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sample_generator.py
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sample_generator.py
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import cv2
import os
from login import Login_Window
def take_samples():
# newpath = r"C:\\Users\\santo\\OneDrive\\Documents\\PythonFiles\\Python_Projects\\Face_login\\samples"
newpath = r"samples"
if not os.path.exists(newpath):
os.makedirs(newpath)
cam = cv2.VideoCapture(0, cv2.CAP_DSHOW) # capturing vdo through Laptop webcam
cam.set(3, 640) # setting vdo Frame Width
cam.set(4, 480) # setting vdo Frame Height
detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# Haar Cascade classifier is used as an effective Object Detection approach
face_id = 1
# Use integer ID for every new face(0,1,2,3,....)
print("Taking samples, look at camera....")
count = 0 # initializing sampling face count
while True:
ret, img = cam.read() # read the faces using the above created object
# converting img into grayscale
converted_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = detector.detectMultiScale(converted_image, 1.3, 5)
for (x, y, w, h) in faces:
# drawing rectangle around detected face
cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
count += 1
cv2.imwrite("samples/face."+str(face_id)+"."+str(count) +
".jpg", converted_image[y:y+h, x:x+w])
# to capture and save imgs into the dataset folder
cv2.imshow('image', img) # used to display img in window
k = cv2.waitKey(100) & 0xff # Waits for a pressed key
if k == 27: # press esc key to stop
break
elif count >= 50: # taking 50 samples (More samples give more accuracy)
break
print("Samples taken successfully. Now closing the program")
cam.release()
cv2.destroyAllWindows()