#####################################selecting primary target face start
if len(faces) > 0:
print("Primary Face Found")
primaryFaceCoordinate = faces[0]
naj = primaryFaceCoordinate
print(primaryFaceCoordinate)
[x, y, w, h] = primaryFaceCoordinate
face = gray[y:y + h, x:x + w]
face = cv2.resize(face, (350, 350)) # cropping the face 350*350
#####################################emotion start
fisherEmotion = fish.findEmotion(face) # fisherface
cv2.imwrite("tensorFace.jpg", face)
image = cv2.imread(
'C:/Users/Nimzan/PycharmProjects/FinalApplication/tensorFace.jpg'
)
tensorEmotions, tensorValues = tensor.getEmotions(
image, sess, finalTensor)
tensorEmotion = tensorEmotions[0]
#####################################emotion end
#####################################comparison start
if fisherEmotion == "happy":
finalEmotion = fisherEmotion
elif fisherEmotion == "surprise":
finalEmotion = fisherEmotion
def fingerAndFacial():
def gohead():
third = Toplevel()
third.title("Music Player")
third.geometry("500x360+120+120")
label = Label(third, text='Music Player')
label.pack()
label = Label(third)
label.pack()
label12 = Label(third, text=finalEmotion, font=20).pack()
label = Label(third)
label.pack()
label = Label(third)
label.pack()
label = Label(third)
label.pack()
v = StringVar()
songlabel = Label(third, textvariable=v, width=35)
index = 0
def updatelabel():
global index
global songname
# v.set(realnames[index])
# v.set("happy")
# return songname
def nextsong(event):
global index
# index += 1
# pygame.mixer.music.load(listofsongs[index])
# pygame.mixer.music.play()
if finalEmotion == "happy":
#pygame.init()
#drum = pygame.mixer.Sound("happy.ogg")
#drum.play()
mixer.init()
pygame.mixer.Sound("happy.ogg")
pygame.mixer.music.load("happy.ogg")
pygame.mixer.music.play()
if finalEmotion == "sadness":
mixer.init()
pygame.mixer.Sound("sad.ogg")
pygame.mixer.music.load("sad.ogg")
pygame.mixer.music.play()
if finalEmotion == "anger":
mixer.init()
pygame.mixer.Sound("fear.ogg")
pygame.mixer.music.load("fear.ogg")
pygame.mixer.music.play()
updatelabel()
def stopsong(event):
pygame.mixer.music.stop()
v.set("")
# return songname
# listbox = Listbox(third)
# listbox.pack()
nextbutton = Button(third, text='Play Music', bg="Gray", fg="White")
nextbutton.pack()
label = Label(third)
label.pack()
stopbutton = Button(third, text='Stop Music', bg="Gray", fg="White")
stopbutton.pack()
nextbutton.bind("<Button-1>", nextsong)
stopbutton.bind("<Button-1>", stopsong)
songlabel.pack()
def combine():
gohead()
second.destroy()
second = Toplevel()
second.geometry("600x470+120+120")
label11 = Label(second).pack()
frame1 = Frame(second)
frame1.pack()
scrollBar = Scrollbar(frame1)
scrollBar.pack(side=RIGHT, fill=Y)
listbox = Listbox(frame1,
width=50,
height=20,
yscrollcommand=scrollBar.set)
listbox.pack(side=LEFT, fill="both")
#####################################d###################intializing tensorflow variables start
###############################################################################file paths start
RETRAINED_LABELS_TXT_FILE_LOC = "C:/Users/Nimzan/PycharmProjects/FinalApplication/TensorFlow/retrained_labels.txt"
RETRAINED_GRAPH_PB_FILE_LOC = "C:/Users/Nimzan/PycharmProjects/FinalApplication/TensorFlow/retrained_graph.pb"
###############################################################################file paths end
retrainedGraphFile = tf.gfile.FastGFile(RETRAINED_GRAPH_PB_FILE_LOC,
'rb') # Loading the trained graph
graphDef = tf.GraphDef() # creating graphdef object
graphDef.ParseFromString(retrainedGraphFile.read()) # parsing the graph
tf.import_graph_def(
graphDef, name='') # import the graph into the current default Graph
sess = tf.Session()
finalTensor = sess.graph.get_tensor_by_name('final_result:0')
#####################################d###################intializing tensorflow variables end
mouth_cascade = cv2.CascadeClassifier(
'TensorflowMouth/haarcascade_mcs_mouth.xml')
cascPath = 'haarcascade_filters/haarcascade_frontalface_default.xml'
faceCascade = cv2.CascadeClassifier(cascPath)
video_capture = cv2.VideoCapture(0)
import serial
from sklearn.externals import joblib
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
arduino = serial.Serial('COM3', 115200, timeout=10)
