Image Retrieval Batik - Final GUI.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import cv2\n",
    "import sqlite3\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "np.set_printoptions(threshold=sys.maxsize)\n",
    "from collections import Counter\n",
    "from PIL import Image\n",
    "import io"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# citra = '11'\n",
    "# imageN = cv2.imread('Testing/'+citra+'.jpg')\n",
    "\n",
    "def img(gambar):\n",
    "    imageG = cv2.cvtColor(gambar, cv2.COLOR_BGR2GRAY)\n",
    "    (thresh, image) = cv2.threshold(imageG, 127, 255, cv2.THRESH_BINARY)\n",
    "    print(image.shape)\n",
    "#     plt.title(citra)\n",
    "#     plt.imshow(imageN[:,:,::-1])\n",
    "    return([imageG, image])\n",
    "\n",
    "# batik = img(imageN)\n",
    "# image = batik[1]\n",
    "# imageG = batik[0]\n",
    "# imageN.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def kirsch(image):\n",
    "    x,y = image.shape\n",
    "    list=[]\n",
    "    kirsch = np.zeros((x,y))\n",
    "    for i in range(2,x-1):\n",
    "        for j in range(2,y-1):\n",
    "            \n",
    "            #utara\n",
    "            k1 = np.square((5) * image[i - 1, j - 1] + 5 * image[i - 1, j] + 5 * image[i - 1, j + 1] -\n",
    "                  3 * image[i, j - 1] - 3 * image[i, j + 1] - 3 * image[i + 1, j - 1] -\n",
    "                  3 * image[i + 1, j] - 3 * image[i + 1, j + 1])\n",
    "            \n",
    "            #timur laut\n",
    "            k2 = np.square((-3) * image[i - 1, j - 1] + 5 * image[i - 1, j] + 5 * image[i - 1, j + 1] -\n",
    "                  3 * image[i, j - 1] + 5 * image[i, j + 1] - 3 * image[i + 1, j - 1] -\n",
    "                  3 * image[i + 1, j] - 3 * image[i + 1, j + 1])\n",
    "            \n",
    "            #timur\n",
    "            k3 = np.square((-3) * image[i - 1, j - 1] - 3 * image[i - 1, j] + 5 * image[i - 1, j + 1] -\n",
    "                  3 * image[i, j - 1] + 5 * image[i, j + 1] - 3 * image[i + 1, j - 1] -\n",
    "                  3 * image[i + 1, j] + 5 * image[i + 1, j + 1])\n",
    "            \n",
    "            #tenggara\n",
    "            k4 = np.square((-3) * image[i - 1, j - 1] - 3 * image[i - 1, j] - 3 * image[i - 1, j + 1] -\n",
    "                  3 * image[i, j - 1] + 5 * image[i, j + 1] - 3 * image[i + 1, j - 1] +\n",
    "                  5 * image[i + 1, j] + 5 * image[i + 1, j + 1])\n",
    "            \n",
    "            #selatan\n",
    "            k5 = np.square((-3) * image[i - 1, j - 1] - 3 * image[i - 1, j] - 3 * image[i - 1, j + 1] -\n",
    "                  3 * image[i, j - 1] - 3 * image[i, j + 1] + 5 * image[i + 1, j - 1] +\n",
    "                  5 * image[i + 1, j] + 5 * image[i + 1, j + 1])\n",
    "            \n",
    "            #barat daya\n",
    "            k6 = np.square((-3) * image[i - 1, j - 1] - 3 * image[i - 1, j] - 3 * image[i - 1, j + 1] +\n",
    "                  5 * image[i, j - 1] - 3 * image[i, j + 1] + 5 * image[i + 1, j - 1] +\n",
    "                  5 * image[i + 1, j] - 3 * image[i + 1, j + 1])\n",
    "            \n",
    "            #barat\n",
    "            k7 = np.square(5 * image[i - 1, j - 1] - 3 * image[i - 1, j] - 3 * image[i - 1, j + 1] + \n",
    "                  5 * image[i, j - 1] - 3 * image[i, j + 1] + 5 * image[i + 1, j - 1] -\n",
    "                  3 * image[i + 1, j] - 3 * image[i + 1, j + 1])\n",
    "            \n",
    "            #barat laut\n",
    "            k8 = np.square(5 * image[i - 1, j - 1] + 5 * image[i - 1, j] - 3 * image[i - 1, j + 1] +\n",
    "                  5 * image[i, j - 1] - 3 * image[i, j + 1] - 3 * image[i + 1, j - 1] -\n",
    "                  3 * image[i + 1, j] - 3 * image[i + 1, j + 1])\n",
    "            \n",
    "            list=[k1, k2, k3, k4, k5, k6, k7, k8]\n",
    "            kirsch[i,j]= int(np.sqrt(max(list)))\n",
    "                         \n",
    "    for i in range(x):\n",
    "        for j in range(y):\n",
