-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathFaceTracker.py
79 lines (66 loc) · 2.42 KB
/
FaceTracker.py
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
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# main.py
#
# Copyright 2020 <pi@raspberrypi>
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston,
# MA 02110-1301, USA.
#
#
import math
import cv2
import imutils
import numpy as np
class FaceTracker:
def __init__(self, x, y, fov):
self.face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
self.res_x = x
self.res_y = y
self.fov = fov
def aimCoordinateConverter(self, res_x, res_y, pos_x, pos_y):
"""
Converts coordinates to range of [-1, 1]
"""
norm_x = (pos_x - 0.5 * res_x)/(res_x/2)
norm_y = (pos_y - 0.5 * res_y)/(res_y/2)
return norm_x, -norm_y
def calculateTargetAngle(self, coord):
"""
Painful trig to find servo turn angle
"""
# servo is centered at 90. add calculated turn angle, clip to
# [20, 160] to make sure that servo doesn't blow itself up.
return math.atan(math.tan(self.fov/2) * coord) * 180/math.pi
def findCoords(self, image):
"""
Find the coordinates/angle of an image
"""
face_detected = False
pos_x = pos_y = angle_x = angle_y = None
faces = self.face_cascade.detectMultiScale(image, 1.3, 5)
for (x,y,w,h) in faces:
face_detected = True
print("Target detected. Aiming...")
pos_x, pos_y = self.aimCoordinateConverter(self.res_x, self.res_y, x+(w/2), y+(h/2))
angle_x = np.clip(90 - self.calculateTargetAngle(pos_x), 20, 160)
angle_y = np.clip(90 + self.calculateTargetAngle(pos_y), 20, 160)
# print("Coordinates: {0}, {1}".format(pos_x, pos_y))
print("Angle calculated: x={0}, y={1}".format(angle_x, angle_y))
image = cv2.rectangle(image, (x,y), (x+w, y+h), (40, 40, 178), 2)
cv2.putText(image, "!", (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 1.2, (40, 40, 178), 2)
break
return face_detected, angle_x, angle_y