filename = "C:/Users/Nimzan/PycharmProjects/FinalApplication/Pulse/model.sav"
loaded_model = joblib.load(filename)
while True:
#################################################################################################################### pulse start
data = arduino.readline(
)[:-2] # the last bit gets rid of the new-line chars
if data:
# print(data)# create data
bpm = int(data)
if (39 > bpm or 200 < bpm):
print("BPM Exceeds the limit")
continue
else:
# print(bpm)
Pulseemotions = loaded_model.predict([[bpm]])
# print(emotion)
print("BPM : " + str(bpm) + " Expected Emotions : " +
Pulseemotions[0])
listbox.insert(
END, "BPM : " + str(bpm) + " Expected Emotions : " +
Pulseemotions[0])
#################################################################################################################### pulse end
ret, frame = video_capture.read() # capturing frames in in videostream
gray = cv2.cvtColor(
frame, cv2.COLOR_BGR2GRAY) # converting the frame to grayscale
#####################################mouth start
mouth_rects = mouth_cascade.detectMultiScale(gray, 1.7, 11)
for (x, y, w, h) in mouth_rects:
y = int(y - 0.15 * h)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
break
#####################################mouth end
#####################################detecting faces start
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
)
#####################################detecting faces end
#####################################selecting primary target face start
if len(faces) > 0:
print("Primary Face Found")
listbox.insert(END, "Primary face found")
primaryFaceCoordinate = faces[0]
print(primaryFaceCoordinate)
listbox.insert(END, primaryFaceCoordinate)
[x, y, w, h] = primaryFaceCoordinate
face = gray[y:y + h, x:x + w]
face = cv2.resize(face, (350, 350)) # cropping the face 350*350
#####################################emotion start
fisherEmotion = fish.findEmotion(face) # fisherface
cv2.imwrite("tensorFace.jpg", face)
image = cv2.imread(
'C:/Users/Nimzan/PycharmProjects/FinalApplication/tensorFace.jpg'
)
tensorEmotions, tensorValues = tensor.getEmotions(
image, sess, finalTensor)
tensorEmotion = tensorEmotions[0]
#####################################emotion end
#####################################comparison start
if fisherEmotion == "happy":
finalEmotion = fisherEmotion
elif fisherEmotion == "surprise":
finalEmotion = fisherEmotion
elif fisherEmotion == tensorEmotions[0]:
finalEmotion = fisherEmotion
elif fisherEmotion == tensorEmotions[1]:
finalEmotion = fisherEmotion
elif fisherEmotion == tensorEmotions[2]:
finalEmotion = fisherEmotion
else:
finalEmotion = tensorEmotions[0]
print(finalEmotion)
listbox.insert(END, finalEmotion)
#####################################comparison end
else:
print("No face Found")
#####################################selecting primary target face end
if finalEmotion != Pulseemotions[0]:
print("Emotion is not relavant to pulse")
print(" ")
listbox.insert(END, "Emotion is not relavant to pulse")
listbox.insert(END, " ")
else:
print("Emotion seems legit")
listbox.insert(END, "Emotion seems legit")
break
#####################################writing on frame start
font = cv2.FONT_HERSHEY_SIMPLEX
bottomLeftCornerOfText = (10, 25)
fontScale = 1
fontColor = (0, 255, 0)
lineType = 2
cv2.putText(frame, finalEmotion, bottomLeftCornerOfText, font,
fontScale, fontColor, lineType)
'''
font = cv2.FONT_HERSHEY_SIMPLEX
bottomLeftCornerOfText = (500, 25)q
fontScale = 1
fontColor = (0, 255, 0)
lineType = 2
cv2.putText(frame, fisherEmotion,
bottomLeftCornerOfText,
font,
fontScale,
fontColor,
lineType)
'''
#####################################writing on frame end
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0),
2) # drawing rectangle aronf the face
cv2.imshow('Video', frame) # Display updated frame
if cv2.waitKey(1) & 0xFF == ord('q'):
break
scrollBar.config(command=listbox.yview)
label11 = Label(second).pack()
label1 = Label(second, text="YOUR EMOTION IS : " + finalEmotion,
font=20).pack()
label11 = Label(second).pack()
nextbutton = Button(second,
width=20,
text='PLAY MUSIC',
command=combine,
bg="Gray",
fg="White")
nextbutton.pack()
# releasing the capture after all done
video_capture.release()
cv2.destroyAllWindows()