dataCollection.py

import cv2
from cvzone.HandTrackingModule import HandDetector
import numpy as np
import math
cap=cv2.VideoCapture(0)
detector=HandDetector(maxHands=1)
offset=20
imgSize=300
folder="Data/E"
counter=0
while True:
    success, img=cap.read()
    hands, img=detector.findHands(img)
    if hands:
        hand=hands[0]
        x, y, w, h=hand['bbox']
        imgWhite=np.ones((imgSize, imgSize, 3), np.uint8)*255
        imgCrop=img[y-offset:y+h+offset, x-offset:x+w+offset]
        imgCropShape=imgCrop.shape
        aspectRatio=h/w
        if aspectRatio>1:
            k=imgSize/h
            wCal=math.ceil(k*w)
            imgResize=cv2.resize(imgCrop, (wCal, imgSize))
            imgResizeShape=imgResize.shape
            wGap=math.ceil((imgSize-wCal)/2)
            imgWhite[:, wGap:wCal+wGap]=imgResize
        else:
            k=imgSize/w
            hCal=math.ceil(k*h)
            imgResize=cv2.resize(imgCrop, (imgSize, hCal))
            imgResizeShape=imgResize.shape
            hGap=math.ceil((imgSize-hCal)/2)
            imgWhite[hGap:hCal+hGap, :]=imgResize
        cv2.imshow("ImageCrop", imgCrop)
        cv2.imshow("ImageWhite", imgWhite)
    cv2.imshow("Image", img)
    key=cv2.waitKey(1)
    if key==ord("s"):
        counter+=1
        cv2.imwrite(f'{folder}/Image_{np.random.randint(0,10000)}.jpg', imgWhite)
        print(counter)