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 Merge(i):
global person_list1, person_list2
if person_list1 == -1 or person_list2 == -1:
print("не выбраны персоны")
return
if i == -1:
FaceAlgo.mergerPerson(person_list1, person_list2)
if i == 1:
FaceAlgo.mergerPerson(person_list2, person_list1)
return
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 make_keras(i):
#FaceAlgo.clear_noname()
FaceAlgo.delEmptyFaces()
# data = FaceAlgo.load_all_faces()
# #face.id, person.id, person.name, face.image_path, data_f
# print(data[0])
# x_train = np.random.random((len(data), 128))
# y_train = np.random.random((len(data), 1))
#
# for i in range(0, len(data)):
# x_train[i] = np.asarray(data[i][4])
# y_train[i] = int(data[i][1])
#y_train = np.random.random((len(data), 1))
#print(x_train[0], y_train[0])
# Generate dummy data
# x_train = np.random.random((1000, 128))
# y_train = np.random.randint(2, size=(1000, 1))
# x_test = np.random.random((100, 128))
# y_test = np.random.randint(2, size=(100, 1))
# #
# print(x_train[0], y_train[0])
# print(len(x_train[0]), len(y_train[0]))
#
# model = Sequential()
# model.add(Dense(512, activation='relu', input_dim=128))
#
# model.add(Dropout(0.2))
# model.add(Dense(max(y_train), activation='softmax'))
# model.compile(loss='categorical_crossentropy',
# optimizer='adam',
# metrics=['accuracy'])
# model = Sequential()
# model.add(Dense(64, input_dim=128, activation='relu'))
# model.add(Dropout(0.5))
# model.add(Dense(64, activation='relu'))
# model.add(Dropout(0.5))
# model.add(Dense(1, activation='sigmoid'))
#
# model.compile(loss='binary_crossentropy',
# optimizer='rmsprop',
# metrics=['accuracy'])
#
# model.fit(x_train, y_train,
# epochs=20,
# batch_size=16)
# score = model.evaluate(x_test, y_test, batch_size=128)
return
def show_frame():
# print("получили кадр")
global lmain, cap, var0, mashtab, count_frame, detect_faces_opencv, AddQ
_, frame = cap.read()
count_frame += 1
if var0.get() == "1":
frame, face_descriptors = FaceAlgo.find_faces_in_image(
frame, bluure, True)
else:
frame, face_descriptors = FaceAlgo.find_faces_in_image(
frame, bluure, False)
for face_descriptor in face_descriptors:
# 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])
else:
print("Create new person?")
alert.CNP(cap)
t_c.destroy()
time.sleep(2)
AddQ = True
# time.sleep(8)
frame = cv2.resize(frame,
None,
fx=mashtab,
fy=mashtab,
interpolation=cv2.INTER_CUBIC)
cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
img = Image.fromarray(cv2image)
img = ImageTk.PhotoImage(image=img)
# lmain.image = img
lmain.imgtk = img
lmain.configure(image=img)
# lmain.image = img
lmain.after(1, show_frame)
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 show_frame():
#print("получили кадр")
global lmain, cap, var0, mashtab, count_frame, detect_faces_opencv, nameMTS
_, frame = cap.read()
count_frame += 1
frame, face_descriptors = FaceAlgo.find_faces_in_image(frame, bluure, True)
for face_descriptor in face_descriptors:
#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])
