lmList = hand1["lmList"]
for button in buttonList:
x, y = button.pos
w, h = button.size
dx = lmList[8][0] - lmList[4][0]
dy = lmList[8][1] - lmList[4][1]
dis = np.sqrt(dx * dx + dy * dy)
if x < lmList[8][0] < x + w and y < lmList[8][
1] < y + h and dis < 100:
cv2.rectangle(img, (x - 5, y - 5), (x + w + 5, y + h + 5),
(175, 0, 175), cv2.FILLED)
cv2.putText(img, button.text, (x + 20, y + 65),
cv2.FONT_HERSHEY_PLAIN, 4, (255, 255, 255), 4)
l, _, _ = detector.findDistance(
(x, y), (lmList[8][0], lmList[8][1]), img)
print(l)
if l < 60:
pygame.mixer.Sound("audios/" + button.text.lower() +
".wav").play(maxtime=1000)
cv2.rectangle(img, button.pos, (x + w, y + h), (0, 255, 0),
cv2.FILLED)
cv2.putText(img, button.text, (x + 20, y + 65),
cv2.FONT_HERSHEY_PLAIN, 4, (255, 255, 255), 4)
sleep(0.2)
cv2.imshow("Image", img)
cv2.waitKey(1)
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)
#Convert volume into hand range
vol = np.interp(length,[10,130],[minVol,maxVol])
volBar = np.interp(length,[10,130],[300,100])
volPer = np.interp(length,[10,130],[0,100])
volume.SetMasterVolumeLevel(vol, None)
if length < 25:
cv2.circle(img, (cx, cy), 10, (255, 0, 255), cv2.FILLED)
cv2.rectangle(img, (100,100), (80,300), (0,255,0),3)
cv2.rectangle(img, (100, int(volBar)), (80, 300), (0,255, 0), cv2.FILLED)
cv2.putText(img, f'{int(volPer)} %', (70, 350), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 3)
while True:
success, img = cap.read()
img = detector.findHands(img)
lmList, bboxInfo = detector.findPosition(img)
img = drawAll(img, buttonList)
if lmList:
for button in buttonList:
x, y = button.pos
w, h = button.size
if x < lmList[8][0] < x + w and y < lmList[8][1] < y + h:
cv2.rectangle(img, (x - 5, y - 5), (x + w + 5, y + h + 5), (175, 0, 175), cv2.FILLED)
cv2.putText(img, button.text, (x + 20, y + 65),
cv2.FONT_HERSHEY_PLAIN, 4, (255, 255, 255), 4)
l, _, _ = detector.findDistance(8, 12, img, draw=False)
print(l)
## when clicked
if l < 30:
keyboard.press(button.text)
cv2.rectangle(img, button.pos, (x + w, y + h), (0, 255, 0), cv2.FILLED)
cv2.putText(img, button.text, (x + 20, y + 65),
cv2.FONT_HERSHEY_PLAIN, 4, (255, 255, 255), 4)
finalText += button.text
sleep(0.15)
cv2.rectangle(img, (50, 350), (700, 450), (175, 0, 175), cv2.FILLED)
cv2.putText(img, finalText, (60, 430),
cv2.FONT_HERSHEY_PLAIN, 5, (255, 255, 255), 5)
mcq.choice3, [60, 300],
1,
1,
offset=20,
border=3)
img, bbox4 = cvzone.putTextRect(img,
mcq.choice4, [230, 300],
1,
1,
offset=20,
border=3)
if hands:
lmList = hands[0]['lmList']
cursor = lmList[8]
length, info = detector.findDistance(lmList[8], lmList[12])
#print((length))
if length < 15:
mcq.update(cursor, [bbox1, bbox2, bbox3, bbox4])
print(mcq.userAnswer)
if mcq.userAnswer is not None:
time.sleep(0.6)
qNo += 1
else:
score = 0
for mcq in mcqlist:
if mcq.answer == mcq.userAnswer:
img = cv2.flip(img, 1)
hands, img = detector.findHands(img)
# Draw All
cv2.rectangle(img, (800, 70), (800 + 400, 70 + 100), (225, 225, 225),
cv2.FILLED)
cv2.rectangle(img, (800, 70), (800 + 400, 70 + 100), (50, 50, 50), 3)
for button in buttonList:
button.draw(img)
# Check for Hand
if hands:
# Find distance between fingers
lmList = hands[0]['lmList']
length, _, img = detector.findDistance(lmList[8], lmList[12], img)
print(length)
x, y = lmList[8]
# If clicked check which button and perform action
if length < 50 and delayCounter == 0:
for i, button in enumerate(buttonList):
if button.checkClick(x, y):
myValue = buttonListValues[int(i % 4)][int(
i / 4)] # get correct number
if myValue == '=':
myEquation = str(eval(myEquation))
else:
myEquation += myValue
delayCounter = 1
detector = HandDetector(detectionCon=0.5, maxHands=1)
