-
Notifications
You must be signed in to change notification settings - Fork 0
/
game.py
124 lines (91 loc) · 3.88 KB
/
game.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
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
import cv2
import numpy as np
import math
import pyautogui
cap = cv2.VideoCapture(0)
while (1):
try:
ret, frame = cap.read()
frame = cv2.flip(frame, 1)
kernel = np.ones((3, 3), np.uint8)
# defining region of interest
roi = frame[100:300, 100:300]
# Making a rectangle around the region of interest
cv2.rectangle(frame, (100, 100), (300, 300), (0, 255, 0), 0)
hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
# defining skin range for HSV
lower_skin = np.array([0, 20, 70], dtype=np.uint8)
upper_skin = np.array([20, 255, 255], dtype=np.uint8)
# Green glove skin : Doesn't work
#lower_skin = np.array([66, 75, 82], dtype=np.uint8)
#upper_skin = np.array([96, 75, 82], dtype=np.uint8)
# extracting skin color image
mask = cv2.inRange(hsv, lower_skin, upper_skin)
# Dilating
mask = cv2.dilate(mask, kernel, iterations=4)
# blurring the image
mask = cv2.GaussianBlur(mask, (5, 5), 100)
# find contours
contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# find contour of max area(hand)
cnt = max(contours, key=lambda x: cv2.contourArea(x))
# approx the contour a little
epsilon = 0.0005 * cv2.arcLength(cnt, True)
approx = cv2.approxPolyDP(cnt, epsilon, True)
# making convex hull
hull = cv2.convexHull(cnt)
# define area of hull and area of hand
areahull = cv2.contourArea(hull)
areacnt = cv2.contourArea(cnt)
# find the percentage of area not covered by hand in convex hull
arearatio = ((areahull - areacnt) / areacnt) * 100
# find the defects in convex hull with respect to hand
hull = cv2.convexHull(approx, returnPoints=False)
defects = cv2.convexityDefects(approx, hull)
# l = no. of defects
l = 0
# code for finding no. of defects due to fingers
for i in range(defects.shape[0]):
s, e, f, d = defects[i, 0]
start = tuple(approx[s][0])
end = tuple(approx[e][0])
far = tuple(approx[f][0])
pt = (100, 180)
# find length of all sides of triangle
a = math.sqrt((end[0] - start[0]) ** 2 + (end[1] - start[1]) ** 2)
b = math.sqrt((far[0] - start[0]) ** 2 + (far[1] - start[1]) ** 2)
c = math.sqrt((end[0] - far[0]) ** 2 + (end[1] - far[1]) ** 2)
s = (a + b + c) / 2
ar = math.sqrt(s * (s - a) * (s - b) * (s - c))
# distance between point and convex hull
d = (2 * ar) / a
# apply cosine rule here
angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c)) * 57
# ignore angles > 90 and ignore points very close to convex hull(they generally come due to noise)
if angle <= 90 and d > 30:
l += 1
cv2.circle(roi, far, 3, [255, 0, 0], -1)
# draw lines around hand
cv2.line(roi, start, end, [0, 255, 0], 2)
l += 1
# print corresponding gestures which are in their ranges
font = cv2.FONT_HERSHEY_SIMPLEX
if l == 1:
if areacnt < 2000:
cv2.putText(frame, 'Put hand in the box', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
else:
if arearatio < 12:
cv2.putText(frame, 'Running', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
#pyautogui.keyDown('down')
elif l > 1:
cv2.putText(frame, 'Jump', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
pyautogui.press('space')
# show the windows
cv2.imshow('mask', mask)
cv2.imshow('frame', frame)
except:
pass
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
cv2.destroyAllWindows()