03. [Preprocessing] Preprocessing_Onestop_code.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/kikiru328/Bone_Detection/blob/main/Final_preprocessing_code.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "QEPhvKIwVy5H"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import cv2\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.linear_model import LinearRegression\n",
        "import glob\n",
        "import math"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "DHkkflCJau19"
      },
      "source": [
        "##### 0. read_img"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iJQh8Ob_azMN"
      },
      "outputs": [],
      "source": [
        "def read_img(path:str)->np.array:\n",
        "    \"\"\"\n",
        "    Read X-ray image from path\n",
        "\n",
        "    Args:\n",
        "        path (str): X-ray pa image path\n",
        "\n",
        "    Returns:\n",
        "        np.array: image 3 channel array\n",
        "    \"\"\"    \n",
        "    original_img = cv2.imread(path)\n",
        "    return original_img"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "zdbiJVGGWHBW"
      },
      "source": [
        "##### 1. Make_mask for Removing background"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "UJb069RmWUzm"
      },
      "outputs": [],
      "source": [
        "def make_mask(original_img:np.array)-> np.array:\n",
        "  \"\"\"\n",
        "  Make a mask for removing background\n",
        "\n",
        "  Args:\n",
        "      original_img (np.array): x-ray pa image\n",
        "\n",
        "  Returns:\n",
        "      np.array: x-ray pa image background\n",
        "  \"\"\"  \n",
        "  \n",
        "  ## change to lab for making mask\n",
        "  img_mask = original_img.copy() # for error checking\n",
        "  img_mask = cv2.cvtColor(img_mask, cv2.COLOR_RGB2BGR)\n",
        "  img_mask = cv2.cvtColor(img_mask, cv2.COLOR_BGR2Lab)\n",
        "  \n",
        "  ## blur _02 \n",
        "  # kernel_size = odds / value = img.mean()\n",
        "\n",
        "  blur_k = int((img_mask.mean()*0.5)//2)*2+1\n",
        "  img_mask = cv2.medianBlur(img_mask, blur_k)\n",
        "  \n",
        "  ## change to Grayscale for threshold\n",
        "  img_mask = cv2.cvtColor(img_mask, cv2.COLOR_Lab2BGR)\n",
        "  img_mask = cv2.cvtColor(img_mask, cv2.COLOR_BGR2GRAY)\n",
        "\n",
        "  ## binary / value = img.mean()\n",
        "  if img_mask.mean() > 100 : \n",
        "    th = img_mask.mean()*0.94\n",
        "  else : \n",
        "    th = img_mask.mean()\n",
        "\n",
        "  ret, img_mask = cv2.threshold(img_mask, th, 255, cv2.THRESH_BINARY)\n",
        "\n",
        "  ## mask based Max value of contours\n",
        "  contours, hierarchy = cv2.findContours(img_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n",
        "  max_cnt = max(contours, key=cv2.contourArea)\n",
        "  mask = np.zeros(img_mask.shape, dtype=np.uint8)\n",
        "  cv2.drawContours(mask, [max_cnt], -1, (255,255,255), -1)\n",
        "  \n",
        "  ## Applying for dilation\n",
        "  k = cv2.getStructuringElement(cv2.MORPH_RECT, (8,8))\n",
        "  mask = cv2.dilate(mask,k)\n",
        "  return mask"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "BFOWA9huY_uy"
      },
      "source": [
        "##### 2. cutting_mask (background cut based mask)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bm8btQgdZFsO"
      },
      "outputs": [],
      "source": [
        "def cut_mask(original_img:np.array, mask:np.array)->np.array:\n",
        "    \"\"\"\n",
        "    Remove mask from original image with mask\n",
        "\n",
        "    Args:\n",
        "        original_img (np.array): x-ray pa image\n",
        "        mask (np.array): x-ray pa image background\n",
        "\n",
        "    Returns:\n",
        "        np.array: removed background image\n",
        "    \"\"\"    \n",
        "    ## copying\n",
        "    img_for_cut = original_img.copy() #for error checking\n",
        "    \n",
        "    ## H/W\n",
        "    height, width = img_for_cut.shape[:2]\n",
        "\n",
