import cv2
from cvzone.HandTrackingModule import HandDetector
import cvzone
import numpy as np
cap = cv2.VideoCapture(2)
cap.set(3, 1280)
cap.set(4, 720)
detector = HandDetector(detectionCon=0.8)
colorR = (255, 0, 255)
cx, cy, w, h = 100, 100, 200, 200
class DragRect():
def __init__(self, posCenter, size=[200, 200]):
self.posCenter = posCenter
self.size = size
def update(self, cursor):
cx, cy = self.posCenter
w, h = self.size
# If the index finger tip is in the rectangle region
if cx - w // 2 < cursor[0] < cx + w // 2 and \
cy - h // 2 < cursor[1] < cy + h // 2:
self.posCenter = cursor
rectList = []
for x in range(5):
# for right only
import cv2
import numpy as np
import mediapipe as mp
import time
from cvzone.HandTrackingModule import HandDetector
detector = HandDetector(0.8)
prevTime = 0
cap = cv2.VideoCapture(0)
tipIds = [8, 12, 16]
while True:
success, img = cap.read()
hands, img = detector.findHands(img)
if hands:
lmList = hands[0]['lmList']
fingers = []
q1 = lmList[20][1]
q2 = lmList[18][1]
if q1 < q2:
fingers.append(1)
else:
fingers.append(0)
s1 = lmList[4][0]
s2 = lmList[3][0]
import cv2 import os import numpy as np # Parameters width, height = 1280, 720 gestureThreshold = 300 folderPath = "Presentation" # Camera Setup cap = cv2.VideoCapture(0) cap.set(3, width) cap.set(4, height) # Hand Detector detectorHand = HandDetector(detectionCon=0.8, maxHands=1) # Variables imgList = [] delay = 30 buttonPressed = False counter = 0 drawMode = False imgNumber = 0 delayCounter = 0 annotations = [[]] annotationNumber = -1 annotationStart = False hs, ws = int(120 * 1), int(213 * 1) # width and height of small image # Get list of presentation images
# pip install cvzone
# pip install opencv-contrib-python
from cvzone.HandTrackingModule import HandDetector
import cv2
cap = cv2.VideoCapture(1)
detector = HandDetector(detectionCon=0.5, maxHands=2)
while True:
success, img = cap.read()
img = cv2.flip(img, 1)
img = detector.findHands(img)
lmList, bbox = detector.findPosition(img, draw=False)
if lmList:
myHandType = detector.handType()
cv2.putText(img, myHandType, (50, 50), cv2.FONT_HERSHEY_PLAIN, 2,
(0, 255, 0), 2)
cv2.imshow("Image", img)
cv2.waitKey(1)
import cv2
import numpy as np
from cvzone.HandTrackingModule import HandDetector
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))
import cv2
import numpy as np
import time
import mediapipe as mp
import pycaw
from cvzone.HandTrackingModule import HandDetector
from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume
cap = cv2.VideoCapture(0)
detector = HandDetector(0.8)
devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(
IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))
#volume.GetMute()
#volume.GetMasterVolumeLevel()
volRange = volume.GetVolumeRange()
vol = 0
volBar = 300
#print(volume.GetVolumeRange())
minVol = volRange[0]
maxVol = volRange[1]
prevTime = 0
volPer = 0
while True:
"""
import cv2
from cvzone.HandTrackingModule import HandDetector
import cvzone
import os
import serial
sericom = serial.Serial("COM10", 9600)
sericom.timeout = 1
cap = cv2.VideoCapture(0) #kamera ıd belirtilir
cap.set(3, 1280) #ıd ve kenar uzunluğu
cap.set(4, 720)
detector = HandDetector(
detectionCon=0.8,
maxHands=1) #el algılama hasssasiyeti ve algılayacagı en fazla el sayısı
class DragImg():
def __init__(self, path, posOrigin, imgType):
self.posOrigin = posOrigin
self.imgType = imgType
self.path = path
if self.imgType == 'png': #png ve jpg ayrımı
self.img = cv2.imread(self.path, cv2.IMREAD_UNCHANGED)
else:
self.img = cv2.imread(self.path)
['1', '2', '3', '+'], ['0', '/', '.', '=']]
buttonList = []
for x in range(4):
for y in range(4):
xpos = x * 100 + 800
ypos = y * 100 + 150
buttonList.append(
Button((xpos, ypos), 100, 100, buttonListValues[y][x]))
# Variables
myEquation = ''
delayCounter = 0
# Webcam
cap = cv2.VideoCapture(0)
detector = HandDetector(detectionCon=0.8, maxHands=1)
while True:
# Get image frame
success, img = cap.read()
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)
from cvzone.HandTrackingModule import HandDetector
import cv2
import socket
cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)
success, img = cap.read()
h, w, _ = img.shape
detector = HandDetector(detectionCon=0.8, maxHands=2)
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
serverAddressPort = ("127.0.0.1", 5052)
while True:
# Get image frame
success, img = cap.read()
# Find the hand and its landmarks
hands, img = detector.findHands(img) # with draw