    "            if kirsch[i,j]>127:\n",
    "                kirsch[i,j]=255\n",
    "            else:\n",
    "                kirsch[i,j]=0\n",
    "    return kirsch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def robinson(image):\n",
    "    m,n = image.shape\n",
    "    list=[]\n",
    "    robinson = np.zeros((m,n))\n",
    "    for i in range(2,m-1):\n",
    "        for j in range(2,n-1):\n",
    "            \n",
    "            #utara\n",
    "            r1 = np.square(1 * image[i - 1, j - 1] + 2 * image[i - 1, j] + 1 * image[i - 1, j + 1] -\n",
    "                  1 * image[i + 1, j - 1] - 2 * image[i + 1, j] - 1 * image[i + 1, j + 1])\n",
    "            \n",
    "            #timur laut\n",
    "            r2 = np.square(1 * image[i - 1, j] + 2 * image[i - 1, j + 1] -\n",
    "                  1 * image[i, j - 1] + 1 * image[i, j + 1] - 2 * image[i + 1, j - 1] - 1 * image[i + 1, j])\n",
    "            \n",
    "            #timur\n",
    "            r3 = np.square((-1) * image[i - 1, j - 1] + 1 * image[i - 1, j + 1] - 2 * image[i, j - 1] +\n",
    "                  2 * image[i, j + 1] - 1 * image[i + 1, j - 1] + 1 * image[i + 1, j + 1])\n",
    "            \n",
    "            #tenggara\n",
    "            r4 = np.square((-2) * image[i - 1, j - 1] - 1 * image[i - 1, j] - 1 * image[i, j - 1] + \n",
    "                  1 * image[i, j + 1] + 1 * image[i + 1, j] + 2 * image[i + 1, j + 1])\n",
    "            \n",
    "            #selatan\n",
    "            r5 = np.square((-1) * image[i - 1, j - 1] - 2 * image[i - 1, j] - 1 * image[i - 1, j + 1] +\n",
    "                  1 * image[i + 1, j - 1] + 2 * image[i + 1, j] + 1 * image[i + 1, j + 1])\n",
    "            \n",
    "            #barat daya\n",
    "            r6 = np.square((-1) * image[i - 1, j] - 2 * image[i - 1, j + 1] + 1 * image[i, j - 1] - \n",
    "                  1 * image[i, j + 1] + 2 * image[i + 1, j - 1] + 1 * image[i + 1, j])\n",
    "            \n",
    "            #barat\n",
    "            r7 = np.square(1 * image[i - 1, j - 1] - 1 * image[i - 1, j + 1] + 2 * image[i, j - 1] - \n",
    "                  2 * image[i, j + 1] + 1 * image[i + 1, j - 1] - 1 * image[i + 1, j + 1])\n",
    "            \n",
    "            #barat laut\n",
    "            r8 = np.square(2 * image[i - 1, j - 1] + 1 * image[i - 1, j] + 1 * image[i, j - 1] - \n",
    "                  1 * image[i, j + 1] - 1 * image[i + 1, j] - 2 * image[i + 1, j + 1])\n",
    "\n",
    "            list=[r1, r2, r3, r4, r5, r6, r7, r8]\n",
    "            robinson[i,j]= int(np.sqrt(max(list)))\n",
    "                         \n",
    "    for i in range(m):\n",
    "        for j in range(n):\n",
    "            if robinson[i,j]>127:\n",
    "                robinson[i,j]=255\n",
    "            else:\n",
    "                robinson[i,j]=0\n",
    "    return robinson"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> MOMENT CITRA </h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# gambarK = np.array(kirsch(image))\n",
    "# gambarR = np.array(robinson(image))\n",
    "\n",
    "# m,n = gambarK.shape\n",
    "\n",
    "# print(m, n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def moment (gambar):\n",
    "    \n",
    "    m,n = gambar.shape\n",
    "\n",
    "    hasil_00 = []\n",
    "    hasil_10 = []\n",
    "    hasil_01 = []\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1) ** 0\n",
    "        for j in range(n):\n",
    "            y = (j+1) ** 0\n",
    "            M00 = x * y * gambar[i,j]\n",
    "            hasil_00.append(M00)\n",
    "\n",
    "    moment_00 = sum(hasil_00)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1) ** 1\n",
    "        for j in range(n):\n",
    "            y = (j+1) ** 0\n",
    "            M10 = x * y * gambar[i,j]\n",
    "            hasil_10.append(M10)\n",
    "\n",
    "    moment_10 = sum(hasil_10)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1) ** 0\n",