        "    ## mask\n",
        "    mask_list = mask.tolist()\n",
        "    \n",
        "    # cut from 5% outline\n",
        "    for y in range(int(height*0.05),height):\n",
        "        if max(mask[y,int(width*0.3):int(width*0.7)]) > 0:\n",
        "            start_y = y-int(height*0.05)\n",
        "            break\n",
        "            \n",
        "    for x in range(int(width*0.05),width):\n",
        "        if max(mask[int(height*0.3):int(height*0.7),x]) > 0:\n",
        "            start_x = x-int(width*0.05)\n",
        "            break\n",
        "            \n",
        "    for x in range(int(width*0.95),-1,-1):\n",
        "        if max(mask[int(height*0.3):int(height*0.7),x]) > 0:\n",
        "            end_x = x+int(width*0.05)\n",
        "            break\n",
        "            \n",
        "    cut_index = 0\n",
        "    if mask_list[height-1][-1] == 255 or mask_list[height-1][0] == 255:\n",
        "        for n in reversed(range(height)):\n",
        "            if mask_list[n][0] == 0 or mask_list[n][-1] == 0:\n",
        "                cut_index = n\n",
        "                break\n",
        "                \n",
        "    if cut_index == 0:\n",
        "        cut_index = height\n",
        "\n",
        "    ## converting color\n",
        "    img_for_cut = cv2.cvtColor(img_for_cut, cv2.COLOR_BGR2GRAY) \n",
        "    img_for_cut = img_for_cut[start_y:(cut_index-1),start_x:end_x]\n",
        "    mask = mask[start_y:(cut_index-1),start_x:end_x]\n",
        "\n",
        "    ## remove background\n",
        "    masked = cv2.bitwise_and(img_for_cut, mask)\n",
        "\n",
        "    return masked"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uA8UVgO6Za6U"
      },
      "source": [
        "##### 3. Overlaying contours (overlay_contours(masked))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "18yR0kCxZfeV"
      },
      "outputs": [],
      "source": [
        "def overlay_contours(masked:np.array) -> np.array:\n",
        "    \"\"\"\n",
        "    * Optional\n",
        "    \n",
        "    make overlaid contour image\n",
        "\n",
        "    Args:\n",
        "        masked (_type_): removed background image\n",
        "\n",
        "    Returns:\n",
        "        np.array: overlaid contour image  \n",
        "    \"\"\"    \n",
        "    copied_img = masked.copy()\n",
        "\n",
        "    ## smoothing\n",
        "    gray_smooth = cv2.bilateralFilter(copied_img, 7,60,60)\n",
        "\n",
        "    ## contours\n",
        "    outline = cv2.Canny(gray_smooth,50,50)\n",
        "\n",
        "    ## overlay\n",
        "    overlaied_img = cv2.add(masked,outline)\n",
        "    return overlaied_img"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RowJ4O6zZjsU"
      },
      "source": [
        "##### 4. Rotation (img_rotation(overlaied_img))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "QNcVc3_2Zlh1"
      },
      "outputs": [],
      "source": [
        "######## Rotation ########\n",
        "\n",
        "def img_rotation(overlaied_img:np.array)-> np.array:\n",
        "\n",
        "    ## copying img\n",
        "    before_rot_img = overlaied_img.copy()\n",
        "    \n",
        "    ## scaled\n",
        "    h, w = before_rot_img.shape[:2]\n",
        "    before_rot_img = cv2.cvtColor(before_rot_img, cv2.COLOR_RGB2BGR)\n",
        "    gray = cv2.cvtColor(before_rot_img, cv2.COLOR_BGR2GRAY)\n",
        "    ret, th = cv2.threshold(gray, 10, 255, cv2.THRESH_BINARY)\n",
        "    th_li = th.tolist()\n",
        "\n",
        "    ## Rotation stage 01\n",
        "    # lower = first black spot\n",
        "\n",
        "    for i in reversed(range(h)):\n",
        "        if th_li[i][0] == 0 and th_li[i][-1] == 0:\n",
        "            lower = i\n",
        "            break\n",
        "\n",
        "    # lower = condition ; bottom = lower / img * 0.95 or 0.9\n",
        "    if lower == h - 1:\n",
        "        lower = int(h*0.9)\n",
        "\n",
        "    # upper = condition ; lower + lower * 0.05\n",
        "    slice5 = int(len(th)*0.05)\n",
