-
Notifications
You must be signed in to change notification settings - Fork 0
/
hand_web_browser.py
146 lines (118 loc) · 5.42 KB
/
hand_web_browser.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
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
import cv2
import numpy as np
import math
import webbrowser as wb
import os
print("Enter full website for")
print("\n2 fingers")
fingers2 = input()
print("\n3 fingers")
fingers3 = input()
print("\n4 fingers")
fingers4 = input()
tabs = 0
count = 0
cap = cv2.VideoCapture(0)
while (cap.isOpened()):
# read image
ret, img = cap.read()
# get hand data from the rectangle sub window on the screen
cv2.rectangle(img, (400, 400), (100, 100), (0, 255, 0), 0)
crop_img = img[100:400, 100:400]
# convert to grayscale
grey = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY)
# applying gaussian blur
value = (35, 35)
blurred = cv2.GaussianBlur(grey, value, 0)
# thresholdin: Otsu's Binarization method
_, thresh1 = cv2.threshold(blurred, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
# show thresholded image, not necessary and can be skipped
cv2.imshow('Thresholded', thresh1)
# check OpenCV version to avoid unpacking error
(version, _, _) = cv2.__version__.split('.')
if version == '4':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
if version == '3':
image, contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
elif version == '2':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# find contour with max area
cnt = max(contours, key=lambda x: cv2.contourArea(x))
# create bounding rectangle around the contour (can skip below two lines)
x, y, w, h = cv2.boundingRect(cnt)
cv2.rectangle(crop_img, (x, y), (x + w, y + h), (0, 0, 255), 0)
# finding convex hull
hull = cv2.convexHull(cnt)
# drawing contours
drawing = np.zeros(crop_img.shape, np.uint8)
cv2.drawContours(drawing, [cnt], 0, (0, 255, 0), 0)
cv2.drawContours(drawing, [hull], 0, (0, 0, 255), 0)
# finding convex hull
hull = cv2.convexHull(cnt, returnPoints=False) # return point false to find convexity defects
# finding convexity defects
defects = cv2.convexityDefects(cnt, hull)
count_defects = 0
cv2.drawContours(thresh1, contours, -1, (0, 255, 0), 3) # to draw all contours pass -1
# applying Cosine Rule to find angle for all defects (between fingers)
# with angle > 90 degrees and ignore defects
for i in range(defects.shape[0]):
s, e, f, d = defects[i, 0] # [ start point, end point, farthest point, approximate distance to farthest point ]
start = tuple(cnt[s][0])
end = tuple(cnt[e][0])
far = tuple(cnt[f][0])
# 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)
# apply cosine rule here
angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c)) * 57
# ignore angles > 90 and highlight rest with red dots
if angle <= 90:
count_defects += 1
cv2.circle(crop_img, far, 1, [0, 0, 255], -1)
# dist = cv2.pointPolygonTest(cnt,far,True)
# draw a line from start to end i.e. the convex points (finger tips)
# (can skip this part)
cv2.line(crop_img, start, end, [0, 255, 0], 2)
# cv2.circle(crop_img,far,5,[0,0,255],-1)
if count == 0:
cv2.putText(img, "Wait for it :p", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
# define actions required
if count_defects == 1 and count != 2 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers2 + '.com')
tabs = tabs + 1
cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
count = 2
elif count_defects == 2 and count != 3 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers3 + '.com')
tabs = tabs + 1
cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
count = 3
elif count_defects == 3 and count != 4 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers4 + '.com')
cv2.putText(img, "4." + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
tabs = tabs + 1
count = 4
elif count_defects == 4 and count != 5:
cv2.putText(img, "5.Close Web browser", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
os.system("taskkill /im chrome.exe /f")
tabs = 0
count = 5
else:
cv2.putText(img, "", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
if count == 2:
cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
elif count == 3:
cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
elif count == 4:
cv2.putText(img, "4." + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
elif count == 5:
cv2.putText(img, "5.WebBrowser close", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
# show appropriate images in windows
cv2.imshow('Gesture', img)
all_img = np.hstack((drawing, crop_img))
# not necessary to show contours and can be skipped
cv2.imshow('Contours', all_img)
k = cv2.waitKey(10)
if k == 27:
break