# hands = detector.findHands(img, draw=False) # without draw
data = []
if hands:
# Hand 1
hand = hands[0]
lmList = hand["lmList"] # List of 21 Landmark points
for lm in lmList:
data.extend([lm[0], h - lm[1], lm[2]])
sock.sendto(str.encode(str(data)), serverAddressPort)
"""
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)
from cvzone.HandTrackingModule import HandDetector
import cv2
cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)
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),
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)
import math
import random
import cvzone
import cv2
import numpy as np
from cvzone.HandTrackingModule import HandDetector
cap = cv2.VideoCapture(2)
cap.set(3, 1280)
cap.set(4, 720)
detector = HandDetector(detectionCon=0.8, maxHands=1)
class SnakeGameClass:
def __init__(self, pathFood):
self.points = [] # all points of the snake
self.lengths = [] # distance between each point
self.currentLength = 0 # total length of the snake
self.allowedLength = 150 # total allowed Length
self.previousHead = 0, 0 # previous head point
self.imgFood = cv2.imread(pathFood, cv2.IMREAD_UNCHANGED)
self.hFood, self.wFood, _ = self.imgFood.shape
self.foodPoint = 0, 0
self.randomFoodLocation()
self.score = 0
self.gameOver = False
def randomFoodLocation(self):
# pip install cvzone
# pip install opencv-contrib-python
from cvzone.HandTrackingModule import HandDetector
import cv2
cap = cv2.VideoCapture(1)
detector = HandDetector(detectionCon=0.5, maxHands=2)
while True:
success, img = cap.read()
img = cv2.flip(img, 1)
img = detector.findHands(img)
cv2.imshow("Image", img)
cv2.waitKey(1)
import cv2
import csv
from cvzone.HandTrackingModule import HandDetector
import cvzone
import time
widthFrame = 1280
heightFrame = 720
cap = cv2.VideoCapture(0)
cap.set(3, widthFrame)
cap.set(4, heightFrame)
detector = HandDetector(detectionCon=0.8)
class MCQ():
def __init__(self, data):
self.question = data[0]
self.choice1 = data[1]
self.choice2 = data[2]
self.choice3 = data[3]
self.choice4 = data[4]
self.answer = int(data[5])
self.userAnswer = None
def update(self, cursor, bboxs):
for x, bbox in enumerate(bboxs):
x1, y1, x2, y2 = bbox
if x1 < cursor[0] < x2 and y1 < cursor[1] < y2:
import cvzone
from cvzone.HandTrackingModule import HandDetector
import cv2
cap = cv2.VideoCapture(0)
detector = HandDetector()
while True:
# Get image frame
success, img = cap.read()
# Find the hand and its landmarks
img = detector.findHands(img, draw=False)
lmList, bbox = detector.findPosition(img, draw=False)
if bbox:
# Draw Corner Rectangle
cvzone.cornerRect(img, bbox)
# Display
cv2.imshow("Image", img)
cv2.waitKey(1)
import asyncio
import cv2
from cvzone.HandTrackingModule import HandDetector
from time import sleep
import numpy as np
import cvzone
import pygame
pygame.mixer.init()
cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)
detector = HandDetector(detectionCon=0.8)
keys = [["C", "D", "E", "F", "G", "A", "B"]]
def drawAll(img, buttonList):
for button in buttonList:
x, y = button.pos
w, h = button.size
cvzone.cornerRect(
img,
(button.pos[0], button.pos[1], button.size[0], button.size[1]),
20,
rt=0)
cv2.rectangle(img, button.pos, (x + w, y + h), (255, 0, 255),
cv2.FILLED)
cv2.putText(img, button.text, (x + 20, y + 65), cv2.FONT_HERSHEY_PLAIN,
import cv2
from cvzone.HandTrackingModule import HandDetector
from time import sleep
import numpy as np
import cvzone
from pynput.keyboard import Controller
cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)
detector = HandDetector(detectionCon=0.8)
keys = [["Q", "W", "E", "R", "T", "Y", "U", "I", "O", "P"],
["A", "S", "D", "F", "G", "H", "J", "K", "L", ";"],
["Z", "X", "C", "V", "B", "N", "M", ",", ".", "/"]]
finalText = ""
keyboard = Controller()
def drawAll(img, buttonList):
for button in buttonList:
x, y = button.pos
w, h = button.size
cvzone.cornerRect(img, (button.pos[0], button.pos[1], button.size[0], button.size[1]),
20, rt=0)
cv2.rectangle(img, button.pos, (x + w, y + h), (255, 0, 255), cv2.FILLED)
cv2.putText(img, button.text, (x + 20, y + 65),
cv2.FONT_HERSHEY_PLAIN, 4, (255, 255, 255), 4)
return img
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)
import cv2
from cvzone.HandTrackingModule import HandDetector
cap = cv2.VideoCapture(1)
cap.set(3, 1280)
cap.set(4, 720)
detector = HandDetector(detectionCon=0.7)
startDist = None
scale = 0
cx, cy = 500,500
while True:
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)