        "    upper = lower - slice5\n",
        "\n",
        "    # x, y = between upper and lower (5%) / wrist center\n",
        "\n",
        "    x,y = [],[]\n",
        "    for i in range(slice5):\n",
        "        cnt = th_li[i + upper].count(255)\n",
        "        index = th_li[i + upper].index(255)\n",
        "        x.append([i+upper])\n",
        "        y.append([int((index*2 + cnt - 1)/2)])\n",
        "\n",
        "\n",
        "    # For drawing straight line\n",
        "    ## x, y / draw regression line\n",
        "    model = LinearRegression()\n",
        "    model.fit(X=x,y=y)\n",
        "\n",
        "    ####################################################\n",
        "\n",
        "    ## Rotation stage 02\n",
        "    angle = math.atan2(h - 0, int(model.predict([[h]])) - int(model.predict([[0]])))*180/math.pi\n",
        "    M = cv2.getRotationMatrix2D((w/2,h/2), angle-90, 1)\n",
        "    rotate = cv2.warpAffine(before_rot_img, M, (w, h))\n",
        "\n",
        "    # Cutting img (rotated img)\n",
        "    for i in range(len(th[-1])):\n",
        "        if th[-1][i] == 255:\n",
        "            start_x = i\n",
        "            break\n",
        "\n",
        "    for i in range(len(th[-1])):\n",
        "        if th[-1][i] == 255:\n",
        "            end_x = i\n",
        "            \n",
        "\n",
        "    s_point = h - int((int(model.predict([[h]])-start_x)) * math.tan(math.pi*((90-angle)/180)))\n",
        "    e_point = h - int((end_x - int(model.predict([[h]]))) * math.tan(math.pi*((angle-90)/180)))\n",
        "    point = max(s_point, e_point)\n",
        "    rotated_img = rotate[:point]\n",
        "    return rotated_img"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e1l-W-dNcfVf"
      },
      "source": [
        "##### 5. Decomposing (Decomposing(rotated_img,a,b,d,e))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9B_u1zzYd5ZI"
      },
      "source": [
        "###### (1) contrast"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "FSgllme6WFaH"
      },
      "outputs": [],
      "source": [
        "def contrast_roi(img:np.array, low:int, high:int)->np.array:\n",
        "    \"\"\"\n",
        "    decompose contrast image\n",
        "\n",
        "    Args:\n",
        "        img (np.array): rotated image\n",
        "        low (int): option\n",
        "        high (int): option\n",
        "\n",
        "    Returns:\n",
        "        np.array: contrastd image\n",
        "    \"\"\"    \n",
        "    ## height, width\n",
        "    h, w = img.shape\n",
        "    \n",
        "    # black image\n",
        "    img_ = np.zeros(img.shape, dtype=np.uint8)\n",
        "\n",
        "    for y in range(h):\n",
        "        for x in range(w):\n",
        "            temp = int((255 / (high - low)) * (img[y][x] - low))\n",
        "            if temp > 255:\n",
        "                img_[y][x] = 255\n",
        "            elif temp < 0:\n",
        "                img_[y][x] = 0\n",
        "            else:\n",
        "                img_[y][x] = temp\n",
        "    return img_"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TPmnIfbjd1lV"
      },
      "source": [
        "###### (2) brightness"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "V7MWVCsYce4B"
      },
      "outputs": [],
      "source": [
        "######## Decompose_brightness ########\n",
        "def bright_ness(img:np.array)->int:\n",
        "    \"\"\"\n",
        "    Get Decompose brightness\n",
        "\n",
        "    Args:\n",
        "        img (np.array): rotated image\n",
        "\n",
        "    Returns:\n",
        "        int: brightness\n",
        "    \"\"\"\n",
        "    ## columns, rows\n",
        "    cols, rows = img.shape[:2]\n",
        "    brightness = np.sum(img) / (255 * cols * rows)\n",
        "    return brightness"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "mcVvvbxneFfB"
      },
      "outputs": [],
      "source": [
        "######## Decomposing ########\n",
        "\n",
        "### img, morphology_value_1, morphology_value_2, filter_value(a,b)\n",
