dataCollection.py

import cv2
import HandTrackModule as htm
import numpy as np
import math
import time

cap = cv2.VideoCapture(0)
detector = htm.handDetection(maxHands=1) #working with 1 hand
offset = 20




folder = "Data/Y"
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((300,300,3), np.uint8)*255 #300 * 200 matrix of a white image
        #startin height(y), ending height(y+h). starting width(x), ending width(x+h)
        imgCrop = img[y-offset:y+h+offset, x-offset:x+w+offset]




        aspectRatio = h/w
        if aspectRatio > 1:
            k = 300 / h #stretch height to image size
            widthCalculated = math.ceil(k * w)
            imgResize = cv2.resize(imgCrop, (widthCalculated, 300))
            imgResizeShape = imgResize.shape
            widthGap = math.ceil((300 - widthCalculated )/ 2)
            imgWhite[:, widthGap:widthCalculated+widthGap] = imgResize #width + gap to center the image, will generate cropped image with white background
        else:
            k = 300 / w #stretch width to image size
            heightCalculated = math.ceil(k * h)
            imgResize = cv2.resize(imgCrop, (300, heightCalculated))
            imgResizeShape = imgResize.shape
            heightGap = math.ceil((300 - heightCalculated )/ 2)
            imgWhite[heightGap:heightCalculated+heightGap, :] = imgResize #width + gap to center the image, will generate cropped image with white background 



        cv2.imshow("ImageCrop", imgCrop)
        cv2.imshow("ImageWhite", imgWhite)

        cv2.waitKey(1)
    cv2.imshow("Image", img)
    key = cv2.waitKey(1)

    if key == ord("s"): #save image to folder the 's' key is clicked
        counter += 1
        cv2.imwrite(f'{folder}/Image_{time.time()}.jpg', imgWhite)
        print(counter)