本文实现手指计数,可以实现0~5的计数。
链接:https://pan.baidu.com/s/1WxthjxuumWyZ3XISAoD8ZQ
提取码:123a
import cv2
import mediapipe as mp
import time
class handDetector():
def __init__(self, mode=False, maxHands=2, detectionCon=0.5, trackCon=0.5):
self.mode = mode
self.maxHands = maxHands
self.detectionCon = detectionCon
self.trackCon = trackCon
self.mpHands = mp.solutions.hands
self.hands = self.mpHands.Hands(self.mode, self.maxHands,
self.detectionCon, self.trackCon)
self.mpDraw = mp.solutions.drawing_utils
def findHands(self, img, draw=True):
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
self.results = self.hands.process(imgRGB)
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):
lmList = []
if self.results.multi_hand_landmarks:
myHand = self.results.multi_hand_landmarks[handNo]
for id, lm in enumerate(myHand.landmark):
h, w, c = img.shape
cx, cy = int(lm.x * w), int(lm.y * h)
lmList.append([id, cx, cy])
if draw:
cv2.circle(img, (cx, cy), 15, (255, 0, 255), cv2.FILLED)
return lmList
def main():
pTime = 0
cTime = 0
cap = cv2.VideoCapture("fingercounter/Fingercounter")
detector = handDetector()
while True:
success, img = cap.read()
img = detector.findHands(img)
lmList = detector.findPosition(img)
if len(lmList) != 0:
print(lmList[4])
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()
import cv2
import time
import os
import HandTrackingModule as htm
wCam, hCam = 640, 480
cap = cv2.VideoCapture(1)
cap.set(3, wCam)
cap.set(4, hCam)
folderPath = "FingerImages"
myList = os.listdir(folderPath)
print(myList)
overlayList = []
for imPath in myList:
image = cv2.imread(f'{folderPath}/{imPath}')
overlayList.append(image)
print(len(overlayList))
pTime = 0
detector = htm.handDetector(detectionCon=0.75)
tipIds = [4, 8, 12, 16, 20]
while True:
success, img = cap.read()
img = detector.findHands(img)
lmList = detector.findPosition(img, draw=False)
if len(lmList) != 0:
fingers = []
if lmList[tipIds[0]][1] > lmList[tipIds[0] - 1][1]:
fingers.append(1)
else:
fingers.append(0)
for id in range(1, 5):
if lmList[tipIds[id]][2] < lmList[tipIds[id] - 2][2]:
fingers.append(1)
else:
fingers.append(0)
totalFingers = fingers.count(1)
print(totalFingers)
h, w, c = overlayList[totalFingers - 1].shape
img[0:h, 0:w] = overlayList[totalFingers - 1]
cv2.rectangle(img, (20, 225), (170, 425), (0, 255, 0), cv2.FILLED)
cv2.putText(img, str(totalFingers), (45, 375), cv2.FONT_HERSHEY_PLAIN,
10, (255, 0, 0), 25)
cTime = time.time()
fps = 1 / (cTime - pTime)
pTime = cTime
cv2.putText(img, f'FPS: {int(fps)}', (400, 70), cv2.FONT_HERSHEY_PLAIN,
3, (255, 0, 0), 3)
cv2.imshow("Image", img)
cv2.waitKey(1)
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