        "\n",
        "def Decomposing(rotated_img,a,b,d,e):\n",
        "    \n",
        "    ######## Decomposing_stage_1 / [ Contours , Mask ] ########\n",
        "    decomp_img_1 = rotated_img.copy()\n",
        "\n",
        "    ## Adjusting brighness\n",
        "\n",
        "    if bright_ness(decomp_img_1) > 0.8:\n",
        "        decomp_img_1 = np.clip(decomp_img_1 - 80., 0, 255).astype(np.uint8)\n",
        "    elif bright_ness(decomp_img_1) > 0.75:\n",
        "        decomp_img_1 = np.clip(decomp_img_1 - 50., 0, 255).astype(np.uint8)\n",
        "    elif bright_ness(decomp_img_1) > 0.65:\n",
        "        decomp_img_1 = np.clip(decomp_img_1 - 30., 0, 255).astype(np.uint8)\n",
        "    else: decomp_img_1 = np.clip(decomp_img_1 - 10., 0, 255).astype(np.uint8)\n",
        "\n",
        "\n",
        "    ## change to Lab\n",
        "\n",
        "    decomp_img_1 = cv2.cvtColor(decomp_img_1, cv2.COLOR_RGB2BGR)\n",
        "    decomp_img_1 = cv2.cvtColor(decomp_img_1, cv2.COLOR_BGR2Lab)\n",
        "\n",
        "    ## Morphology\n",
        "\n",
        "    k = cv2.getStructuringElement(cv2.MORPH_CROSS, (a, a))\n",
        "    decomp_img_1 = cv2.morphologyEx(decomp_img_1, cv2.MORPH_TOPHAT, k) # Emphasis\n",
        "\n",
        "    ## Filter\n",
        "\n",
        "    decomp_img_1 = cv2.bilateralFilter(decomp_img_1,-1, d, e)\n",
        "\n",
        "    ## Lab to gray for binary\n",
        "\n",
        "    decomp_img_1 = cv2.cvtColor(decomp_img_1, cv2.COLOR_Lab2BGR)\n",
        "    decomp_img_1 = cv2.cvtColor(decomp_img_1, cv2.COLOR_BGR2GRAY)\n",
        "\n",
        "    ## img_normalization\n",
        "\n",
        "    decomp_img_1 = cv2.normalize(decomp_img_1, None, 0, 255, cv2.NORM_MINMAX)\n",
        "\n",
        "    ## CLAHE\n",
        "\n",
        "    decomp_img_1 = cv2.equalizeHist(decomp_img_1)\n",
        "    clahe = cv2.createCLAHE(clipLimit=1.0, tileGridSize=(3,3)) \n",
        "    decomp_img_1= clahe.apply(decomp_img_1)          \n",
        "\n",
        "\n",
        "    ## Threshold / value = img.mean()\n",
        "    ret, mask = cv2.threshold(decomp_img_1,\n",
        "                            np.mean(decomp_img_1),\n",
        "                            255,\n",
        "                            cv2.THRESH_BINARY) \n",
        "\n",
        "    ## Extract object / same value pixels\n",
        "\n",
        "    contours, hierarchy = cv2.findContours(mask, \n",
        "                                            cv2.RETR_EXTERNAL, # only outline\n",
        "                                            cv2.CHAIN_APPROX_SIMPLE) # Contour vertex coordinate\n",
        "\n",
        "\n",
        "    ## drawing Contours\n",
        "\n",
        "    cv2.drawContours(mask, contours, -1, (255,255,255), -1) # -1: 모든 컨트어 표시 /color/ fill\n",
        "\n",
        "\n",
        "        \n",
        "    ######## Decomposing_stage_2 / [ Brightness_Empahsis ] ########\n",
        "\n",
        "\n",
        "\n",
        "    ## Empahsis\n",
        "    decomp_img_2 = rotated_img.copy()\n",
        "    if bright_ness(decomp_img_2) > 0.8:\n",
        "        decomp_img_2 = np.clip(decomp_img_2 - 80., 0, 255).astype(np.uint8)\n",
        "    elif bright_ness(decomp_img_2) > 0.75:\n",
        "        decomp_img_2 = np.clip(decomp_img_2 - 50., 0, 255).astype(np.uint8)\n",
        "    elif bright_ness(decomp_img_2) > 0.65:\n",
        "        decomp_img_2 = np.clip(decomp_img_2 - 30., 0, 255).astype(np.uint8)\n",
        "    else: decomp_img_2 = np.clip(decomp_img_2 - 10., 0, 255).astype(np.uint8)\n",
        "\n",
        "\n",
        "    ## Morphology\n",
        "    k2 = cv2.getStructuringElement(cv2.MORPH_CROSS,(b,b))\n",
        "    decomp_img_2 = cv2.morphologyEx(decomp_img_2, cv2.MORPH_TOPHAT, k2)\n",
        "\n",
        "    ## contrast\n",
        "    decomp_img_2 = cv2.cvtColor(decomp_img_2, cv2.COLOR_BGR2RGB)\n",
        "    decomp_img_2 = cv2.cvtColor(decomp_img_2, cv2.COLOR_BGR2GRAY)\n",
        "\n",
        "    if decomp_img_2.mean() <= 15:\n",
        "        low = decomp_img_2.mean() * 3.2\n",