# else:
# print("Улыбочку!)")
frame = cv2.resize(frame,
None,
fx=mashtab,
fy=mashtab,
interpolation=cv2.INTER_CUBIC)
cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
img = Image.fromarray(cv2image)
img = ImageTk.PhotoImage(image=img)
# lmain.image = img
lmain.imgtk = img
lmain.configure(image=img)
#lmain.image = img
lmain.after(1, show_frame)
def show_frame():
#print("получили кадр")
global lmain, cap, var0, mashtab, count_frame, detect_faces_opencv
_, frame = cap.read()
count_frame += 1
# if detect_faces_opencv:
# frame = cv2.resize(frame, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_CUBIC)
#
# gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#
# faces = face_cascade.detectMultiScale(gray, 1.3, 5)
# small=1
# for (x, y, w, h) in faces:
# cv2.rectangle(gray, (x, y), (x + w, y + h), (255, 0, 0), 2)
# #print(w)
# if w>65:
# small=0
# #cv2.imshow("gray", gray)
#
# if len(faces)<=0 or small==1:
# if count_frame%50==0:
# frame = cv2.resize(frame, None, fx=mashtab, fy=mashtab, interpolation=cv2.INTER_CUBIC)
# cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
# img = Image.fromarray(cv2image)
# img = ImageTk.PhotoImage(image=img)
#
# lmain.imgtk = img
# lmain.configure(image=img)
#
# lmain.after(1, show_frame)
# return
if var0.get() == "1":
frame, face_descriptors = FaceAlgo.find_faces_in_image(
frame, bluure, True)
else:
frame, face_descriptors = FaceAlgo.find_faces_in_image(
frame, bluure, False)
for face_descriptor in face_descriptors:
#отрисовываем и проверяем все найденные лица
ret, dist = FaceAlgo.compare_face(face_descriptor[0])
print(ret, dist)
if ret:
# if len(ret)>0:
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])
frame = cv2.resize(frame,
None,
fx=mashtab,
fy=mashtab,
interpolation=cv2.INTER_CUBIC)
cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
img = Image.fromarray(cv2image)
img = ImageTk.PhotoImage(image=img)
lmain.imgtk = img
lmain.configure(image=img)
#lmain.image = img
lmain.after(1, show_frame)
def delEmptyFaces():
print("удаляем пустые персоны")
FaceAlgo.delEmptyFaces()
refresh_main_window()
def delbuff():
FaceAlgo.del_buff()
# fm.add_command(label="Exit", command=close_win) hm = Menu(m) # второй пункт меню m.add_cascade(label="Работа", menu=hm) #hm.add_command(label="Отладочные функции", command=WorkWindows) #hm.add_command(label="Сортировка", command=SortWindows) hm.add_command(label="Обновить список", command=refresh_main_window) sfm = Menu(fm) hm.add_cascade(label="Сортировка",menu=sfm) sfm.add_command(label="Сортировка", command=SortWindows) sfm.add_command(label="Сравнить лицо", command=ww.compare_person) sfm.add_command(label="Разнести лица по персонам", command=ww.make_all_person) #hm.add_command(label="About", command=about) hm = Menu(m) # второй пункт меню m.add_cascade(label="Персона", menu=hm) hm.add_command(label="Добавить персону", command=create_person) ofm = Menu(fm) hm.add_cascade(label="Удаления",menu=ofm) ofm.add_command(label="Удалить пустые персоны", command=FaceAlgo.delEmptyFaces()) ofm.add_command(label="Удалить все персоны", command=ww.del_all_person) ofm.add_command(label="Удалить выбранную персону", command=del_person) ofm.add_command(label="Удалить пустые персоны", command=delEmptyFaces) ofm.add_command(label="Удалить буфер", command=delbuff) #hm.add_command(label="About", command=about) root.mainloop()
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 OnSelect1(event):
global all_person, person_list1, persons2, frame3, frame2
#print("click")
# selections = listbox.curselection() # tuple of digit-string(s), aTupleOfSTRINGs, where digit-string(s) range from { 0, 1, .., N-1 }
# selections = [int(x) + 1 for x in selections] # transform string(s) to shifted int(s), make 'em { 1, 2, .., N }
if listbox1.curselection():
person_list1 = all_person[listbox1.curselection()[0]]
print("выделили", person_list1.name)
list_comp = FaceAlgo.ComparePersons(
all_person[listbox1.curselection()[0]])
listbox2.delete(0, END)
persons2.clear()
# добавляем в лист бокс данные
for p in list_comp:
# listbox.insert(END, str(p.name+" "+p.second_name) )
listbox2.insert(END, str(str(p[2]) + " " + str(round(p[5], 2))))
ret, p = db.search_person_id(p[1])
if ret:
persons2.append(p)
listbox2.grid(row=0, column=4, padx=10, pady=10)
list = frame2.grid_slaves()
for l in list:
l.destroy()
list = frame3.grid_slaves()
for l in list:
l.destroy()
row_c = 0
count = 0
for face in person_list1.face:
count += 1
if count > 3:
break
frame = cv2.imread(face.image_path)
height, width = frame.shape[:-1]
if height > 0 and width > 0:
frame = cv2.resize(frame, (115, 115),
interpolation=cv2.INTER_CUBIC)
cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
img = Image.fromarray(cv2image)
# imgtk = ImageTk.PhotoImage(image=img)
# img = ImageTk.PhotoImage(Image.open(face.image_path))
img = ImageTk.PhotoImage(image=img)
# print(face.image_path)
# panel = Label(t, image=img)
# panel = Label(t, text = face.image_path)
panel = Button(frame3, image=img)
# panel = Button(t, image=img, text=c)
# panel.bind('<Button-1>', push_image)
panel.image = img
panel.grid(row=row_c, column=0, sticky=(N, W, E, S))
row_c += 1
def compare_person(i):
FaceAlgo.compare_face_by_id(23)
FaceAlgo.compare_face_by_id(3)