def del_buff(i):
answer, person_buf = db.search_person("bufer")
if answer:
for f in person_buf.face:
db.del_face(f)
FaceAlgo.clear_noname()
def onPaste():
global listbox_faces, person
# переносим из bufer в выбранный профиль
answer, person_buf = db.search_person("bufer")
if answer:
for f in person_buf.face:
db.set_face(person, f)
refesh_persone()
def onPaste(person):
global listbox_faces
# переносим из bufer в выбранный профиль
answer, person_buf = db.search_person("bufer")
if answer:
for f in person_buf.face:
db.set_face(person, f)
WindowfPersonRefresh(person)
def delEmptyFaces():
print("Загружаем данные с базы...")
mass_faces.clear()
all = db.select_all_person()
res, noname = db.search_person("noname")
for person in all:
if person.name!="noname" and person.name!="bufer":
if len(person.face)==0:
print("удаляем пустую персону", person.name)
db.del_persone(person)
def make_all_person():
print("Выбираем все лица из noname. И делаем разнос по персонам")
#начинаем перебор всех лиц, по похожести, и сравниваем с уж созданными персонами
res, noname = db.search_person("noname")
print(
"распределяем все лица по персонам. если уникальное, то создаем новую персону"
)
FaceAlgo.load_all_faces()
#перебираем все лица в noname, если нет похожих людей, то создаем новых
faces, data = db.search_faces(noname)
#print((data[0]))
new_face_counter = 0
print("всего лиц ", len(data))
for i in range(0, len(data)):
#print("сравниваем лицо", data[i])
if len(data[i]) != 128:
print(i, data[i])
#перезагружаем всю базу, будет очень медленно
#FaceAlgo.load_all_faces()
#print("сравниваем лицо",i)
ret, dist = FaceAlgo.compare_face(data[i], 0.45, False)
if ret:
if len(ret) > 0:
print(ret)
# оценка, имя персоны, id персоны, дескриптор
print("Похож на ", ret[1], dist)
# находим персону в базе
#print(ret)
if dist > 0.1:
res, pers = db.search_person_id(ret[1])
if res:
print("Добавляем лицо в персону", pers.name)
#db.set_face(pers, faces[i])
FaceAlgo.set_face(pers, faces[i])
# else:
# print("Лицо не добавляем. сильно похожее")
else:
new_face_counter += 1
facename = "name" + str(new_face_counter)
new_p = db.add_person(facename)
# добавляем неизвестно елицо в персну
print("нет совпадений в лице создаем новую персону под лицо",
facename, faces[i].id, faces[i].image_path)
#db.set_face(new_p, faces[i])
FaceAlgo.set_face(new_p, faces[i])
#перезагружаем весь кэш. Поменялось многое
FaceAlgo.load_all_faces()
def scan():
global AddQ, personMTS, nameMTS, feet
nameMTS = feet.get() #str(random.randint(1, 100))
print("********")
print("n " + nameMTS)
db.add_person(nameMTS)
answer, personMTS = db.search_person(nameMTS)
FaceAlgo.name(nameMTS, personMTS)
CameraWindow2.WindowsCamera(cap, True)
regreg.destroy()
def load_all_faces():
global mass_faces, noname
print("Загружаем данные с базы...")
mass_faces.clear()
all = db.select_all_person()
res,noname =db.search_person("noname")
for person in all:
#if person.name != "noname" and person.name != "bufer":
for face in person.face:
#print(face.image_path)
#faces.append(p.image_path)
data_f = []
for d in face.data:
data_f.append(float(d.code))
# print (len(data_f))
mass_faces.append([face.id, person.id, person.name, face.image_path, data_f ])
print("Загрузили")
return mass_faces
def onCut(person):
global listbox_faces,page_win_person, max_in_page
#values = [listbox_faces.get(idx) for idx in listbox_faces.curselection()]
answer, person_buf = db.search_person("bufer")
if answer:
# for face in person.face:
# print(face)
list_faces = []
for n in listbox_faces.curselection():
#print()
list_faces.append( person.face[int(page_win_person*max_in_page +n)])
print(n)
for f in list_faces:
db.set_face(person_buf, f)
WindowfPersonRefresh(person)
def onCut():
global listbox_faces, max_in_page, person, frame5,frame6
#values = [listbox_faces.get(idx) for idx in listbox_faces.curselection()]
#page_win_person_main = read_page()
answer, person_buf = db.search_person("bufer")
if answer:
# for face in person.face:
# print(face)
list_faces = []
for n in listbox_faces.curselection():
#print(int(page_win_person*max_in_page +n))
print (page_win_person_main)
print(int(n), (int(page_win_person_main * max_in_page + n)))
#num = (int(page_win_person * max_in_page + n))
list_faces.append( person.face[int(page_win_person_main*max_in_page +n)])
#list_faces.append(person.face[int(n)])
print(n)
for f in list_faces:
db.set_face(person_buf, f)
refesh_persone()
def f_2():
