image_files=[]

for j in range(200):

adress = os.path.join(folder_load, str(j)+'.jpg')

if os.path.isfile(adress):

image_files.append(adress)

else:

break

Device_List = ie.available_devices

DeviceName =""

Platform=''

try:

if os.uname()[4][:3] == 'arm':

print('RPi found')

if 'MYRIAD' in Device_List:

DeviceName = 'MYRIAD'

Platform='RPiOS'

print('MYRIAD found')

else:

DeviceName = 'None'

Platform='RPiOS'

print('MYRIAD NOT found - everything will not work')

else:

print('CPU found, unix')

if 'CPU' in Device_List:

DeviceName = 'CPU'

Platform = 'UNIX'

print('CPU found, unix')

else:

DeviceName = 'None'

Platform='UNIX'

print('CPU NOT found, unix - everything will not work ')

except:

if 'CPU' in Device_List:

DeviceName = 'CPU'

Platform = 'WIN'

print('CPU found, win')

else:

DeviceName = 'None'

Platform = 'WIN'

print('CPU NOT found, WIN - everything will not work ')

#AudioPart

Audio=False

try:

CHUNK = 480

FORMAT = pyaudio.paInt16

CHANNELS = 1

RATE = 16000

RECORD_SECONDS = 1

p = pyaudio.PyAudio()

stream = p.open(format = FORMAT,

channels = CHANNELS,

rate = RATE,

input = True,

input_device_index = 0,

frames_per_buffer = CHUNK)

vad = webrtcvad.Vad()

vad.set_mode(3)

Audio=True

except Exception:

print("exeption, no audio")

images_angry = LoadData("./Images/angry/")

print('loaded angry - '+str(len(images_angry)))

images_happy = LoadData("./Images/happy/")

images_neutral = LoadData("./Images/neutral/")

images_sad = LoadData("./Images/sad/")

images_surprise = LoadData("./Images/surprise/")

angry_pos=0

happy_pos=0

neutral_pos=0

sad_pos=0

surprise_pos=0

time_now = time.time()

time_last = time.time()

ie = IECore()

DeviceName, Platform = DecideParams(ie)

rtsp = "rtsp://192.168.0.87/stream0"

if Platform=='RPiOS':

DrawOnImage = True

ShowImage = False

last_time_eye_save = -1

save_eye = True

USBCam=True

Video = True

else:

DrawOnImage = True

ShowImage = True

last_time_eye_save = -1

save_eye = True

USBCam = True

Video = True

if Video:

cv2.namedWindow("Main", cv2.WND_PROP_FULLSCREEN)

cv2.setWindowProperty("Main", cv2.WND_PROP_FULLSCREEN, 1)

SM = StateMachine.State()

Tel = telegram_reports.BOT()

FaceDetector = DetectionModels.FaceDetectModel(ie,DeviceName,Platform)

FaceLMDetector = DetectionModels.FacePointModel(ie,DeviceName,Platform)

FaceEmotionDetector = DetectionModels.FaceExpressionModel(ie,DeviceName,Platform)

FaceOrientDetector = DetectionModels.FaceOrientationModel(ie,DeviceName,Platform)

EyeOrientationDetector = DetectionModels.EyeOrientationModel(ie,DeviceName,Platform)

EyeType = DetectionModels.EyeTypeModel(ie,DeviceName,Platform)

if RPicamera:

camera = PiCamera()

camera.resolution = (640, 480)

camera.framerate = 32

rawCapture = PiRGBArray(camera, size=(640, 480))

time.sleep(0.1)

else:

if USBCam:

cap = cv2.VideoCapture(0)

else:

cap = cv2.VideoCapture(rtsp)

while True:

if RPicamera:

rawCapture.truncate(0)

image = next(camera.capture_continuous(rawCapture, format="bgr", use_video_port=True)).array

else:

was_read, image = cap.read()

if not USBCam:

image = cv2.resize(image,(640,360))

(input_height, input_width) = image.shape[:-1]

input_image = image.copy()

input_image_raw = image.copy()

disp = FaceDetector.PredictFace(image)

isFaceFound = False

if Audio:

data_audio = stream.read(CHUNK, exception_on_overflow = False)

result_audio = vad.is_speech(data_audio, RATE)

#if result_audio:

# print('Kek_')

else:

result_audio=False

for j in range(disp.shape[0]):

hypotesis = disp[j]

if hypotesis[2]>0.8:

isFaceFound=True

emo = 'neutral'

vec1='NotPresent'

vec2='NotPresent'

emo_disp = np.zeros(5)

(pitch, roll, yaw) = (0,0,0)

(vec, gazeAnglesx, gazeAnglesy) = (0,0,0)

xtl = (int)(hypotesis[3]*input_width)

ytl = (int)(hypotesis[4] * input_height)

xbr = (int)(hypotesis[5]*input_width)

ybr = (int)(hypotesis[6] * input_height)

img = input_image_raw[ytl:ybr,xtl:xbr,:]

