Data Collection Code Done

dataCollection.py

+import cv2
+from cvzone.HandTrackingModule import HandDetector
+import numpy as np
+import math
+import time
+
+cap = cv2.VideoCapture(1)
+detector = HandDetector(maxHands=1)
+
+offset = 20
+imgSize = 300
+
+folder = "Data/Yes"
+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)
+    cv2.waitKey(1)
+    if key == ord("s"):
+        counter += 1
+        cv2.imwrite(f'{folder}/Image_{time.time()}.jpg', imgWhite)
+        print(counter)