global istate, lmain, cap, var0, mashtab, count_frame, detect_faces_opencv, AddQ, nameMTS, personMTS, statusMTS, Rtime, Btime
statusMTS = "Ok"
bluure = 5
mashtab = 0.5
print("Thread2")
face_cascade = cv2.CascadeClassifier(
'C:\CV_Start\haarcascades\haarcascade_frontalface_default.xml')
count_frame = 0
detect_faces_opencv = False
flag_opencv = False
cap = cv2.VideoCapture(0)
var0 = 1
# while 1:
# time.sleep(1)
# print("------")
while True:
_, frame = cap.read()
count_frame += 1
frame, face_descriptors = FaceAlgo.find_faces_in_image(
frame, bluure, False)
person_name = "no_name"
#print('preparing for recognize')
for face_descriptor in face_descriptors:
#print('recognizing')
# отрисовываем и проверяем все найденные лица
ret, dist = FaceAlgo.compare_face(face_descriptor[0])
#print(ret, dist)
if ret:
if len(ret) > 0:
d = face_descriptor[1]
cv2.putText(frame,
str(str(round(dist, 2)) + " " + str(ret[2])),
(d.left(), d.top()), cv2.FONT_HERSHEY_COMPLEX,
1, (0, 255, 0), 2)
#print("Похож на ", ret[2])
person_name = str(ret[2])
# evt = threading.Event()
# q.put((person_name, evt))
# print('Waiting for data to be doubled')
# evt.wait()
else:
if statusMTS == "Er":
print("Error")
continue
# if (Btime) - (int(time.time())) > 0:
# print("Error")
# Btime -= int(time.time())
# continue
else:
print("Create new person")
nameMTS = input()
db.add_person(nameMTS)
answer, personMTS = db.search_person(nameMTS)
FaceAlgo.name(nameMTS, personMTS)
frame, face_descriptors = FaceAlgo.find_faces_in_image(
frame, bluure, nameMTS, True)
tstart = int(time.time())
while ((tstart + 15) - (int(time.time())) > 0):
_, frame = cap.read()
frame, face_descriptors = FaceAlgo.find_faces_in_image(
frame, bluure, nameMTS, True)
Rtime = (tstart + 15) - (int(time.time()))
print((tstart + 15) - (int(time.time())))
# time.sleep(8)
if person_name != "no_name":
print(person_name)
def find_faces_in_image(image, bluur, add_flag=False):
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
bluur_image = int(cv2.Laplacian(gray, cv2.CV_64F).var())
#cv2.imshow("Video", image)
#print("bluure", bluur_image)
if bluur_image < bluur:
#print("bad bluure", bluur)
cv2.putText(image, str(bluur_image), (30, 30), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2)
return image, []
cv2.putText(image, str(bluur_image), (30, 30), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)
img = image
img_show = image.copy()
#img2 = image
# img2 = cv2.resize(image, None, fx=0.50, fy=0.5, interpolation=cv2.INTER_CUBIC)
dets_webcam = detector(img, 1)
face_descriptors = []
#face_descriptor=[]
for k, d in enumerate(dets_webcam):
face = img[d.top(): d.bottom(), d.left():d.right()].copy()
if d.left() < 0 or d.top() < 0:
print("плохие границы под лицо")
continue
if abs(d.left() - d.right()) < 70:
print("маленькое лицо. отбраковываем", d.left() - d.right())
continue
cv2.rectangle(img_show, (d.left(), d.top()), (d.right(), d.bottom()), (0, 0, 255), 2)
#cv2.imshow("Video", img_show)
#cv2.waitKey(1)
#print(d.bottom(), d.top(), d.right(), d.left())
# cv2.imshow("Face", face)
shape = sp(img, d)
face_descriptor = facerec.compute_face_descriptor(img, shape)
#cv2.putText(img, ret[2], (l, t), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2)
#
# # print(face_descriptor)
#
if add_flag:
answer, person = db.search_person("noname")
if answer:
print(person.name)
# добавим новое лицо найденному человеку
#gray = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
#print(np.max(cv2.convertScaleAbs(cv2.Laplacian(gray, 3))))
# производим поиск и в noname тоже
ret, dist = compare_face(face_descriptor, 0.5, True)
print("схожесть", dist)
if ret:
# if len(ret)>0:
if len(ret) > 0:
if dist>0.35:
print("Добавляем лицо в базу")
face_file = 'c:/faces_db/' + str(int(time.time())) + '.jpg'
# face =cv2.resize(face, (100, 100), interpolation=cv2.INTER_CUBIC)
cv2.imwrite(face_file, face)
# face_descriptor = [0.3, 0.7, -0.9]
add_face(person, face_file, face_descriptor)
#face = db.add_face(person, face_file, face_descriptor)
else:
print("В базе есть сильно похожее лицо, не добавляем")
face_descriptors.append([face_descriptor, d])
#return img_show, face_descriptor, d
return img_show, face_descriptors
def clear_noname():
#удаляем все лица c noname
res, noname = db.search_person("noname")
db.del_face_in_persone(noname)
def del_buff():
print("Чистим буфер")
answer, person_buf = db.search_person("bufer")
if answer:
for f in person_buf.face:
db.del_face(f)
