def main():
capture_images()
aligned = facenet.align_face(images)
comparisons = facenet.compare(aligned)
print("Is image 1 and 2 similar? ", bool(comparisons[0][1]))
print("Is image 1 and 3 similar? ", bool(comparisons[0][2]))
from easyfacenet.simple import facenet
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
images = [
'images/adi.jpeg', 'images/state.jpeg', 'images/state2.jpeg',
'images/erik.jpeg', 'images/state3.jpeg'
]
aligned = facenet.align_face(images)
comparisons = facenet.compare(aligned)
print("Is image ADI and ERIK similar? ", bool(comparisons[0][3]))
print("Is image STATE and ERIK similar? ", bool(comparisons[1][3]))
print("Is image STATE and STATE2 similar? ", bool(comparisons[1][2]))
print("Is image STATE and STATE3 similar? ", bool(comparisons[1][4]))
'haarcascades/haarcascade_frontalface_default.xml')
eye_cascade = cv.CascadeClassifier('haarcascades/haarcascade_eye.xml')
name = ["Adan", "Erick", "Python", "Geras"]
cap = cv.VideoCapture(0)
while True:
_, frame = cap.read()
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
face = frame[y - 10:y + h + 10, x - 10:x + w + 10]
cv.imwrite("images/face.jpg", face)
if cv.waitKey(1) & 0xFF == ord('q'):
for i in range(4):
nombre = "images/" + str(name[i]) + ".jpeg"
images = ["images/face.jpg", nombre]
aligned = facenet.align_face(images)
comparar = facenet.compare(aligned)
if bool(comparar[0][1]):
print(name[i])
break
cv.imshow('frame', frame)
if cv.waitKey(10) == 27:
break
cap.release()
cv.destroyAllWindows()
np.load = np_load_old