(input_h, input_w) = img.shape[:-1]

if input_h>5 and input_w>5:

disp2 = FaceLMDetector.PredictPoints(img)

emo, emo_disp = FaceEmotionDetector.PredictExpression(img)

pitch, roll, yaw = FaceOrientDetector.PredictOrientation(img)

if DrawOnImage:

cv2.rectangle(input_image,(xtl,ytl),(xbr,ybr),(255,0,0),2)

input_image = DrawFunctions.draw_axis(input_image,yaw,pitch,roll,(int)((xtl+xbr)/2),(int)((ytl+ybr)/2))

for i in range(5):

point_x = disp2[i*2][0][0]

point_y = disp2[i * 2+1][0][0]

cv2.circle(input_image, ((int)(xtl+point_x*input_w), (int)(ytl+point_y*input_h)), 1, (255, 0, 0), 2)

cv2.putText(input_image,emo, (xtl,ybr),cv2.FONT_HERSHEY_COMPLEX,0.5,(0,0,0),1)

if DetectEyes:

xmidl = (int)(xtl+disp2[0][0][0]*input_w)

ymidl = (int)(ytl+disp2[1][0][0]*input_h)

widthl = (int)(input_w/4)

w2l = (int)(widthl/2)

xmidr = (int)(xtl + disp2[2][0][0] * input_w)

ymidr = (int)(ytl + disp2[3][0][0] * input_h)

widthr = widthl

w2r = (int)(widthr / 2)

if w2l>5 and w2r>5 and xmidl - w2l>0 and xmidl + w2l<input_width and ymidl - w2l>0 and ymidl + w2l<input_height and ymidr - w2r>0 and ymidr + w2r<input_height and xmidr - w2r>0 and xmidr + w2r<input_width:

img_left_eye = input_image_raw[ymidl - w2l:ymidl + w2l, xmidl - w2l:xmidl + w2l, :]

img_right_eye = input_image_raw[ymidr - w2r:ymidr + w2r, xmidr - w2r:xmidr + w2r, :]

vec1 = EyeType.PredictType(img_left_eye)

vec2 = EyeType.PredictType(img_right_eye)

#print(vec1)

#print(vec2)

'''

if time.time()-last_time_eye_save>1 and save_eye:

last_time_eye_save=time.time()

name = randomString(8)

cv2.imwrite('./EyeDataset/'+name+'_left.jpg',img_left_eye)

cv2.imwrite('./EyeDataset/' + name + '_right.jpg', img_right_eye)

'''

vec, gazeAnglesx, gazeAnglesy = EyeOrientationDetector.PredictOrientation(img_left_eye,img_right_eye,pitch,roll,yaw)

if DrawOnImage:

if abs(gazeAnglesx)<5 and abs(gazeAnglesy)<5:

cv2.rectangle(input_image, (xtl, ytl), (xbr, ybr), (0, 255, 0), 2)

if OutputDirections:

print(str(gazeAnglesx)+" "+str(gazeAnglesy))

if isFaceFound:

if DetectEyes:

SM.append(True,(xtl,ytl),(input_w,input_h),emo,(pitch, roll, yaw),(vec, gazeAnglesx, gazeAnglesy),emo_disp,(vec1,vec2),result_audio)

else:

SM.append(True, (xtl, ytl), (input_w, input_h), emo, (pitch, roll, yaw),

([0,0,0], 0, 0),emo_disp,('NotPresent','NotPresent'),result_audio)

else:

SM.append(False, (0, 0), (0, 0), 'neutral', (0, 0, 0), ([0,0,0], 0, 0),(0,0,0,0,0),('NotPresent','NotPresent'),result_audio)

Tel.ReleaseRequests(SM,input_image)

if ShowImage:

cv2.imshow("depth",input_image)

cv2.waitKey(10)

if Video:

blank_image = np.zeros((480, 640, 3), np.uint8)

if Tel.GameMode:

time_now = time.time()

dt = (time_now-time_last)*30

sdvig=1

if dt==0:

sdvig=1

else:

if dt>10:

sdvig=10

else:

sdvig=int(dt)

if SM.FrameList[-1].Emotion=='anger':

#blank_image=cv2.imread('./Images/sun.jpg')

#blank_image=cv2.imread('./Images/happy.jpg')

blank_image=cv2.imread(images_angry[angry_pos])

angry_pos+=sdvig

if angry_pos>=len(images_angry):

angry_pos=0

if SM.FrameList[-1].Emotion=='happy':

#blank_image=cv2.imread('./Images/lightning.jpg')

#blank_image=cv2.imread('./Images/sad.jpg')

blank_image=cv2.imread(images_happy[happy_pos])

happy_pos+=sdvig

if happy_pos>=len(images_happy):

happy_pos=0

if SM.FrameList[-1].Emotion=='neutral':

#blank_image=cv2.imread('./Images/tree.jpg')

#blank_image=cv2.imread('./Images/surpryze.jpg')

blank_image=cv2.imread(images_neutral[neutral_pos])

neutral_pos+=sdvig

if neutral_pos>=len(images_neutral):

neutral_pos=0

if SM.FrameList[-1].Emotion=='sad':

#blank_image=cv2.imread('./Images/lightning.jpg')

#blank_image=cv2.imread('./Images/angry.jpg')

blank_image=cv2.imread(images_sad[sad_pos])

sad_pos+=sdvig

if sad_pos>=len(images_sad):

sad_pos=0

if SM.FrameList[-1].Emotion=='surprise':

#blank_image=cv2.imread('./Images/cherniy_kvadrat.jpg')

#blank_image=cv2.imread('./Images/neutral.jpg')

blank_image=cv2.imread(images_surprise[surprise_pos])

surprise_pos+=sdvig

if surprise_pos>=len(images_surprise):

surprise_pos=0

time_last = time_now

else:

cv2.putText(blank_image,'GameModIsOff', (320,240),cv2.FONT_HERSHEY_COMPLEX,0.5,(255,255,255),1)

cv2.imshow("Main",blank_image)