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recog.py
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recog.py
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import cv2
import numpy as np
import serial
cascadePath = "haarcascade_frontalface_default.xml"
cam = cv2.VideoCapture(0)
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("recognizer\\trainningData.yml")
faceCascade = cv2.CascadeClassifier(cascadePath)
font = cv2.FONT_HERSHEY_SIMPLEX
id = 0
names = ['vikas', 'naman', 'none', 'Ilza', 'Z', 'W']
#minW = 0.1 * cam.get(3)
#minH = 0.1 * cam.get(4)
arduino = serial.Serial('COM14', 9600) # Change 'COM14' to the correct port for your Arduino
while True:
ret, img = cam.read()
img = cv2.flip(img, 1)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2, # Adjust this value
minNeighbors=5, # Adjust this value
# 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])
if confidence > 60:
detected_name = names[id]
confidence = " {0}%".format(round(confidence))
if detected_name == 'naman':
try:
arduino.write(b'1') # Signal to turn on the LED
except Exception as e:
print(f"Error communicating with Arduino: {e}")
else:
detected_name = "Unknown"
confidence = " {0}%".format(round(confidence))
cv2.putText(img, str(detected_name), (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)
k = cv2.waitKey(10) & 0xff
if k == 27:
break
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()
arduino.close()