    "        for j in range(n):\n",
    "            y = (j+1) ** 1\n",
    "            M01 = x * y * gambar[i,j]\n",
    "            hasil_01.append(M01)\n",
    "\n",
    "    moment_01 = sum(hasil_01)\n",
    "\n",
    "#     print(\"Moment Citra p,q (0,0) : \"+str(moment_00))\n",
    "#     print(\"Moment Citra p,q (1,0) : \"+str(moment_10))\n",
    "#     print(\"Moment Citra p,q (0,1) : \"+str(moment_01))\n",
    "    \n",
    "    return([moment_00,moment_01,moment_10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> X & Y MEAN </h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mean(gambar):\n",
    "    \n",
    "    momen = moment(gambar)\n",
    "    \n",
    "    moment_10 = momen[2]\n",
    "    moment_00 = momen[0]\n",
    "    moment_01 = momen[1]\n",
    "    \n",
    "    Xmean = moment_10/moment_00\n",
    "    Ymean = moment_01/moment_00\n",
    "    \n",
    "#     print(\"\\n\")\n",
    "#     print(\"X mean : \" + str(Xmean))\n",
    "#     print(\"Y mean : \" + str(Ymean))\n",
    "    \n",
    "    return([Xmean, Ymean])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> CENTRAL MOMENT CITRA </h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def central(gambar):\n",
    "\n",
    "    XYmean = mean(gambar)\n",
    "    \n",
    "    m,n = gambar.shape\n",
    "    \n",
    "    Xmean = XYmean[0]\n",
    "    Ymean = XYmean[1]\n",
    "\n",
    "    hasilCM_00 = []\n",
    "    hasilCM_01 = []\n",
    "    hasilCM_10 = []\n",
    "    hasilCM_11 = []\n",
    "    hasilCM_02 = []\n",
    "    hasilCM_20 = []\n",
    "    hasilCM_12 = []\n",
    "    hasilCM_21 = []\n",
    "    hasilCM_03 = []\n",
    "    hasilCM_30 = []\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 0\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 0\n",
    "            CM00 = x * y * gambar[i,j]\n",
    "            hasilCM_00.append(CM00)\n",
    "\n",
    "    Cmoment_00 = sum(hasilCM_00)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 0\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 1\n",
    "            CM01 = x * y * gambar[i,j]\n",
    "            hasilCM_01.append(CM01)\n",
    "\n",
    "    Cmoment_01 = sum(hasilCM_01)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 1\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 0\n",
    "            CM10 = x * y * gambar[i,j]\n",
    "            hasilCM_10.append(CM10)\n",
    "\n",
    "    Cmoment_10 = sum(hasilCM_10)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 1\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 1\n",
    "            CM11 = x * y * gambar[i,j]\n",
    "            hasilCM_11.append(CM11)\n",
    "\n",
    "    Cmoment_11 = sum(hasilCM_11)\n",
    "    \n",
    "    \n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 0\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 2\n",
    "            CM02 = x * y * gambar[i,j]\n",
    "            hasilCM_02.append(CM02)\n",
    "\n",
    "    Cmoment_02 = sum(hasilCM_02)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 2\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 0\n",
    "            CM20 = x * y * gambar[i,j]\n",
    "            hasilCM_20.append(CM20)\n",
    "\n",
    "    Cmoment_20 = sum(hasilCM_20)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 1\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 2\n",
    "            CM12 = x * y * gambar[i,j]\n",
    "            hasilCM_12.append(CM12)\n",
    "\n",
    "    Cmoment_12 = sum(hasilCM_12)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 2\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 1\n",
    "            CM21 = x * y * gambar[i,j]\n",
    "            hasilCM_21.append(CM21)\n",
    "\n",
    "    Cmoment_21 = sum(hasilCM_21)\n",
    "    \n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 0\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 3\n",
    "            CM03 = x * y * gambar[i,j]\n",
    "            hasilCM_03.append(CM03)\n",
    "        \n",
    "    Cmoment_03 = sum(hasilCM_03)\n",
