def add_person(people_folder):
person_name = input('What is the name of the new person: ').lower()
folder = people_folder + '/' + person_name
if not os.path.exists(folder):
input("I will now take 20 pictures. Press ENTER when ready.")
os.mkdir(folder)
video = VideoCamera()
detector = FaceDetector()
counter = 1
timer = 0
cv2.namedWindow('Video Feed', cv2.WINDOW_AUTOSIZE)
cv2.namedWindow('Saved Face', cv2.WINDOW_NORMAL)
while counter < 21:
frame = video.get_frame()
face_coord = detector.detect(frame)
if len(face_coord):
frame, face_img = oo.get_images(frame, face_coord)
if timer % 100 == 5:
cv2.imwrite(folder + '/' + str(counter) + '.jpg',
face_img[0])
print('Images Saved:' + str(counter))
counter += 1
cv2.imshow('Saved Face', face_img[0])
cv2.imshow('Video Feed', frame)
cv2.waitKey(50)
timer += 5
else:
print("This name already exists.")
sys.exit()
def get_all_cams(data, user_setup):
""" Returns four cameras """
return [
VideoCamera(user_setup[0], "640x360"),
VideoCamera(user_setup[1], "640x360"),
VideoCamera(user_setup[2], "640x360"),
VideoCamera(user_setup[3], "640x360")
]
def set_quad_cam(cam):
global data
chosenquadcam = int(cam)
if chosenquadcam > len(list_of_cam_objects["quad"]):
chosenquadcam = list_of_cam_objects["quad"][0]
data["cameras"].append(
VideoCamera(list_of_cam_objects["quad"][chosenquadcam - 1].fulladress))
data["cameras"].append(
VideoCamera(list_of_cam_objects["quad"][chosenquadcam - 1].fulladress))
data["cameras"].append(
VideoCamera(list_of_cam_objects["quad"][chosenquadcam - 1].fulladress))
data["cameras"].append(
VideoCamera(list_of_cam_objects["quad"][chosenquadcam - 1].fulladress))
def init_list_of_new_cameras(config):
""" Initiate the cameras """
result = {}
for cam in config:
result[cam[0]] = VideoCamera(cam)
return result
def set_quad_cam(data, user_setup):
""" Sets the chosen camera as quad cam with lower resolution """
result = []
for _ in range(4):
quad = VideoCamera(user_setup[data["single"]], "640x360")
result.append(quad)
return result
def choosecam(cam_nr):
""" choose cam middle route """
global data
print("Cam number: {}".format(cam_nr))
if cam_nr > 0:
data["selected_cam"] = cam_nr
data["camera_object"] = VideoCamera(
list_of_cam_objects["single"][cam_nr - 1].fulladress)
return render_template("index.html",
data=list_of_cam_objects["single"],
menu=3)
return render_template("index.html",
data=list_of_cam_objects["single"],
menu=2)
def video_feed():
return Response(gen(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def set_cam(cam):
global data
data["cameras"].append(
VideoCamera(list_of_cam_objects["single"][int(cam) - 1].fulladress))
def recognize_people(people_folder):
try:
people = [person for person in os.listdir(people_folder)]
except:
print("Have you added at least one person to the system?")
sys.exit()
print("This are the people in the Recognition System:")
for person in people:
print("-" + person)
start = time.time()
#choice = check_choice()
recognizer = None
detector = FaceDetector()
recognizer = cv2.face.createLBPHFaceRecognizer()
threshold = 91 #93
images = []
labels = []
labels_people = {}
for i, person in enumerate(people):
labels_people[i] = person
for image in os.listdir(people_folder + '/' + person):
images.append(cv2.imread(people_folder +'/'+ person + '/' + image, 0))
labels.append(i)
try:
recognizer.train(images, np.array(labels))
print("train model")
except:
print("\nOpenCV Error: Do you have at least two people in the database?\n")
sys.exit()
end = time.time()
print(end - start)
video = VideoCamera()
while True:
frame = video.get_frame()
faces_coord = detector.detect(frame)
if len(faces_coord):
frame, faces_img = oo.get_images(frame, faces_coord)
for i, face_img in enumerate(faces_img):
if __version__ == "3.1.0":
collector = cv2.face.MinDistancePredictCollector()
recognizer.predict(face_img, collector)
conf = collector.getDist()
pred = collector.getLabel()
else:
pred, conf = recognizer.predict(face_img)
print("Prediction: " + str(pred))
print('Confidence: ' + str(round(conf)))
print('Threshold: ' + str(threshold))
if conf < threshold:
cv2.putText(frame, labels_people[pred].capitalize(),
(faces_coord[i][0], faces_coord[i][1] - 2),
cv2.FONT_HERSHEY_PLAIN, 1.7, (206, 0, 209), 2,
cv2.LINE_AA)
else:
cv2.putText(frame, "Unknown",
(faces_coord[i][0], faces_coord[i][1]),
cv2.FONT_HERSHEY_PLAIN, 1.7, (206, 0, 209), 2,
cv2.LINE_AA)
cv2.putText(frame, "ESC to exit", (5, frame.shape[0] - 5),
cv2.FONT_HERSHEY_PLAIN, 1.2, (206, 0, 209), 2, cv2.LINE_AA)
cv2.imshow('Video', frame)
if cv2.waitKey(100) & 0xFF == 27:
sys.exit()