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faceRecognizer.py
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import cv2
import numpy as np
import time
import sqlite3 as lite
from paths import getHaarcascadePath
from lock import openLock
def faceRecognizer():
con = lite.connect("users.db")
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer/trainer.yml')
cascadePath = getHaarcascadePath()
faceCascade = cv2.CascadeClassifier(cascadePath);
font = cv2.FONT_HERSHEY_SIMPLEX
#iniciate id counter
id = 0
# Initialize and start realtime video capture
cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video widht
cam.set(4, 480) # set video height
# Define min window size to be recognized as a face
minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)
startTime = time.time()
while True:
recogPercent = None
ret, img = cam.read()
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor = 1.2,
minNeighbors = 5,
minSize = (int(minW), int(minH)),
)
for(x,y,w,h) in faces:
cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)
id, confidence = recognizer.predict(gray[y:y+h,x:x+w])
# Check if confidence is less them 100 ==> "0" is perfect match
if (confidence < 100):
name = "user"
with con:
cur = con.cursor()
cur.execute("SELECT * FROM users WHERE id=:Id", {"Id": id})
con.commit()
row = cur.fetchone()
name = row[1]
#id = names[id]
id = name
recogPercent = round(100 - confidence)
confidence = " {0}%".format(round(100 - confidence))
else:
id = "unknown"
confidence = " {0}%".format(round(100 - confidence))
cv2.putText(img, str(id), (x+5,y-5), font, 1, (255,255,255), 2)
cv2.putText(img, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 1)
cv2.imshow('camera',img)
if(recogPercent != None and recogPercent > 50):
openLock()
break
if(time.time() - startTime > 30):
break
k = cv2.waitKey(10) & 0xff # Press 'ESC' for exiting video
if k == 27:
break
# Do a bit of cleanup
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()