-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathHandTrackingMod.py
80 lines (51 loc) · 2.11 KB
/
HandTrackingMod.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
import cv2
import mediapipe as mp
import time
class HandTracker():
def __init__(self,mode = False,maxNoHands = 2,minDetectionConfidence=0.5,minTrackingConfidence=0.5):
self.Mode = mode
self.MaxNoHands = maxNoHands
self.MinDetectionConfidence = minDetectionConfidence
self.MinTrackingConfidence = minTrackingConfidence
self.mpHands = mp.solutions.hands
self.hands = self.mpHands.Hands(self.Mode,self.MaxNoHands,
self.MinDetectionConfidence,self.MinTrackingConfidence)
self.mpDraw = mp.solutions.drawing_utils
def DetectingHands(self,img):
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
self.result = self.hands.process(imgRGB)
# print(result.multi_hand_landmarks)
if self.result.multi_hand_landmarks:
for handLms in self.result.multi_hand_landmarks:
self.mpDraw.draw_landmarks(img, handLms, self.mpHands.HAND_CONNECTIONS)
return img
def getHandCoordinates(self, img,handno = 0):
lst = []
if self.result.multi_hand_landmarks:
handLms = self.result.multi_hand_landmarks[handno]
for id, lm in enumerate(handLms.landmark):
h, w, c = img.shape
cx, cy = int(lm.x * w), int(lm.y * h)
lst.append([id,cx,cy])
if id == 4:
cv2.circle(img, (cx,cy), 10, (255,0,255),cv2.FILLED)
return lst
def main():
pTime = 0
cTime = 0
cap = cv2.VideoCapture(0)
detector = HandTracker()
while True:
success, img = cap.read()
img = detector.DetectingHands(img)
lst = detector.getHandCoordinates(img)
if len(lst) != 0:
print(lst)
cTime = time.time()
fps = 1 / (cTime - pTime)
pTime = cTime
cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3, (200, 0, 200), 3)
cv2.imshow("Image", img)
cv2.waitKey(1)
if __name__ == "__main__":
main()