        "        high = decomp_img_2.mean() * 3.6\n",
        "    elif decomp_img_2.mean() <= 20:\n",
        "        low = decomp_img_2.mean() * 3\n",
        "        high = decomp_img_2.mean() * 3.6\n",
        "    else:\n",
        "        low = decomp_img_2.mean() * 3\n",
        "        high = decomp_img_2.mean() * 3.7\n",
        "\n",
        "    decomp_img_2 = cv2.blur(decomp_img_2,(2,2))\n",
        "    decomp_img_2 = contrast_roi(decomp_img_2, low, high)\n",
        "\n",
        "\n",
        "    ######## Decomposing_Final_stage / [ Result ] ########\n",
        "\n",
        "    ### Bone empahsis / bitwise (mask)\n",
        "\n",
        "    ## Morphology\n",
        "\n",
        "    ## Contours\n",
        "    contours, hierarchy = cv2.findContours(decomp_img_2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n",
        "    cv2.drawContours(decomp_img_2, contours, -1, (255, 255, 255), -1)\n",
        "\n",
        "    ## Bitwise (mask) / print white parts\n",
        "\n",
        "    decomp_img_2 = cv2.bitwise_and(decomp_img_2, mask) \n",
        "\n",
        "    decomp_img_2 = cv2.cvtColor(decomp_img_2, cv2.COLOR_GRAY2BGR)\n",
        "    decomp_img_2 = cv2.blur(decomp_img_2,(2,2))\n",
        "\n",
        "    bone_extraction = cv2.resize(decomp_img_2, (600, 800))\n",
        "\n",
        "    return bone_extraction\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wRcyrMnPeUJ_"
      },
      "source": [
        "##### Bone_extraction(path)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 90,
      "metadata": {
        "id": "On6owi1tUDCh"
      },
      "outputs": [],
      "source": [
        "def Bone_extraction(path):\n",
        "    try:\n",
        "        original_img = read_img(path)\n",
        "        mask = make_mask(original_img)\n",
        "        masked = cut_mask(original_img, mask)\n",
        "        overlaied_img = overlay_contours(masked)\n",
        "        rotated_img = img_rotation(overlaied_img)\n",
        "        bone = Decomposing(rotated_img,60,55,50,25)\n",
        "        return bone\n",
        "\n",
        "    except:\n",
        "        print('ERROR > Please check again' ) \n",
        "\n",
        "\n",
        " "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 92,
      "metadata": {
        "id": "4ro3hKV5cdbo"
      },
      "outputs": [],
      "source": [
        "a = '/content/drive/MyDrive/Bone_detection/data/image/female/1F.jpg'\n",
        "b = '/content/drive/MyDrive/Bone_detection/data/image/female/1_F.jpg'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 93,
      "metadata": {
        "id": "GNBZn_oinyBt"
      },
      "outputs": [],
      "source": [
        "checkList = [a,b]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 94,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 830
        },
        "id": "0XJVjsSOsoAX",
        "outputId": "5ab99238-eed1-4cfb-f0b9-df4eb8dd9b89"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "ERROR > Please check again\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7fd9902cb1d0>"
            ]
          },
          "execution_count": 94,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 720x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "for i in checkList:\n",
        "    bone = Bone_extraction(i)\n",
        "\n",
        "plt.figure(figsize=(10,15))\n",
        "plt.imshow(bone)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "metadata": {
        "id": "L1p3B2BkURyY"
      },
      "outputs": [],
      "source": [
        "# import \n",
        "\n",
        "import numpy as np\n",
        "import cv2\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.linear_model import LinearRegression\n",
        "import glob\n",
        "import math\n",
        "# import image_dehazer"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "authorship_tag": "ABX9TyP0BfBVOeAHSd6hIkjJL1wR",
      "collapsed_sections": [],
      "include_colab_link": true,
      "mount_file_id": "11Cr7C8dRtUnxUwxiqW4FNvHAZ-Qq4U9q",
      "name": "Final_preprocessing_code.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}