    "\n",
    "    for i in range(m):\n",
    "        x = (i+1 - Xmean) ** 3\n",
    "        for j in range(n):\n",
    "            y = (j+1 - Ymean) ** 0\n",
    "            CM30 = x * y * gambar[i,j]\n",
    "            hasilCM_30.append(CM30)\n",
    "\n",
    "    Cmoment_30 = sum(hasilCM_30)\n",
    "\n",
    "#     print(\"\\n\")\n",
    "#     print(\"Central Moment Citra p,q (0,0) : \"+str(Cmoment_00))\n",
    "#     print(\"Central Moment Citra p,q (0,1) : \"+str(Cmoment_01))\n",
    "#     print(\"Central Moment Citra p,q (1,0) : \"+str(Cmoment_10))\n",
    "#     print(\"Central Moment Citra p,q (1,1) : \"+str(Cmoment_11))\n",
    "    \n",
    "#     print(\"Central Moment Citra p,q (0,2) : \"+str(Cmoment_02))\n",
    "#     print(\"Central Moment Citra p,q (2,0) : \"+str(Cmoment_20))\n",
    "#     print(\"Central Moment Citra p,q (1,2) : \"+str(Cmoment_12))\n",
    "#     print(\"Central Moment Citra p,q (2,1) : \"+str(Cmoment_21))\n",
    "    \n",
    "#     print(\"Central Moment Citra p,q (0,3) : \"+str(Cmoment_03))\n",
    "#     print(\"Central Moment Citra p,q (3,0) : \"+str(Cmoment_30))\n",
    "    \n",
    "    return([Cmoment_00, Cmoment_01, Cmoment_10, Cmoment_11, Cmoment_02, Cmoment_20, Cmoment_12, Cmoment_21, Cmoment_03, Cmoment_30])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> NORMALIZED CENTRAL MOMENT </h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normal_central(gambar):\n",
    "\n",
    "    central_momen = central(gambar)\n",
    "    \n",
    "    Cmoment_00 = central_momen[0]\n",
    "    Cmoment_11 = central_momen[3]\n",
    "    Cmoment_02 = central_momen[4]\n",
    "    Cmoment_20 = central_momen[5]\n",
    "    Cmoment_12 = central_momen[6]\n",
    "    Cmoment_21 = central_momen[7]\n",
    "    Cmoment_03 = central_momen[8]\n",
    "    Cmoment_30 = central_momen[9]\n",
    "\n",
    "    gamma11 = ((1 + 1) / 2) + 1\n",
    "    gamma02 = ((0 + 2) / 2) + 1\n",
    "    gamma12 = ((1 + 2) / 2) + 1\n",
    "    gamma03 = ((0 + 3) / 2) + 1\n",
    "\n",
    "    NCM11 = Cmoment_11 / (Cmoment_00**gamma11)\n",
    "    NCM02 = Cmoment_02 / (Cmoment_00**gamma02)\n",
    "    NCM20 = Cmoment_20 / (Cmoment_00**gamma02)\n",
    "    NCM12 = Cmoment_12 / (Cmoment_00**gamma12)\n",
    "    NCM21 = Cmoment_21 / (Cmoment_00**gamma12)\n",
    "    NCM03 = Cmoment_03 / (Cmoment_00**gamma03)\n",
    "    NCM30 = Cmoment_30 / (Cmoment_00**gamma03)\n",
    "\n",
    "#     print(\"\\n\")\n",
    "#     print(\"Normalized Central Moment p,q (1,1) : \" + str(NCM11))\n",
    "#     print(\"Normalized Central Moment p,q (0,2) : \" + str(NCM02))\n",
    "#     print(\"Normalized Central Moment p,q (2,0) : \" + str(NCM20))\n",
    "#     print(\"Normalized Central Moment p,q (1,2) : \" + str(NCM12))\n",
    "#     print(\"Normalized Central Moment p,q (2,1) : \" + str(NCM21))\n",
    "#     print(\"Normalized Central Moment p,q (0,3) : \" + str(NCM03))\n",
    "#     print(\"Normalized Central Moment p,q (3,0) : \" + str(NCM30))\n",
    "    \n",
    "    return([NCM11, NCM02, NCM20, NCM12, NCM21, NCM03, NCM30])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> GEOMETRIC INVARIANT MOMENT </h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gim(gambar):\n",
    "    \n",
    "    ncm = normal_central(gambar)\n",
    "\n",
    "    NCM11 = ncm[0]\n",
    "    NCM02 = ncm[1]\n",
    "    NCM20 = ncm[2]\n",
    "    NCM12 = ncm[3]\n",
    "    NCM21 = ncm[4]\n",
    "    NCM03 = ncm[5]\n",
    "    NCM30 = ncm[6]\n",
    "\n",
    "    fitur_bentuk = []\n",
    "\n",
    "    M1 = NCM20 + NCM02\n",
    "    M2 = (NCM20 + NCM20)**2 + (2*NCM02)**2\n",
    "    M3 = (NCM30 - NCM12)**2 + (3*NCM21 - NCM03)**2\n",
    "    M4 = (NCM30 + NCM12)**2 + (NCM21 + NCM03)**2\n",
    "    M5 = (NCM30 - 3*NCM12) * (NCM30 + NCM12) * ((NCM30 + NCM12)**2 - 3*(NCM21 + NCM03)**2) + (3*NCM21 - NCM03) * (NCM21 + NCM03) * (3*(NCM30 + NCM12)**2 - (NCM21 + NCM03)**2)\n",
