diff --git a/count_rice.ipynb b/count_rice.ipynb
index f8bb510..8205c9d 100644
--- a/count_rice.ipynb
+++ b/count_rice.ipynb
@@ -1,12 +1,5 @@
 {
  "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# wlXlv Image"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -19,6 +12,7 @@
     "from PIL import Image\n",
     "from scipy import ndimage\n",
     "\n",
+    "\n",
     "def count_rice_number(img_path):\n",
     "    # Load the uploaded image\n",
     "    img = cv2.imread(img_path)\n",
@@ -31,6 +25,7 @@
     "    ##### Add MedianFilter to remove salt and pepper noise #####\n",
     "    ############################################################\n",
     "    gray = cv2.medianBlur(gray, 3)\n",
+    "    gray = cv2.GaussianBlur(gray, (3, 3), 0)\n",
     "\n",
     "    #############################################\n",
     "    ######## Apply Fourier Transform ############\n",
diff --git a/crop_frame.ipynb b/crop_frame.ipynb
index 2829aa2..a15304f 100644
--- a/crop_frame.ipynb
+++ b/crop_frame.ipynb
@@ -7,11 +7,14 @@
    "outputs": [],
    "source": [
     "import math\n",
+    "\n",
     "import cv2\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "from PIL import Image\n",
     "from scipy import ndimage\n",
+    "\n",
+    "\n",
     "def crop_cell(img_path):\n",
     "    # Load the uploaded image\n",
     "    img = cv2.imread(img_path)\n",
@@ -71,7 +74,7 @@
     "    \n",
     "    ######### PREPROCESS THE ROTATED IMAGE TO DETECT CELL ###########\n",
     "    ## Convert image to grayscale image \n",
-    "    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
+    "    gray = cv2.cvtColor(rotated_image_raw, cv2.COLOR_BGR2GRAY)\n",
     "    ## Apply Gaussian Blur for smoothing\n",
     "    gray = cv2.GaussianBlur(gray, (5, 5), 4) \n",
     "    # Define the gamma value\n",
@@ -132,7 +135,7 @@
     "    sorted_contours = sort_contours(filtered_contours)\n",
     "    \n",
     "    print(f\"Number of cells : {len(sorted_contours)}\")\n",
-    "    fig, ax = plt.subplots(math.ceil(len(sorted_contours) / 4), 4, figsize=(12, 6))\n",
+    "    fig, ax = plt.subplots(math.ceil(len(sorted_contours) / 4), 4, figsize=(8, 6))\n",
     "    for a in ax.ravel():\n",
     "        a.axis('off')\n",
     "    print(ax.shape)\n",