Deteksi senyum
import cv2
# Load the cascade
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
smile_cascade = cv2.CascadeClassifier('haarcascade_smile.xml')
#faces = face_cascade.detectMultiScale(gray, 1.3, 5)
def detect(gray, frame):
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), ((x + w), (y + h)), (255, 0, 0), 2)
roi_gray = gray[y:y + h, x:x + w]
roi_color = frame[y:y + h, x:x + w]
smiles = smile_cascade.detectMultiScale(roi_gray, 1.8, 20)
for (sx, sy, sw, sh) in smiles:
cv2.rectangle(roi_color, (sx, sy), ((sx + sw), (sy + sh)), (0, 0, 255), 2)
return frame
video_capture = cv2.VideoCapture(0)
while True:
# Captures video_capture frame by frame
_, frame = video_capture.read()
# To capture image in monochrome
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# calls the detect() function
canvas = detect(gray, frame)
# Displays the result on camera feed
cv2.imshow('Video', canvas)
# The control breaks once q key is pressed
if cv2.waitKey(1) & 0xff == ord('q'):
break
# Release the capture once all the processing is done.
video_capture.release()
cv2.destroyAllWindows()
Muddy Mantis