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import numpy as np | |
import cv2 | |
import requests | |
import face_recognition | |
import os | |
from datetime import datetime | |
import streamlit as st | |
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]) | |
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') | |
cap = cv2.VideoCapture(0) # Use 0 for the default camera | |
while True: | |
ret, frame = cap.read() | |
frame = cv2.flip(frame, 1) # Flip horizontally | |
st.image(frame) | |
if ret: | |
imgS = cv2.resize(frame, (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) | |
matchIndex = np.argmin(faceDis) | |
if matches[matchIndex]: | |
name = classnames[matchIndex] | |
st.write(name) | |
y1, x2, y2, x1 = faceLoc | |
y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4 | |
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2) | |
cv2.rectangle(frame, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED) | |
cv2.putText(frame, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2) | |
# Sending data to a URL | |
url = "https://kiwi-whispering-plier.glitch.me/update" | |
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") | |
st.image(image) | |
if bytes_data is None: | |
st.stop() | |