dH, dW = 480, 380
def resizeimg(image):
h, w = image.shape[:2]
if h < w:
img = cv2.resize(image,
(dW, math.floor(h / (w / dW)))) #有小數點無條件捨去，負數就進位
else:
img = cv2.resize(image, (math.floor(w / (h / dH)), dH))
return img
img = resizeimg(cv2.imread('/content/drive/MyDrive/lcc/fcu/hand1.jpg'))
detector = HandDetector(mode=False, maxHands=2) #動態追蹤True
img1 = detector.findHands(img)
cv2_imshow(img)
myHandType = detector.handType
print(myHandType)
ImList, bboxInfo = detector.findPosition(img)
print(ImList)
print(bboxInfo)
from cvzone.PoseModule import PoseDetector
img = resizeimg(cv2.imread('/content/drive/MyDrive/lcc/fcu/pose1.jpg'))
pose = PoseDetector()
img = pose.findPose(img)
cv2_imshow(img)
vol = 0
volBar = 300
#print(volume.GetVolumeRange())
minVol = volRange[0]
maxVol = volRange[1]
prevTime = 0
volPer = 0
while True:
success, img = cap.read()
hands, img = detector.findHands(img)
if hands:
lmList = hands[0]['lmList']
x1, y1 = lmList[4][0], lmList[4][1]
x2, y2 = lmList[8][0], lmList[8][1]
cx, cy = (x1+x2)//2 , (y1+y2)//2
cv2.circle(img,(x1,y1),10,(0,255,0),cv2.FILLED)
cv2.circle(img, (x2, y2), 10, (0, 255, 0), cv2.FILLED)
cv2.circle(img, (cx, cy), 10, (0, 255, 0), cv2.FILLED)
cv2.line(img, (x1,y1),(x2,y2),(0,255,0),3)
length, info = detector.findDistance((x1,y1),(x2,y2))
#print(length)
dataAll = list(reader)[1:]
#print(len(dataAll))
#Create Object for each mcq
mcqlist = []
for q in dataAll:
mcqlist.append(MCQ(q))
#print(len(mcqlist))
qNo = 0
qTotal = len(dataAll)
while True:
success, img = cap.read()
img = cv2.flip(img, 1)
hands, img = detector.findHands(img, flipType=False)
if qNo < qTotal:
mcq = mcqlist[qNo]
img, bbox = cvzone.putTextRect(img,
mcq.question, [60, 100],
1,
1,
offset=20,
border=3)
img, bbox1 = cvzone.putTextRect(img,
mcq.choice1, [60, 200],
1,
1,
annotationStart = False
hs, ws = int(120 * 1), int(213 * 1) # width and height of small image
# Get list of presentation images
pathImages = sorted(os.listdir(folderPath), key=len)
print(pathImages)
while True:
# Get image frame
success, img = cap.read()
img = cv2.flip(img, 1)
pathFullImage = os.path.join(folderPath, pathImages[imgNumber])
imgCurrent = cv2.imread(pathFullImage)
# Find the hand and its landmarks
hands, img = detectorHand.findHands(img) # with draw
# Draw Gesture Threshold line
cv2.line(img, (0, gestureThreshold), (width, gestureThreshold),
(0, 255, 0), 10)
if hands and buttonPressed is False: # If hand is detected
hand = hands[0]
cx, cy = hand["center"]
lmList = hand["lmList"] # List of 21 Landmark points
fingers = detectorHand.fingersUp(hand) # List of which fingers are up
# Constrain values for easier drawing
xVal = int(np.interp(lmList[8][0], [width // 2, width], [0, width]))
yVal = int(np.interp(lmList[8][1], [150, height - 150], [0, height]))
indexFinger = xVal, yVal
import cvzone
cap = cv2.VideoCapture(0)
detector = HandDetector(detectionCon=0.8, maxHands=1)
# function
x = [300, 245, 200, 170, 100, 257, 80, 112, 145, 130, 103, 93, 80, 75, 70, 60]
y = [20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95]
coff = np.polyfit(x, y, 2)
while True:
success, img = cap.read()
# print(img.shape)
hands = detector.findHands(img, draw=False)
if hands:
lmList = hands[0]['lmList']
x1, y1 = lmList[5]
x2, y2 = lmList[17]
x, y, w, h = hands[0]['bbox']
distance = np.sqrt(((y2 - y1) ** 2 + (x2 - x1) ** 2))
A, B, C = coff
distanceCm = A * (distance ** 2) + B * distance + C
# print(distanceCm)
cvzone.putTextRect(img, f'{int(distanceCm)} cm', (x + 5, y - 50))
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 255), 3)
if distanceCm <= 70:
cv2.putText(img, "Hand Detected", (50, 80), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 255, 0), 5)
Eli modül yardımı ile algılma
cvzone modülü 1.5 sürümü ve üstünde findPosition kaldırıldı
"""
import cv2
from cvzone.HandTrackingModule import HandDetector
cap = cv2.VideoCapture(0) #kamera ID numarası
detector = HandDetector(detectionCon=0.5,
maxHands=2) #max el sayısı ve el alglama hassasiyeti
I = [] #parmakların konumunu tutmak için
while True:
_, img = cap.read() #kamera okuma
img = cv2.flip(img, 1) #resmi aynalama
img = cv2.resize(img, (1280, 640)) #ekran boyutlarını ayarlama
img = detector.findHands(img) #elleri algılama
I, box = detector.findPosition(
img) #parmakları algılama (20 nokta algılama)
if I:
#x ve y konumlarını alma ilk parametre nokta ikincisi x veya y demek
f = detector.fingersUp()
x1 = I[4][0]
y1 = I[4][1]
x2 = I[8][0]
y2 = I[8][1]
#belirtilen konumları cembere alma ve cizgi cekme
cv2.circle(img, (x1, y1), 7, (0, 255, 255), 2)
cv2.circle(img, (x2, y2), 7, (0, 255, 255), 2)
cv2.line(img, (x1, y1), (x2, y2), (255, 0, 255), 2)