import cv2
import numpy as np
cam = cv2.VideoCapture(0)
detector=cv2.CascadeClassifier('Classifiers/face.xml')
i=0
offset=50

name_person = input('Enter registration number of person : ')

with open("id_count.txt", "r") as file:
    name = file.read()

with open("id_count.txt", "w") as file:
    file.write(str(int(name)+1))

with open("hash_faces.txt", "a") as file:
    file.write(name + " " + name_person + "\n")
    
while True:
    ret, im =cam.read()
    im = np.array(im, dtype=np.uint8)
    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
    faces=detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5, minSize=(100, 100), flags=cv2.CASCADE_SCALE_IMAGE)
    for(x,y,w,h) in faces:
        i=i+1
        cv2.imwrite("dataSet/face-"+name +'.'+ str(i) + ".jpg", gray[y-offset:y+h+offset,x-offset:x+w+offset])
        cv2.rectangle(im,(x-50,y-50),(x+w+50,y+h+50),(225,0,0),2)
        cv2.imshow('im',im[y-offset:y+h+offset,x-offset:x+w+offset])
        cv2.waitKey(100)
    if i>100:
        cam.release()
        cv2.destroyAllWindows()
        break

4047fca2e65e20bbd29234a911e2061d2c33a21c
<mask token>

<mask token>
with open('id_count.txt', 'r') as file:
    name = file.read()
with open('id_count.txt', 'w') as file:
    file.write(str(int(name) + 1))
with open('hash_faces.txt', 'a') as file:
    file.write(name + ' ' + name_person + '\n')
while True:
    ret, im = cam.read()
    im = np.array(im, dtype=np.uint8)
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    faces = detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5,
        minSize=(100, 100), flags=cv2.CASCADE_SCALE_IMAGE)
    for x, y, w, h in faces:
        i = i + 1
        cv2.imwrite('dataSet/face-' + name + '.' + str(i) + '.jpg', gray[y -
            offset:y + h + offset, x - offset:x + w + offset])
        cv2.rectangle(im, (x - 50, y - 50), (x + w + 50, y + h + 50), (225,
            0, 0), 2)
        cv2.imshow('im', im[y - offset:y + h + offset, x - offset:x + w +
            offset])
        cv2.waitKey(100)
    if i > 100:
        cam.release()
        cv2.destroyAllWindows()
        break

<mask token>
cam = cv2.VideoCapture(0)
detector = cv2.CascadeClassifier('Classifiers/face.xml')
i = 0
offset = 50
name_person = input('Enter registration number of person : ')
with open('id_count.txt', 'r') as file:
    name = file.read()
with open('id_count.txt', 'w') as file:
    file.write(str(int(name) + 1))
with open('hash_faces.txt', 'a') as file:
    file.write(name + ' ' + name_person + '\n')
while True:
    ret, im = cam.read()
    im = np.array(im, dtype=np.uint8)
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    faces = detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5,
        minSize=(100, 100), flags=cv2.CASCADE_SCALE_IMAGE)
    for x, y, w, h in faces:
        i = i + 1
        cv2.imwrite('dataSet/face-' + name + '.' + str(i) + '.jpg', gray[y -
            offset:y + h + offset, x - offset:x + w + offset])
        cv2.rectangle(im, (x - 50, y - 50), (x + w + 50, y + h + 50), (225,
            0, 0), 2)
        cv2.imshow('im', im[y - offset:y + h + offset, x - offset:x + w +
            offset])
        cv2.waitKey(100)
    if i > 100:
        cam.release()
        cv2.destroyAllWindows()
        break

import cv2
import numpy as np
cam = cv2.VideoCapture(0)
detector = cv2.CascadeClassifier('Classifiers/face.xml')
i = 0
offset = 50
name_person = input('Enter registration number of person : ')
with open('id_count.txt', 'r') as file:
    name = file.read()
with open('id_count.txt', 'w') as file:
    file.write(str(int(name) + 1))
with open('hash_faces.txt', 'a') as file:
    file.write(name + ' ' + name_person + '\n')
while True:
    ret, im = cam.read()
    im = np.array(im, dtype=np.uint8)
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    faces = detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5,
        minSize=(100, 100), flags=cv2.CASCADE_SCALE_IMAGE)
    for x, y, w, h in faces:
        i = i + 1
        cv2.imwrite('dataSet/face-' + name + '.' + str(i) + '.jpg', gray[y -
            offset:y + h + offset, x - offset:x + w + offset])
        cv2.rectangle(im, (x - 50, y - 50), (x + w + 50, y + h + 50), (225,
            0, 0), 2)
        cv2.imshow('im', im[y - offset:y + h + offset, x - offset:x + w +
            offset])
        cv2.waitKey(100)
    if i > 100:
        cam.release()
        cv2.destroyAllWindows()
        break

import cv2
import numpy as np
cam = cv2.VideoCapture(0)
detector=cv2.CascadeClassifier('Classifiers/face.xml')
i=0
offset=50

name_person = input('Enter registration number of person : ')

with open("id_count.txt", "r") as file:
    name = file.read()

with open("id_count.txt", "w") as file:
    file.write(str(int(name)+1))

with open("hash_faces.txt", "a") as file:
    file.write(name + " " + name_person + "\n")
    
while True:
    ret, im =cam.read()
    im = np.array(im, dtype=np.uint8)
    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
    faces=detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5, minSize=(100, 100), flags=cv2.CASCADE_SCALE_IMAGE)
    for(x,y,w,h) in faces:
        i=i+1
        cv2.imwrite("dataSet/face-"+name +'.'+ str(i) + ".jpg", gray[y-offset:y+h+offset,x-offset:x+w+offset])
        cv2.rectangle(im,(x-50,y-50),(x+w+50,y+h+50),(225,0,0),2)
        cv2.imshow('im',im[y-offset:y+h+offset,x-offset:x+w+offset])
        cv2.waitKey(100)
    if i>100:
        cam.release()
        cv2.destroyAllWindows()
        break
