Face Tilt Detection in degrees from live webcam using Python 3 OpenCV script. The output will be displayed inside a GUI Desktop App.
This code is pretty useful for face angle detection or rotated face detection using Python programming language.
Download Pre-trained XML Classifiers
To detect the face and eyes of the user, we need 2 pre-trained XML classifiers. You can download these classifiers from the links given below.
- Face detection classifier: haarcascade_frontalface_default.xml
- Eye detection classifier: haarcascade_eye.xml
pip install opencv-python
pip install numpy
code.py
import cv2 as cv
import numpy as np
# 0 for webcam feed ; add "path to file"
# for detection in video file
capture = cv.VideoCapture(0)
face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv.CascadeClassifier("haarcascade_eye.xml")
while True:
ret, frame = capture.read()
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.1, 5)
x, y, w, h = 0, 0, 0, 0
for (x, y, w, h) in faces:
cv.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv.circle(frame, (x + int(w * 0.5), y +
int(h * 0.5)), 4, (0, 255, 0), -1)
eyes = eye_cascade.detectMultiScale(gray[y:(y + h), x:(x + w)], 1.1, 4)
index = 0
eye_1 = [None, None, None, None]
eye_2 = [None, None, None, None]
for (ex, ey, ew, eh) in eyes:
if index == 0:
eye_1 = [ex, ey, ew, eh]
elif index == 1:
eye_2 = [ex, ey, ew, eh]
cv.rectangle(frame[y:(y + h), x:(x + w)], (ex, ey),
(ex + ew, ey + eh), (0, 0, 255), 2)
index = index + 1
if (eye_1[0] is not None) and (eye_2[0] is not None):
if eye_1[0] < eye_2[0]:
left_eye = eye_1
right_eye = eye_2
else:
left_eye = eye_2
right_eye = eye_1
left_eye_center = (
int(left_eye[0] + (left_eye[2] / 2)),
int(left_eye[1] + (left_eye[3] / 2)))
right_eye_center = (
int(right_eye[0] + (right_eye[2] / 2)),
int(right_eye[1] + (right_eye[3] / 2)))
left_eye_x = left_eye_center[0]
left_eye_y = left_eye_center[1]
right_eye_x = right_eye_center[0]
right_eye_y = right_eye_center[1]
delta_x = right_eye_x - left_eye_x
delta_y = right_eye_y - left_eye_y
# Slope of line formula
angle = np.arctan(delta_y / delta_x)
# Converting radians to degrees
angle = (angle * 180) / np.pi
# Provided a margin of error of 10 degrees
# (i.e, if the face tilts more than 10 degrees
# on either side the program will classify as right or left tilt)
if angle > 10:
cv.putText(frame, 'RIGHT TILT :' + str(int(angle))+' degrees',
(20, 30), cv.FONT_HERSHEY_SIMPLEX, 1,
(0, 255, 0), 2, cv.LINE_4)
elif angle < -10:
cv.putText(frame, 'LEFT TILT :' + str(int(angle))+' degrees',
(20, 30), cv.FONT_HERSHEY_SIMPLEX, 1,
(0, 255, 0), 2, cv.LINE_4)
else:
cv.putText(frame, 'STRAIGHT :', (20, 30),
cv.FONT_HERSHEY_SIMPLEX, 1,
(0, 255, 0), 2, cv.LINE_4)
cv.imshow('Frame', frame)
if cv.waitKey(1) & 0xFF == 27:
break
capture.release()
cv.destroyAllWindows()