-
Notifications
You must be signed in to change notification settings - Fork 2
/
HandTrackingModule.py
109 lines (91 loc) · 2.94 KB
/
HandTrackingModule.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
import cv2
import mediapipe as mp
import time
import math
class handDetector():
def __init__(self, mode=False, maxHands=2, modelComplexity=1, detectionCon=0.5, trackCon=0.5):
self.mode = mode
self.maxHands = maxHands
self.modelComplexity = modelComplexity
self.detectionCon = detectionCon
self.trackCon = trackCon
self.mpHands = mp.solutions.hands
self.hands = self.mpHands.Hands(self.mode, self.maxHands, self.modelComplexity, self.detectionCon, self.trackCon)
self.mpDraw = mp.solutions.drawing_utils
self.tipIds = [4, 8, 12, 16, 20]
def findHands(self, img, draw=True):
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
self.results = self.hands.process(imgRGB)
#print(results.multi_hand_landmarks)
if self.results.multi_hand_landmarks:
for handLms in self.results.multi_hand_landmarks:
if draw:
self.mpDraw.draw_landmarks(img, handLms, self.mpHands.HAND_CONNECTIONS)
return img
def findPosition(self, img, handNo=0, draw=True):
xList = []
yList = []
bbox = []
self.lmList = []
if self.results.multi_hand_landmarks:
myHand = self.results.multi_hand_landmarks[handNo]
for id, lm in enumerate(myHand.landmark):
#print(id, lm)
h, w, c = img.shape
cx, cy = int(lm.x*w), int(lm.y*h)
xList.append(cx)
yList.append(cy)
#print(id, cx, cy)
self.lmList.append([id, cx, cy])
if draw:
cv2.circle(img, (cx, cy), 5, (255,0,255), cv2.FILLED)
xmin, xmax = min(xList), max(xList)
ymin, ymax = min(yList), max(yList)
bbox = xmin, ymin, xmax, ymax
if draw:
cv2.rectangle(img, (bbox[0]-20, bbox[1]-20), (bbox[2]+20, bbox[3]+20), (0, 255, 0), 2)
return self.lmList, bbox
def findDistance(self, p1, p2, img, draw=True):
x1, y1 = self.lmList[p1][1], self.lmList[p1][2]
x2, y2 = self.lmList[p2][1], self.lmList[p2][2]
cx, cy = (x1+x2)//2, (y1+y2)//2
if draw:
cv2.circle(img, (x1,y1), 15, (255,0,255), cv2.FILLED)
cv2.circle(img, (x2,y2), 15, (255,0,255), cv2.FILLED)
cv2.line(img, (x1,y1), (x2,y2), (255,0,255), 3)
cv2.circle(img, (cx,cy), 15, (255,0,255), cv2.FILLED)
length = math.hypot(x2-x1, y2-y1)
return length, img, [x1, y1, x2, y2, cx, cy]
def fingersUp(self):
fingers = []
# Thumb
if self.lmList[self.tipIds[0]][1] < self.lmList[self.tipIds[0]-1][1]:
fingers.append(1)
else:
fingers.append(0)
# 4 Fingers
for id in range(1,5):
if self.lmList[self.tipIds[id]][2] < self.lmList[self.tipIds[id]-2][2]:
fingers.append(1)
else:
fingers.append(0)
return fingers
def main():
pTime = 0
cTime = 0
cap = cv2.VideoCapture(0)
detector = handDetector()
while True:
success, img = cap.read()
img = detector.findHands(img)
lmList = detector.findPosition(img)
if len(lmList) != 0:
print(lmList[1])
cTime = time.time()
fps = 1. / (cTime - pTime)
pTime = cTime
cv2.putText(img, str(int(fps)), (10,70), cv2.FONT_HERSHEY_PLAIN, 3, (255,0,255), 3)
cv2.imshow("Image", img)
cv2.waitKey(1)
if __name__ == "__main__":
main()