while True:
# Get image frame
success, img = cap.read()
# Find the hand and its landmarks
img = detector.findHands(img)
lmList, bboxInfo = detector.findPosition(img)
if lmList:
bbox = bboxInfo['bbox']
# Find how many fingers are up
fingers = detector.fingersUp()
totalFingers = fingers.count(1)
cv2.putText(img, f'Fingers:{totalFingers}', (bbox[0] + 200, bbox[1] - 30),
cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)
# Find Distance Between Two Fingers
distance, img, info = detector.findDistance(8, 12, img)
cv2.putText(img, f'Dist:{int(distance)}', (bbox[0] + 400, bbox[1] - 30),
cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)
# Find Hand Type
myHandType = detector.handType()
cv2.putText(img, f'Hand:{myHandType}', (bbox[0], bbox[1] - 30),
cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)
# Display
cv2.imshow("Image", img)
cv2.waitKey(1)
import cvzone
from cvzone.HandTrackingModule import HandDetector
import cv2
import pyautogui
cap = cv2.VideoCapture(0)
cap.set(3, 1500)
cap.set(4, 900)
detector = HandDetector(detectionCon=0.6, maxHands=1, minTrackCon=0.4)
while True:
success, img = cap.read()
img = cv2.flip(img, 1)
hands, img = detector.findHands(img)
if hands:
hand = hands[0]
lmList1 = hand["lmList"]
#print(lmList1)
x = lmList1[8][0]
y = lmList1[8][1]
pyautogui.moveTo(x, y)
length_single_click, info, img = detector.findDistance(
lmList1[8], lmList1[12], img)
length_double_click, info, img = detector.findDistance(
lmList1[12], lmList1[16], img)
if length_single_click < 40:
pyautogui.click(button='left')
if length_double_click + length_single_click < 90:
pyautogui.click(clicks=2, interval=0, button=pyautogui.PRIMARY)
cv2.imshow("Image", img)
cv2.waitKey(1)
if hands:
lmList = hands[0]['lmList']
cursor = lmList[8]
w, h = listImg[0].size
# resimlerin yerlerini kordinatlarını alıyoruz
xr, yr = listImg[0].posOrigin
xg, yg = listImg[1].posOrigin
xb, yb = listImg[2].posOrigin
xrs, yrs = listImg[3].posOrigin
#curcor bu aralığa girip girmediğini kontrol ediyoruz
if xr < cursor[0] < xr + w and yr < cursor[1] < yr + h:
length, info, img = detector.findDistance(lmList[8], lmList[4],
img, 5, (0, 0, 255))
length1 = int((length / 1000) * 500) - 15
if xg < cursor[0] < xg + w and yg < cursor[1] < yg + h:
length, info, img = detector.findDistance(lmList[8], lmList[4],
img, 5, (0, 255, 0))
length2 = int((length / 1000) * 500) - 15
if xb < cursor[0] < xb + w and yb < cursor[1] < yb + h:
length, info, img = detector.findDistance(lmList[8], lmList[4],
img, 5, (255, 0, 0))
length3 = int((length / 1000) * 500) - 15
if xrs < cursor[0] < xrs + w and yrs < cursor[1] < yrs + h:
length1 = 0
length2 = 0
success, img = cap.read()
hands, img = detector.findHands(img)
img1 = cv2.imread("cvarduino.jpg")
if len(hands) == 2:
# print(detector.fingersUp(hands[0]), detector.fingersUp(hands[1]))
if detector.fingersUp(hands[0]) == [1, 1, 0, 0, 0] and \
detector.fingersUp(hands[1]) == [1, 1, 0, 0, 0]:
# print("Zoom Gesture")
lmList1 = hands[0]["lmList"]
lmList2 = hands[1]["lmList"]
# point 8 is the tip of the index finger
if startDist is None:
#length, info, img = detector.findDistance(lmList1[8], lmList2[8], img)
length, info, img = detector.findDistance(hands[0]["center"], hands[1]["center"], img)
startDist = length
#length, info, img = detector.findDistance(lmList1[8], lmList2[8], img)
length, info, img = detector.findDistance(hands[0]["center"], hands[1]["center"], img)
scale = int((length - startDist) // 2)
cx, cy = info[4:]
print(scale)
else:
startDist = None
try:
h1, w1, _= img1.shape
newH, newW = ((h1+scale)//2)*2, ((w1+scale)//2)*2
img1 = cv2.resize(img1, (newW,newH))