    "    M6 = (NCM20 - NCM02) * ((NCM30 + NCM12)**2 - 3*(NCM21 + NCM03)**2) + 4*NCM11 * (NCM30 + NCM12) * (NCM21 + NCM03)\n",
    "    M7 = (3*NCM21 - NCM03) * (NCM30 + NCM12) * ((NCM30 + NCM12)**2 - 3*(NCM21 + NCM03)**2) + (3*NCM12 - NCM30) * (NCM21 + NCM03) * (3*(NCM30 + NCM12)**2 - (NCM21 + NCM03)**2)\n",
    "\n",
    "#     print(\"\\n\")\n",
    "#     print(\"M1 = \" + str(M1))\n",
    "#     print(\"M2 = \" + str(M2))\n",
    "#     print(\"M3 = \" + str(M3))\n",
    "#     print(\"M4 = \" + str(M4))\n",
    "#     print(\"M5 = \" + str(M5))\n",
    "#     print(\"M6 = \" + str(M6))\n",
    "#     print(\"M7 = \" + str(M7))\n",
    "\n",
    "    fitur_bentuk = [M1, M2, M3, M4, M5, M6, M7]\n",
    "    \n",
    "    return(fitur_bentuk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> FITUR BENTUK dari ED KIRSCH </h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.000005</td>\n",
       "      <td>1.160000e-13</td>\n",
       "      <td>1.400000e-12</td>\n",
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       "      <td>5.890000e-25</td>\n",
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       "      <td>1.180000e-12</td>\n",
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       "      <td>110</td>\n",
       "      <td>23</td>\n",
       "      <td>0.001122</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>1.210000e-12</td>\n",
       "      <td>1.980000e-12</td>\n",
       "      <td>1.570000e-24</td>\n",
       "      <td>7.120000e-16</td>\n",
       "      <td>1.690000e-24</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <td>111</td>\n",
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       "      <td>0.001107</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>7.910000e-13</td>\n",
       "      <td>1.530000e-12</td>\n",
       "      <td>7.630000e-25</td>\n",
       "      <td>4.490000e-16</td>\n",
       "      <td>-8.350000e-25</td>\n",
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       "      <td>112</td>\n",
       "      <td>23b</td>\n",
       "      <td>0.001103</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>6.670000e-13</td>\n",
       "      <td>9.970000e-13</td>\n",
       "      <td>3.920000e-25</td>\n",
       "      <td>3.040000e-16</td>\n",
       "      <td>5.460000e-25</td>\n",
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       "    <tr>\n",
       "      <td>113</td>\n",
       "      <td>23c</td>\n",
       "      <td>0.000994</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2.860000e-13</td>\n",
       "      <td>9.000000e-13</td>\n",
       "      <td>-2.450000e-25</td>\n",
       "      <td>-1.300000e-16</td>\n",
       "      <td>-2.710000e-25</td>\n",
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       "      <td>0.000003</td>\n",
       "      <td>3.620000e-13</td>\n",
       "      <td>1.520000e-12</td>\n",
       "      <td>7.180000e-25</td>\n",
       "      <td>1.820000e-15</td>\n",
       "      <td>8.100000e-25</td>\n",
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       "<p>115 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    citra        m1        m2            m3            m4            m5  \\\n",
       "0       1  0.001667  0.000006  1.120000e-12  1.050000e-12 -4.260000e-25   \n",
       "1      1a  0.001666  0.000006  1.240000e-12  1.150000e-12 -2.180000e-26   \n",
       "2      1b  0.001664  0.000006  1.550000e-12  1.150000e-12 -2.630000e-25   \n",
       "3      1c  0.001550  0.000005  1.160000e-13  1.400000e-12  5.270000e-25   \n",
       "4      1d  0.001665  0.000006  1.170000e-13  1.180000e-12 -2.060000e-25   \n",
       "..    ...       ...       ...           ...           ...           ...   \n",
       "110    23  0.001122  0.000003  1.210000e-12  1.980000e-12  1.570000e-24   \n",
       "111   23a  0.001107  0.000003  7.910000e-13  1.530000e-12  7.630000e-25   \n",
       "112   23b  0.001103  0.000003  6.670000e-13  9.970000e-13  3.920000e-25   \n",
       "113   23c  0.000994  0.000002  2.860000e-13  9.000000e-13 -2.450000e-25   \n",
