def detectFacesOnScreen():
"""Detects facial emotions of faces on the computer screen"""
if cnn.loadModel():
with mss.mss() as sct:
monitor = {'top': 0, 'left': 0, 'width': 800, 'height': 900}
while True:
frame = np.array(sct.grab(monitor))
coordinates,gray = d.detectFace(frame,True)
for (x,y,w,h) in coordinates:
face = cv2.resize(gray[y:y+h,x:x+w],d.FACE_DIMENSIONS)
outputProcessing(frame,x,y,w,h,cnn.predictImageLables(face)[0])
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
else:
print("Invalid Model path "+cnn.MODEL_PATH)
def detectFacesInWebcam():
"""Detects facial emotions in webcam feed"""
if cnn.loadModel():
cap = cv2.VideoCapture(0)
while(cap.isOpened()):
ret, frame = cap.read()
coordinates,gray = d.detectFace(frame,True)
for (x,y,w,h) in coordinates:
face = cv2.resize(gray[y:y+h,x:x+w],d.FACE_DIMENSIONS)
outputProcessing(frame,x,y,w,h,cnn.predictImageLables(face)[0])
cv2.imshow('frame',frame)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
else:
print("Invalid Model path "+cnn.MODEL_PATH)
def detectFacesInVideo(videoPath):
"""Plays the video in the path with facial emotion labels"""
if cnn.loadModel():
if os.path.exists(videoPath):
cap = cv2.VideoCapture(videoPath)
while(True):
ret, frame = cap.read()
if ret:
coordinates,gray = d.detectFace(frame,True)
for (x,y,w,h) in coordinates:
face = cv2.resize(gray[y:y+h,x:x+w],d.FACE_DIMENSIONS)
outputProcessing(frame,x,y,w,h,cnn.predictImageLables(face)[0])
cv2.imshow('frame',frame)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
else:
break
cap.release()
cv2.destroyAllWindows()
else:
print("Invalid video path "+videoPath)
else:
print("Invalid Model path "+cnn.MODEL_PATH)