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main.py
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import cv2
import numpy as np
import HandTrackingModule as htm
import HandTrackingModul as ht
import os
import pyautogui as p
import time
import autopy
def m(cap):
######################
frameR = 100 #Frame Reduction
smoothening = 7 #random value
######################
pTime = 0
plocX, plocY = 0, 0
clocX, clocY = 0, 0
detector = ht.handDetector(maxHands=1)
wScr, hScr = autopy.screen.size()
# print(wScr, hScr)
while True:
# Step1: Find the landmarks
success, img = cap.read()
img = detector.findHands(img)
lmList, bbox = detector.findPosition(img)
# Step2: Get the tip of the index and middle finger
if len(lmList) != 0:
x1, y1 = lmList[8][1:]
x2, y2 = lmList[12][1:]
# Step3: Check which fingers are up
fingers = detector.fingersUp()
cv2.rectangle(img, (frameR, frameR), (wCam - frameR, hCam - frameR),
(255, 0, 255), 2)
# Step4: Only Index Finger: Moving Mode
if fingers[1] == 1 and fingers[2] == 0:
# Step5: Convert the coordinates
x3 = np.interp(x1, (frameR, wCam-frameR), (0, wScr))
y3 = np.interp(y1, (frameR, hCam-frameR), (0, hScr))
# Step6: Smooth Values
clocX = plocX + (x3 - plocX) / smoothening
clocY = plocY + (y3 - plocY) / smoothening
# Step7: Move Mouse
autopy.mouse.move(wScr - clocX, clocY)
cv2.circle(img, (x1, y1), 15, (255, 0, 255), cv2.FILLED)
plocX, plocY = clocX, clocY
# Step8: Both Index and middle are up: Clicking Mode
if fingers[1] == 1 and fingers[2] == 1:
# Step9: Find distance between fingers
length, img, lineInfo = detector.findDistance(8, 12, img)
# Step10: Click mouse if distance short
if length < 40:
cv2.circle(img, (lineInfo[4], lineInfo[5]), 15, (0, 255, 0), cv2.FILLED)
autopy.mouse.click()
# Step11: Frame rate
cTime = time.time()
fps = 1/(cTime-pTime)
pTime = cTime
cv2.putText(img, str(int(fps)), (28, 58), cv2.FONT_HERSHEY_PLAIN, 3, (255, 8, 8), 3)
# Step12: Display
cv2.imshow("Image", img)
cv2.waitKey(1)
def f(cap):
#cap = cv2.VideoCapture("http://192.168.43.220:9000/stream.mjpg")
#cap = cv2.VideoCapture("http://192.168.43.1:6677/videofeed?username=CCJDMAFKB&password=")
folderPath = "FigerImages"
myList = os.listdir(folderPath)
print(myList)
overlayList = []
for imPath in myList:
image = cv2.imread(f'{folderPath}/{imPath}')
# print(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)
# print(lmList)
if len(lmList) != 0:
fingers = []
# Thumb
if lmList[tipIds[0]][1] > lmList[tipIds[0] - 1][1]:
fingers.append(1)
else:
fingers.append(0)
# 4 Fingers
for id in range(1, 5):
if lmList[tipIds[id]][2] < lmList[tipIds[id] - 2][2]:
fingers.append(1)
else:
fingers.append(0)
# print(fingers)
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)
cap=cv2.VideoCapture("http://192.168.43.1:6677/videofeed?username=CCJDMAFKB&password=")
wCam, hCam = 640, 480
cap.set(3, wCam)
cap.set(4, hCam)
f(cap)
m(cap)