dataCollection.py

import cv2
from cvzone.HandTrackingModule import HandDetector
import numpy as np
import math
import time

cap = cv2.VideoCapture(0)
detector = HandDetector(maxHands=2)

offset = 20
imgSize = 300
folder = "Data/Z"
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]
        imageCropShape = 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("ImageWhitep", imgWhite)

    cv2.imshow("Image", img)
    key = cv2.waitKey(1)
    if key == ord("s"):
        counter += 1
        cv2.imwrite(f'{folder}/Image_{time.time()}.jpg', imgWhite)
        print(counter)