Michael-BJ / Smart-CCTV-Using-Machine-Learning

Smart CCTV that uses a telegram bot and speaker to recognize a person's face and issue an alert if the face is not recognized.

Smart CCTV Using Machine Learning

How it's works ?

1. First install library that we need

pip install opencv-python   
pip install numpy
pip install face-recognition
pip install pyttsx3 
pip install telepot

2. Capture the face that you want to recognize

import cv2

cap = cv2.VideoCapture(0)

while True:
    _, frame = cap.read()
    cv2.imshow('take a picture ',frame)
    if cv2.waitKey(1) & 0xFF == ord('y') :
        cv2.imwrite('my_picture.jpg', frame)
        break

cap.release()
cv2.destroyAllWindows()

3. Connect the program to your webcam

import cv2
import numpy as np

cap = cv2.VideoCapture(0)
while True:
    _, frame = cap.read()
    cv2.imshow('just face', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

4. Load the image that you want to recognize

etcodetech_image = face_recognition.load_image_file("etcodetech.jpg")
etcodetech_face_encoding = face_recognition.face_encodings(etcodetech_image)[0]

known_face_encoding = [
    etcodetech_face_encoding
]
known_face_names = [
    "etcodetech"
]

5. Download the model of face and load to the program

faceDetect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

6. For identification the picture or video change into gray

while True:
    _, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = faceDetect.detectMultiScale(gray, 1.3,5)

7. Change BGR to RGB

 rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    encodings = face_recognition.face_encodings(rgb)
    names = []

8. Compare the known face and unknown face

for encoding in encodings:
        matches = face_recognition.compare_faces(known_face_encoding,
        encoding)
        name = "Unknown"

        if True in matches:
            matchedIdxs = [i for (i, b) in enumerate(matches) if b]
            counts = {}
            for i in matchedIdxs:
                best_match_index = np.argmin(matches)
                name = known_face_names[best_match_index]
                counts[name] = counts.get(name, 0) + 1
            name = max(counts, key=counts.get)
        names.append(name)

9. Put the text (name) and rectangle to the picture or video

for ((x, y, w, h), name) in zip(faces, names):
    cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
    cv2.putText(frame, name, (x, y), cv2.FONT_HERSHEY_SIMPLEX,
    0.75, (0, 255, 0), 2)`

10. Connect the program to the speaker

engine = pyttsx3.init() 
if matches [0] == True:
    engine.say("Wellcome home etcodetech") 
else:
    engine.say("Who are you ? i don't know you")
    engine.say("Please go back later")
engine.runAndWait()   

11. Capture the picture and send to the bot telegram

bot = telepot.Bot('insert your token')
if matches [0] == True:
    engine.say("Wellcome home etcodetech") 
    cv2.imwrite("family.jpg", frame)
    bot.sendPhoto('insert your chat id', photo=open('family.jpg', 'rb'))
else:
    engine.say("Who are you ? i don't know you")
    engine.say("Please go back later")
    cv2.imwrite("guest.jpg", frame)
    bot.sendPhoto('insert your chat id', photo=open('guest.jpg', 'rb'))
engine.runAndWait()       

Demo

Clik the picture to see the Video