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/Hi"
counter = 0

while True:
    success, img = cap.read()
    if not success:
        print("Failed to capture image")
        continue

    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
        try:
            imgCrop = img[y - offset:y + h + offset, x - offset:x + w + offset]
            if imgCrop.size == 0:
                raise ValueError("Empty image crop detected")

            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)

        except cv2.error as e:
            print("OpenCV error:", e)
        except ValueError as e:
            print(e)

    cv2.imshow("Image", img)
    key = cv2.waitKey(1)
    if key == ord("s"):
        if imgCrop.size == 0:
            continue
        counter += 1
        cv2.imwrite(f'{folder}/Image_{time.time()}.jpg', imgWhite)
        print(counter)