       "114   23d  0.001105  0.000003  3.620000e-13  1.520000e-12  7.180000e-25   \n",
       "\n",
       "               m6            m7  jenis  \n",
       "0   -1.290000e-15 -1.050000e-24      1  \n",
       "1   -1.240000e-15  1.300000e-24      1  \n",
       "2   -1.410000e-15 -1.470000e-24      1  \n",
       "3   -3.710000e-16  5.890000e-25      1  \n",
       "4    1.170000e-16  1.460000e-24      1  \n",
       "..            ...           ...    ...  \n",
       "110  7.120000e-16  1.690000e-24      0  \n",
       "111  4.490000e-16 -8.350000e-25      0  \n",
       "112  3.040000e-16  5.460000e-25      0  \n",
       "113 -1.300000e-16 -2.710000e-25      0  \n",
       "114  1.820000e-15  8.100000e-25      0  \n",
       "\n",
       "[115 rows x 9 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_data_k = pd.read_csv('kirsch.csv')\n",
    "file_data_k"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> FITUR BENTUK dari ED ROBINSON </h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2</td>\n",
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       "      <td>3</td>\n",
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       "      <td>2.050000e-12</td>\n",
       "      <td>-7.530000e-25</td>\n",
       "      <td>-4.240000e-16</td>\n",
       "      <td>1.070000e-24</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
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       "      <td>1.120000e-13</td>\n",
       "      <td>1.640000e-12</td>\n",
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       "      <td>2.610000e-16</td>\n",
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       "      <td>110</td>\n",
       "      <td>23</td>\n",
       "      <td>0.001165</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>1.520000e-12</td>\n",
       "      <td>2.530000e-12</td>\n",
       "      <td>2.260000e-24</td>\n",
       "      <td>9.320000e-16</td>\n",
       "      <td>2.900000e-24</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>111</td>\n",
       "      <td>23a</td>\n",
       "      <td>0.001150</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>9.970000e-13</td>\n",
       "      <td>1.970000e-12</td>\n",
       "      <td>1.110000e-24</td>\n",
       "      <td>5.800000e-16</td>\n",
       "      <td>-1.460000e-24</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>112</td>\n",
       "      <td>23b</td>\n",
       "      <td>0.001145</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>8.290000e-13</td>\n",
       "      <td>1.310000e-12</td>\n",
       "      <td>5.300000e-25</td>\n",
       "      <td>3.960000e-16</td>\n",
       "      <td>9.440000e-25</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>113</td>\n",
       "      <td>23c</td>\n",
       "      <td>0.001031</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>3.020000e-13</td>\n",
       "      <td>1.050000e-12</td>\n",
       "      <td>-4.220000e-25</td>\n",
       "      <td>-1.800000e-16</td>\n",
       "      <td>-2.460000e-25</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <td>114</td>\n",
       "      <td>23d</td>\n",
       "      <td>0.001148</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>4.550000e-13</td>\n",
       "      <td>1.980000e-12</td>\n",
       "      <td>1.070000e-24</td>\n",
       "      <td>2.450000e-15</td>\n",
       "      <td>1.440000e-24</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>115 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    citra        m1        m2            m3            m4            m5  \\\n",
       "0       1  0.001761  0.000007  2.080000e-12  1.510000e-12 -1.960000e-25   \n",
       "1      1a  0.001760  0.000007  2.000000e-12  1.620000e-12  4.840000e-25   \n",
       "2      1b  0.001759  0.000007  2.720000e-12  1.660000e-12  3.610000e-25   \n",
       "3      1c  0.001637  0.000005  4.280000e-13  2.050000e-12 -7.530000e-25   \n",
       "4      1d  0.001760  0.000007  1.120000e-13  1.640000e-12  8.030000e-26   \n",
