ChikonEyeX2.py

"""
ChikonEye literally watches your back.
preventing others who peeps your computer from seeing your valuable secret works.
Now your works are safe and secure.

Chikon eye uses your laptop(primary = 0 or secondary = 1, 2 so on) camera to see how 
many people are watching at the computer screen. If some1 unauthorized tries to see 
it automatically locks the computer screen.

developed by Ashraf Minhaj
mail me at- ashraf_minhaj@yahoo.com
"""
"""
Version: 2.0 (all codes in one .py file).
Update: 7th April 2019
No need to input parent folder path. The code finds the parent path
by itself.

Contains: 1. Dataset Creator (take photo and create a dataset)
          2. Tariner    (training your model)
          3. Recognizer (the code that recognizes you)
          4. Amazingly with GUI support (makes this code more user friendly)
"""
"""
I'll make and executable .exe file so that this can be run on any computer.
right now it can be used by the people who has python, numpy, opencv, pyautogui
and pillow installed in their pc. Don't worry exe is coming soon.
"""

#__ Press 'q' to quit or stop the program



import cv2  
import numpy as np
import pyautogui
from time import sleep
from PIL import Image  #pip install packages
import os

#location of opencv haarcascade <change according to your file location>
face_cascade = cv2.CascadeClassifier('F:\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt2.xml') 
cap = cv2.VideoCapture(0)   # 0 = main camera , 1 = extra connected webcam and so on.
rec = cv2.face.LBPHFaceRecognizer_create()

#the path where the code is saved
pathz = os.path.dirname(os.path.abspath(__file__)) #get path of the software

dir_path = f"{pathz}\\dataSet"


#___make a path named dataSet
try:
    os.mkdir(dir_path)
except OSError:
    print("Folder exists or Error!")
else:
    print("created")


#recogizer module
def recog():
    """ Recognizes people from the pretrained .yml file """
    #print("Starting")
    rec.read(f"{pathz}\\chikoneye.yml")  #yml file location <change as yours>
    id = 0  #set id variable to zero

    font = cv2.FONT_HERSHEY_COMPLEX 
    col = (255, 0, 0)
    strk = 2 

    while True:  #This is a forever loop
        ret, frame = cap.read() #Capture frame by frame 
    
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) #change color from BGR to Gray
        faces = face_cascade.detectMultiScale(gray, scaleFactor = 1.5, minNeighbors = 5)

        #print(faces)
        for(x, y, w, h) in faces:
            #print(x, y, w, h)
            roi_gray = gray[y: y+h, x: x+w]  #region of interest is face

            #*** Drawing Rectangle ***
            color = (255, 0, 0)
            stroke = 2
            end_cord_x = x+w
            end_cord_y = y+h
            cv2.rectangle(frame, (x,y), (end_cord_x, end_cord_y), color, stroke)

            #***detect
            id, conf = rec.predict(roi_gray)
            #cv2.putText(np.array(roi_gray), str(id), font, 1, col, strk)
            print(id) #prints the id's
        
            #if sees unauthorized person
            if id != 1: 
                #execute lock command
                pyautogui.hotkey('win', 'r')   #win + run key combo
                pyautogui.typewrite("cmd\n")   # type cmd and 'Enter'= '\n'
                sleep(0.500)       #a bit delay <needed!>
                #windows lock code to command prompt and hit 'Enter'
                pyautogui.typewrite("rundll32.exe user32.dll, LockWorkStation\n") 
            
            """
            elif id == 1:      #if authorized person (me & my Brother Siam)
                print("Authorized Person\n") #do nothing
            """

        
    
        cv2.imshow('ChikonEye', frame)

        #check if user wants to quit the program (pressing 'q')
        if cv2.waitKey(10) == ord('q'):
            op = pyautogui.confirm("Close the Program 'ChikonEye'?") 
            if op == 'OK':
                print("Out")
                break
            
                

    cap.release()
    cv2.destroyAllWindows() #remove all windows we have created




#create dataset and train the model
def data_Train():
    sampleNum = 0
    #print("Starting training")
    id = pyautogui.prompt(text="""
    Enter User ID.\n\nnote: numeric data only 1 2 3 etc.""", title='ChikonEye', default='none')
    #check for user input
    
    """
    if id >  :
        print(id)
        pyautogui.alert(text='WRONG INPUT',title='ChikonEye',button='Back')
        recog()
    """

    #if user input is 1 2 or 3  
    if int(id) < 0:
        pyautogui.alert(text='WRONG INPUT',title='ChikonEye',button='Back')

    elif int(id) > 0:
        while True:
            ret, img = cap.read()  
            gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
            faces = face_cascade.detectMultiScale(gray, 1.3, 5)

            for(x, y, w, h) in faces: #find faces
                sampleNum = sampleNum + 1  #increment sample num till 21
                cv2.imwrite(f'{pathz}\\dataSet\\User.{id}.{sampleNum}.jpg', gray[y: y+h, x: x+w]) #uncomment this
                cv2.rectangle(img, (x,y), (x+w, y+h), (255,0,0), 4)
                cv2.waitKey(100)

            cv2.imshow('faces', img)  #show image while capturing
            cv2.waitKey(1)
            if(sampleNum > 20): #21 sample is collected
                break   
            
    trainer()  #Train the model based on new images

    recog() #start recognizing
            


#Trainer 
def trainer():
    faces = []   #empty list for faces
    Ids = [] #empty list for IDs

    path = dir_path

    #gets image id with path
    def getImageWithID(path):
        imagePaths = [os.path.join(path,f) for f in os.listdir(path)]
        #print(f"{imagePaths}\n")
    
        for imagePath in imagePaths:
            faceImg = Image.open(imagePath).convert('L')
            #cv2.imshow('faceImg', faceImg)
            faceNp = np.array(faceImg, 'uint8')
            ID = int(os.path.split(imagePath)[-1].split('.')[1])
            #print(ID)
            faces.append(faceNp)
            Ids.append(ID)

            cv2.waitKey(10)

        return Ids, faces


    ids, faces = getImageWithID(path)

    print(ids, faces)
    rec.train(faces, np.array(ids))
    #create a yml file at the folder. WIll be created automatically.
    rec.save(f'{pathz}\\chikoneye.yml')   
    pyautogui.alert("Done Saving.\nPress OK to continue")
    cv2.destroyAllWindows()
    



#Options checking
opt =pyautogui.confirm(text= 'Chose an option', title='ChikonEye', buttons=['START', 'Train', 'Exit'])
if opt == 'START':
    #print("Starting the app")
    recog()
    
if opt == 'Train':
    opt = pyautogui.confirm(text="""
    Please look at the Webcam.\nTurn your head a little while capturing.\nPlease add just one face at a time.
    \nClick 'Ready' when you're ready.""", title='ChikonEye', buttons=['Ready', 'Cancel'])
        
    if opt == 'Ready':
            #print("Starting image capture + Training")
            data_Train()
    if opt == 'Cancel':
        print("Cancelled")
        recog()
        

if opt == 'Exit':
    print("Quit the app")