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test2.py
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test2.py
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import cv2
import streamlit as st
from fastapi import FastAPI
import face_recognition
import numpy as np
import time
import os
from fastapi.responses import StreamingResponse
app = FastAPI()
from face_recognition import face_locations, face_encodings
from firebase_admin import db ,credentials
import firebase_admin
imagepath="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures"
piclepath="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/encodings.pickle"
firbaseurl="https://database-faceapp-default-rtdb.asia-southeast1.firebasedatabase.app/"
servicekey="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/settings/serviceAccountKey.json"
cred=credentials.Certificate(servicekey)
firebase_admin.initialize_app(cred,{
'databaseURL': f'{firbaseurl}',
'storageBucket': 'database-faceapp.appspot.com',
})
path="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures/222156259.jpeg"
img=cv2.imread(path)
encodex=face_encodings(img)[0]
print(encodex)
@st.cache_resource
def get_cap():
return 0
def detect_and_recognize_face(frame,encode):
# Convert frame to RGB for face recognition
cut_frame=cv2.resize(frame,(0,0),None,0.25,0.25)
rgb_frame = cv2.cvtColor(cut_frame, cv2.COLOR_BGR2RGB)
frameencode=face_encodings(rgb_frame)
# Find all faces and their encodings
face_locations_list = face_locations(rgb_frame)
currentfaceencode = face_encodings(frameencode, face_locations_list)
if face_locations_list:
# Loop through each detected face
for face_encoding, face_location in zip(currentfaceencode, face_locations_list):
# Compare face encoding with encodings in database/pickle file
matches = face_recognition.compare_faces(encode, face_encoding)
facedistance=face_recognition.face_distance(encode,face_encoding)
print(facedistance)
name = "Unknown"
matchindex=np.argmin(facedistance)
print(matchindex)
# Draw rectangle and name around the face
top, right, bottom, left = face_location
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
cv2.putText(frame, name, (left + 6, top - 6), cv2.FONT_HERSHEY_DUPLEX, 0.8, (255, 255, 255), 1)
return frame
def generate_frames():
cap=cv2.VideoCapture("https://192.168.0.100:8080/video")
cap.set(3,640)
cap.set(4,480)
while True:
success, frame = cap.read() # read the camera frame
frame=detect_and_recognize_face(frame,encode=encodex)
if not success:
break
ret, buffer = cv2.imencode('.jpg', frame)
frame = buffer.tobytes()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
# save_image=cv2.imwrite(os.path.join(/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/screens)"test.jpg",x)
# def video_feed():
# cap = get_cap() # 0 for default webcam
# return StreamingResponse(generate_frames(cap), media_type="multipart/x-mixed-replace; boundary=frame")
@app.get("/")
async def home():
return {"message":"Welcome to the Live Attendance System"}
@app.get("/video_feed")
async def video_feed():
return StreamingResponse(generate_frames(), media_type="multipart/x-mixed-replace;boundary=frame")
def main():
app.run()
if __name__ == '__main__':
import uvicorn
uvicorn.run(app, host="localhost", port=8000)