       "..    ...       ...       ...           ...           ...           ...   \n",
       "110    23  0.001165  0.000003  1.520000e-12  2.530000e-12  2.260000e-24   \n",
       "111   23a  0.001150  0.000003  9.970000e-13  1.970000e-12  1.110000e-24   \n",
       "112   23b  0.001145  0.000003  8.290000e-13  1.310000e-12  5.300000e-25   \n",
       "113   23c  0.001031  0.000002  3.020000e-13  1.050000e-12 -4.220000e-25   \n",
       "114   23d  0.001148  0.000003  4.550000e-13  1.980000e-12  1.070000e-24   \n",
       "\n",
       "               m6            m7  jenis  \n",
       "0   -1.830000e-15 -2.590000e-24      1  \n",
       "1   -1.800000e-15  2.740000e-24      1  \n",
       "2   -1.950000e-15 -3.400000e-24      1  \n",
       "3   -4.240000e-16  1.070000e-24      1  \n",
       "4    2.610000e-16  3.090000e-24      1  \n",
       "..            ...           ...    ...  \n",
       "110  9.320000e-16  2.900000e-24      0  \n",
       "111  5.800000e-16 -1.460000e-24      0  \n",
       "112  3.960000e-16  9.440000e-25      0  \n",
       "113 -1.800000e-16 -2.460000e-25      0  \n",
       "114  2.450000e-15  1.440000e-24      0  \n",
       "\n",
       "[115 rows x 9 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_data_r = pd.read_csv('robinson.csv')\n",
    "file_data_r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> TRAIN DATA K-NN </h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataK = np.array(file_data_k)\n",
    "dataR = np.array(file_data_r)\n",
    "\n",
    "X1 = dataK[:, 1:8]\n",
    "X1 = X1.astype('float64')\n",
    "y1 = dataK[:, -1]\n",
    "y1 = y1.astype('float64')\n",
    "\n",
    "X2 = dataR[:, 1:8]\n",
    "X2 = X2.astype('float64')\n",
    "y2 = dataR[:, -1]\n",
    "y2 = y2.astype('float64')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> K-NN CLASSIFIER </h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def euclidean_distance(x1, x2):\n",
    "    return np.sqrt(np.sum((x1-x2)**2))\n",
    "\n",
    "class KNN:\n",
    "    \n",
    "    def __init__(self, k=9):\n",
    "        self.k = k\n",
    "        \n",
    "    def fit(self, X, y):\n",
    "        self.X_train = X\n",
    "        self.y_train = y\n",
    "        \n",
    "    def prediksi(self, x):\n",
    "        distance = [euclidean_distance(x, x_train) for x_train in self.X_train]\n",
    "        k_distance = np.argsort(distance)[:self.k]\n",
    "        k_nearest_label = [self.y_train[i] for i in k_distance]\n",
    "        most_common = Counter(k_nearest_label).most_common(1)\n",
    "        return most_common[0][0]\n",
    "        \n",
    "    def predict(self, X):\n",
    "        prediksi = [self.prediksi(x) for x in X]\n",
    "        return np.array(prediksi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connecting to wss://anvil.works/uplink\n",
      "Anvil websocket open\n",
      "Connected to \"Default environment (dev)\" as SERVER\n"
     ]
    }
   ],
   "source": [
    "import anvil.server\n",
    "import anvil.media\n",
    "\n",
    "citra = []\n",
    "citra = np.array(citra)\n",
    "\n",
    "anvil.server.connect(\"45O6OFWG7MWL452R6GGYQFXF-GEC2QKGYLT2DSN2J\")\n",
    "@anvil.server.callable\n",
    "\n",
    "def gambar(file):\n",
    "    with anvil.media.TempFile(file) as filename:\n",
    "        global citra\n",
    "        citra = cv2.imread(filename)\n",
    "#         citra.append(batik)\n",
    "#         print(type(batik))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# citra = np.array(citra)\n",
    "# citra.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "@anvil.server.callable\n",
    "def guiK():\n",
    "    \n",
    "    global citra\n",
    "    cv2.imwrite(\"ini.jpeg\",citra)\n",
    "    cv2.imread(\"ini.jpeg\")\n",
    "\n",
    "    imageN = citra\n",
    "    batik = img(imageN)\n",
    "    image = batik[1]\n",
    "    imageG = batik[0]\n",
    "\n",
    "    gambarK = np.array(kirsch(image))\n",
    "\n",
    "    m,n = gambarK.shape\n",
    "\n",
    "    #     print(m, n)\n",
