dataCollection.py

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

cap = cv2.VideoCapture(0)
detector = HandDetector(maxHands=1)

offset = 20
imgSize = 300

folder = "Data/C"
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_{time.time()}.jpg', imgWhite)
        print(counter)

    if key & 0xFF == ord('q'):
        break