dataCollection.py

import cv2
import mediapipe as mp
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/Left"
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
        elif aspectRatio < 1:
            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 cv2.waitKey(10) & 0xFF == ord('q'):
        break

cap.release()