File size: 3,874 Bytes
9befc9d c69ec6c 9befc9d 67b481a d81f3c7 9befc9d c9b325d d5985cd d81f3c7 41cef17 d81f3c7 c9b325d d81f3c7 c9b325d d81f3c7 c9b325d d81f3c7 c9b325d d81f3c7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 |
from PIL import Image
import numpy as np
import cv2
import requests
import face_recognition
import os
from datetime import datetime
import streamlit as st
# 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.")
# Load images for face recognition
Images = []
classnames = []
directory = "photos"
myList = os.listdir(directory)
for cls in myList:
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])
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
encodeListknown = findEncodings(Images)
# Function to validate Aadhaar card number
def validate_aadhaar(aadhaar):
# Implement your Aadhaar card validation logic here
# For simplicity, let's assume any 4-digit number is a valid Aadhaar card
return len(aadhaar) == 4 and aadhaar.isdigit()
# Take picture using the camera and input Aadhaar card details
img_file_buffer = st.camera_input("Take a picture")
aadhaar_number = st.text_input("Enter Aadhaar Number:")
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
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].upper()
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)
if name != "Unknown":
# Update Aadhaar data
url = "https://attendanceviaface.000webhostapp.com"
url1 = "/update.php"
data1 = {'name': name, 'aadhaar': aadhaar_number}
response = requests.post(url + url1, data=data1)
if response.status_code == 200:
st.success("Data updated on: " + url)
else:
st.warning("Data not updated")
# 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.error("Invalid Aadhaar card number. Please enter a valid 4-digit Aadhaar number.")
|