diff --git a/main.py b/main.py
new file mode 100644
index 0000000..a6396f6
--- /dev/null
+++ b/main.py
@@ -0,0 +1,42 @@
+import cv2
+import numpy as np
+import os
+
+
+def main():
+    cap = cv2.VideoCapture(0)
+    x, y, w, h = 300, 50, 350, 350
+
+    while (cap.isOpened()):
+        ret, img = cap.read()
+        img = cv2.flip(img, 1)
+        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+        mask2 = cv2.inRange(hsv, np.array([2, 50, 60]), np.array([25, 150, 255]))
+        res = cv2.bitwise_and(img, img, mask=mask2)
+        gray = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
+        median = cv2.GaussianBlur(gray, (5, 5), 0)
+
+        kernel_square = np.ones((5, 5), np.uint8)
+        dilation = cv2.dilate(median, kernel_square, iterations=2)
+        opening = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel_square)
+        ret, thresh = cv2.threshold(opening, 30, 255, cv2.THRESH_BINARY)
+
+        thresh = thresh[y:y + h, x:x + w]
+        contours = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[1]
+        if len(contours) > 0:
+            contour = max(contours, key=cv2.contourArea)
+            if cv2.contourArea(contour) > 2500:
+                x1, y1, w1, h1 = cv2.boundingRect(contour)
+                handImage = thresh[y1:y1 + h1, x1:x1 + w1]
+                handImage = cv2.resize(handImage, (50, 50))
+                cv2.imshow("Hand", handImage)
+                print(len(np.array(handImage)[0][0]))
+
+        
+        cv2.imshow("Frame", img)
+        cv2.imshow("Contours", thresh)
+        k = cv2.waitKey(10)
+        if k == 27:
+            break
+
+main()
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