Update app.py

app.py

@@ -1,92 +1,132 @@
-from keras.models import load_model
 from PIL import Image
 import numpy as np
-import cv2 
+import cv2
 import requests
-
 import face_recognition
 import os
-from datetime import datetime
+import streamlit as st
 
-#the following are to do with this interactive notebook code
-from matplotlib import pyplot as plt # this lets you draw inline pictures in the notebooks
-import pylab # this allows you to control figure size 
-pylab.rcParams['figure.figsize'] = (10.0, 8.0) # this controls figure size in the notebook
+# Set page title and description
+st.set_page_config(
+    page_title="Aadhaar Based Face Recognition Attendance System",
+    page_icon="📷",
+    layout="centered",
+    initial_sidebar_state="collapsed"
+)
+st.title("Attendance System Using Face Recognition 📷")
+st.markdown("This app recognizes faces in an image, verifies Aadhaar card details, and updates attendance records with the current timestamp.")
 
-import io
-import streamlit as st
-bytes_data=None
+# Load images for face recognition
+Images = []   # List to store Images
+classnames = []  # List to store classnames
+aadhar_numbers = []  # List to store Aadhaar numbers
+
+directory = "photos"
+myList = os.listdir(directory)
 
-Images = []
-classnames = []
-myList = os.listdir()
-#st.write(myList)
 for cls in myList:
-    if os.path.splitext(cls)[1] == ".jpg"  :
-        curImg = cv2.imread(f'{cls}')
+    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])
-st.write(classnames)
+        # Assume Aadhaar number is part of the image filename (e.g., "123456_john.jpg")
+        aadhar_numbers.append(cls.split('_')[0])
 
+# Function to validate Aadhaar card number
+def validate_aadhaar(aadhaar):
+    # Implement your Aadhaar card validation logic here
+    # For simplicity, let's assume any 6-digit number is a valid Aadhaar card
+    return len(aadhaar) == 6 and aadhaar.isdigit()
 
-def findEncodings(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
+# Function to update Aadhaar data
+def update_data(name, aadhaar_number):
+    url = "https://attendanceviaface.000webhostapp.com"
+    url1 = "/update.php"
+    data = {'name': name, 'aadhaar': aadhaar_number}
+    response = requests.post(url + url1, data=data)
+    
+    if response.status_code == 200:
+        st.success("Data updated on: " + url)
+    else:
+        st.warning("Data not updated")
 
+# Function to display image with overlay
+def display_image_with_overlay(image, name):
+    # Add overlay to the image (e.g., bounding box and name)
+    # ...
 
-encodeListknown = findEncodings(Images)
-st.write('Encoding Complete')
+    # 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")
 
-img_file_buffer=st.camera_input("Take a picture")
-if img_file_buffer is not None:
-     
-     test_image = Image.open(img_file_buffer)
-     st.image(test_image, use_column_width=True)
-     
-     image = np.asarray(test_image)
+# Take input Aadhaar card details
+aadhaar_number = st.text_input("Enter your Last 6-digits Aadhaar Number:")
     
-     #########################
-     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)
-
-     for encodeFace,faceLoc in zip(encodesCurFrame,facesCurFrame):
-         matches = face_recognition.compare_faces(encodeListknown,encodeFace)
-         faceDis = face_recognition.face_distance(encodeListknown,encodeFace)
-         #print(faceDis)
-         matchIndex = np.argmin(faceDis)
-
-         if matches[matchIndex]:
-             name = classnames[matchIndex].upper()
-             st.write(name)
-             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)
-
-             ##############
-             url = "https://rgiattendance.000webhostapp.com" 
-             url1 = "/update.php"
-             data1 =  {'name':name }
-             response = requests.post(url+url1, data=data1)
-
-             # # https://aimljul23f.glitch.me/fsave?nm=testname
-             # url = "https://aimljul23f.glitch.me/" 
-             # url1 = "fsave?nm=" + name 
-             # # data1 =  {'name':name   } 
-             # response = requests.post(url+url1)
-             
-             if response.status_code == 200 : 
-                 st.write(" data updated on : " + url)
-             else : st.write("data NOT updated " + url+url1)
-                 
-     ##############################
-     st.image(image)
-if bytes_data is None:
-     st.stop()
+# Take picture using the camera 
+img_file_buffer = st.camera_input("Take a picture")
+
+# Load images for face recognition
+encodeListknown = [face_recognition.face_encodings(img)[0] for img in Images]
+
+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)
+        facesCurFrame = face_recognition.face_locations(imgS)
+        encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)
+
+        name = "Unknown"  # Default name for unknown faces
+        match_found = False  # Flag to track if a match is found
+
+        # Checking if faces are detected
+        if len(encodesCurFrame) > 0:
+            for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
+                # Assuming that encodeListknown is defined and populated in your code
+                matches = face_recognition.compare_faces(encodeListknown, encodeFace)
+                faceDis = face_recognition.face_distance(encodeListknown, encodeFace)
+                matchIndex = np.argmin(faceDis)
+
+                if matches[matchIndex]:
+                    name = classnames[matchIndex].upper()
+                    
+                    # Check if Aadhaar number is found in the database
+                    if aadhaar_number not in aadhar_numbers:
+                        st.error("Face recognized, but Aadhaar number not found in the database.")
+                    else:
+                        # Update data only if a known face is detected and Aadhaar number is valid
+                        update_data(name, aadhaar_number)
+                        match_found = True  # Set the flag to True
+                    
+                else:
+                    # Face recognized, but not matched with Aadhaar number
+                    st.error("Face recognized, but Aadhaar number does not match.")
+
+                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)
+
+            display_image_with_overlay(image, name)
+
+            # Display the name corresponding to the entered Aadhaar number
+            if not match_found:
+                # Match Aadhaar number with the list
+                aadhar_index = aadhar_numbers.index(aadhaar_number) if aadhaar_number in aadhar_numbers else None
+                if aadhar_index is not None:
+                    st.success(f"Match found: {classnames[aadhar_index]}")
+                else:
+                    st.warning("Face not detected, and Aadhaar number not found in the database.")
+            else:
+                st.success(f"Face recognized: {name}")
+
+        else:
+            st.warning("No faces detected in the image. Face recognition failed.")
+
+    else:
+        st.error("Invalid Aadhaar card number. Please enter a valid 6-digit Aadhaar number.")