    "\n",
    "    cv2.imwrite(\"hasilK.jpeg\",gambarK)\n",
    "\n",
    "    citra_DTK =  cv2.imread('hasilK.jpeg')\n",
    "    \n",
    "    fitur_bentuk_K = gim(gambarK)\n",
    "\n",
    "    k=9\n",
    "\n",
    "    #KIRSCH\n",
    "    clf = KNN(k)\n",
    "    clf.fit(X1, y1)\n",
    "    prediksiK = clf.predict([fitur_bentuk_K])\n",
    "\n",
    "    print(\"\\n\")\n",
    "    print('========= KIRSCH =========')    \n",
    "    if prediksiK == 0:\n",
    "        hasilK = 0\n",
    "        print('Prediksi : Non-Parang Rusak')\n",
    "    else :\n",
    "        hasilK = 1\n",
    "        print('Prediksi : Parang Rusak')\n",
    "\n",
    "    \n",
    "    gray_byte_arr = io.BytesIO()\n",
    "    biner_byte_arr = io.BytesIO()\n",
    "    DTK_byte_arr = io.BytesIO()\n",
    "    \n",
    "    DTK = Image.fromarray(citra_DTK)\n",
    "    DTK.save(DTK_byte_arr,format=\"JPEG\")\n",
    "    img_DTK = DTK_byte_arr.getvalue()\n",
    "    media_DTK = anvil.BlobMedia(content_type=\"image/jpeg\", content=img_DTK)\n",
    "    \n",
    "    gray = Image.fromarray(imageG,\"L\")\n",
    "    gray.save(gray_byte_arr,format=\"JPEG\")\n",
    "    img_gray = gray_byte_arr.getvalue()\n",
    "    media_gray = anvil.BlobMedia(content_type=\"image/jpeg\", content=img_gray)\n",
    "    \n",
    "    biner = Image.fromarray(image,\"L\")\n",
    "    biner.save(biner_byte_arr, format=\"JPEG\")\n",
    "    img_biner = biner_byte_arr.getvalue()\n",
    "    media_biner = anvil.BlobMedia(content_type=\"image/jpeg\", content=img_biner)\n",
    "    \n",
    "    return([fitur_bentuk_K, hasilK, media_gray, media_biner, media_DTK])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(300, 200)\n",
      "\n",
      "\n",
      "========= KIRSCH =========\n",
      "Prediksi : Parang Rusak\n"
     ]
    }
   ],
   "source": [
    "@anvil.server.callable\n",
    "def guiR():\n",
    "    \n",
    "    global citra\n",
    "    cv2.imwrite(\"ini.jpeg\",citra)\n",
    "    cv2.imread(\"ini.jpeg\")\n",
    "\n",
    "    imageN = citra\n",
    "    batik = img(imageN)\n",
    "    image = batik[1]\n",
    "    imageG = batik[0]\n",
    "\n",
    "    gambarR = np.array(robinson(image))\n",
    "\n",
    "    m,n = gambarR.shape\n",
    "\n",
    "    #     print(m, n)\n",
    "\n",
    "    cv2.imwrite(\"hasilR.jpeg\",gambarR)\n",
    "\n",
    "    citra_DTR =  cv2.imread('hasilR.jpeg')\n",
    "    \n",
    "    fitur_bentuk_R = gim(gambarR)\n",
    "\n",
    "    k=9\n",
    "\n",
    "    #ROBINSON\n",
    "    clf = KNN(k)\n",
    "    clf.fit(X2, y2)\n",
    "    prediksiR = clf.predict([fitur_bentuk_R])\n",
    "\n",
    "    print(\"\\n\")\n",
    "    print('========= ROBINSON =========')\n",
    "    if prediksiR == 0:\n",
    "        hasilR = 0\n",
    "        print('Prediksi : Non-Parang Rusak')\n",
    "    else :\n",
    "        hasilR = 1\n",
    "        print('Prediksi : Parang Rusak')\n",
    "    \n",
    "    gray_byte_arr = io.BytesIO()\n",
    "    biner_byte_arr = io.BytesIO()\n",
    "    DTR_byte_arr = io.BytesIO()\n",
    "    \n",
    "    DTR = Image.fromarray(citra_DTR)\n",
    "    DTR.save(DTR_byte_arr,format=\"JPEG\")\n",
    "    img_DTR = DTR_byte_arr.getvalue()\n",
    "    media_DTR = anvil.BlobMedia(content_type=\"image/jpeg\", content=img_DTR)\n",
    "    \n",
    "    gray = Image.fromarray(imageG,\"L\")\n",
    "    gray.save(gray_byte_arr,format=\"JPEG\")\n",
    "    img_gray = gray_byte_arr.getvalue()\n",
    "    media_gray = anvil.BlobMedia(content_type=\"image/jpeg\", content=img_gray)\n",
    "    \n",
    "    biner = Image.fromarray(image,\"L\")\n",
    "    biner.save(biner_byte_arr, format=\"JPEG\")\n",
    "    img_biner = biner_byte_arr.getvalue()\n",
    "    media_biner = anvil.BlobMedia(content_type=\"image/jpeg\", content=img_biner)\n",
    "    \n",
    "    return([fitur_bentuk_R, hasilR, media_gray, media_biner, media_DTR])"
   ]
  }
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