FaceDetectionAPI_OpenCV/Demo_SmileDetection.py at master · mrsingh47/FaceDetectionAPI_OpenCV · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
"""
Step1: Import package open CV
Step2: Import XML based DataSet for comparision
Step3: You can display message if face is detected else Nothing


"""


import cv2

face_cascade=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade=cv2.CascadeClassifier('haarcascade_eye.xml')
smile_cascade=cv2.CascadeClassifier('haarcascade_smile.xml')

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
    ret, frame = video_capture.read()

    # To capture image in monochrome
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)

    # 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()