(image, (0, 0), None, 0.25, 0.25)
         imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
@@ -89,7 +96,8 @@ if webrtc_ctx.video_transformer:
                 cv2.putText(image, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
 
                 if name != "Unknown":
-                    url = "https://mrvishal7705.000webhostapp.com"
+                    # Update Aadhaar data
+                    url = "https://attendanceviaface.000webhostapp.com"
                     url1 = "/update.php"
                     data1 = {'name': name, 'aadhaar': aadhaar_number}
                     response = requests.post(url + url1, data=data1)
@@ -99,11 +107,19 @@ if webrtc_ctx.video_transformer:
                     else:
                         st.warning("Data not updated")
 
-        # Display the result
+                    # Store face encoding and Aadhaar number in the database
+                    face_encoding_bytes = pickle.dumps(encodeFace)
+                    cursor.execute("INSERT INTO faces (aadhaar, encoding) VALUES (?, ?)", (aadhaar_number, face_encoding_bytes))
+                    conn.commit()
+
+        # Apply styling with CSS
         st.markdown('<style>img { animation: pulse 2s infinite; }</style>', unsafe_allow_html=True)
         st.image(image, use_column_width=True, output_format="PNG")
 
         if name == "Unknown":
             st.info("Face not detected. Please try again.")
-else:
-    st.warning("Webcam not available. Please make sure your camera is connected and accessible.")
+    else:
+        st.error("Invalid Aadhaar card number. Please enter a valid 4-digit Aadhaar number.")
+
+# Close the database connection
+conn.close()