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import os
import cv2
import numpy as np
from PIL import Image
import face_recognition
import streamlit as st
import requests
# Set up Streamlit
st.title("Face Recognition App")
# Load images from the current directory
Images = []
classnames = []
myList = os.listdir()
for cls in myList:
if os.path.splitext(cls)[1] == ".jpg":
curImg = cv2.imread(f'{cls}')
Images.append(curImg)
classnames.append(os.path.splitext(cls)[0])
# Function to find face encodings
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)
st.write('Encoding Complete')
# Take a picture using Streamlit camera input
img_file_buffer = st.camera_input("Take a picture")
# Check if an image was taken
if img_file_buffer is not None:
test_image = Image.open(img_file_buffer)
st.image(test_image, use_column_width=True)
# Convert the image to numpy array
image = np.asarray(test_image)
# Resize image
imgS = cv2.resize(image, (0, 0), None, 0.25, 0.25)
imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
# Find face locations and encodings
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)
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)
# Update data using requests
url = "https://rgiattendance.000webhostapp.com/update.php"
data1 = {'name': name}
response = requests.post(url, data=data1)
if response.status_code == 200:
st.write("Data updated on: " + url)
else:
st.write("Data NOT updated " + url)
st.image(image)
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