DroneDataClassification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Python 3's print function and division\n",
    "from __future__ import print_function, division\n",
    "import os\n",
    "from numpy import *\n",
    "import rasterio as rio\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "# Tell GDAL to throw Python exceptions, and register all drivers\n",
    "import numba"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def norm(band):\n",
    "    band_min, band_max = band.min(), band.max()\n",
    "    return ((band - band_min)/(band_max - band_min))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def CreateGeoTiff(Name, Array, DataType, NDV, bandnames=None, ref_image=None, GeoT=None, Projection=None):\n",
    "    # If it's a 2D image we fake a third dimension:\n",
    "    if len(Array.shape) == 2:\n",
    "        Array = np.array([Array])\n",
    "    if ref_image == None and (GeoT == None or Projection == None):\n",
    "        raise RuntimeWarning('ref_image or settings required.')\n",
    "    if bandnames != None:\n",
    "        if len(bandnames) != Array.shape[0]:\n",
    "            raise RuntimeError('Need {} bandnames. {} given'\n",
    "                               .format(Array.shape[0], len(bandnames)))\n",
    "    else:\n",
    "        bandnames = ['Band {}'.format(i+1) for i in range(Array.shape[0])]\n",
    "    if ref_image != None:\n",
    "        refimg = gdal.Open(ref_image)\n",
    "        GeoT = refimg.GetGeoTransform()\n",
    "        Projection = refimg.GetProjection()\n",
    "    driver = gdal.GetDriverByName('GTIFF')\n",
    "    Array[np.isnan(Array)] = NDV\n",
    "    DataSet = driver.Create(\n",
    "        Name, Array.shape[2], Array.shape[1], Array.shape[0], DataType)\n",
    "    DataSet.SetGeoTransform(GeoT)\n",
    "    DataSet.SetProjection(Projection)\n",
    "    for i, image in enumerate(Array, 1):\n",
    "        DataSet.GetRasterBand(i).WriteArray(image)\n",
    "        DataSet.GetRasterBand(i).SetNoDataValue(NDV)\n",
    "        DataSet.SetDescription(bandnames[i-1])\n",
    "    DataSet.FlushCache()\n",
    "    return Name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# next setup a colormap for our map\n",
    "colors = dict((\n",
    "    (0, (0, 0, 0, 255)),  # No data\n",
    "    (1, (0, 255, 0, 255)),   # Green - C Water H\n",
    "    (2, (255, 0, 0, 255)),  # Lime - Other Vegatation\n",
    "    (3, (0, 0, 255, 255)),   # Blue - Water L\n",
    "    (4, (255, 255, 0, 255)),   # Blue - Water D\n",
    "    (5, (255, 0, 255, 255)),   # Tan - Forest\n",
    "     (6, (0, 255, 255, 255)),   # Tan - Forest\n",
    "     (7, (255, 255, 255, 255)),   # Tan - Forest\n",
    "))\n",
    "\n",
    "n = 8\n",
    "# Put 0 - 255 as float 0 - 1\n",
    "for k in colors:\n",
    "    v = colors[k]\n",
    "    _v = [_v / 255.0 for _v in v]\n",
    "    colors[k] = _v\n",
    "\n",
    "index_colors = [colors[key] if key in colors else\n",
    "                (255, 255, 255, 0) for key in range(0, n+1)]\n",
    "\n",
    "cmap = plt.matplotlib.colors.ListedColormap(\n",
    "    index_colors, 'Classification', n+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_band_image(path,dronedata):\n",
    "    \"\"\"\n",
    "    This function takes as input the ldrone image and the path of the \n",
    "    folder that the images are stored, reads the image and returns the data as\n",
    "    an array\n",
    "    input:   drone          drone image\n",
    "             path           string            path ,of the folder\n",
    "    output:  data           array (n x m)     array of the band image\n",
    "             spatialRef     string            projection \n",
    "             geoTransform   tuple             affine transformation coefficients\n",
    "             targetprj                        spatial reference\n",
    "    \"\"\"\n",
    "    import os\n",
    "    import rasterio\n",
    "\n",
    "    \n",
    "    os.chdir(path)\n",
    "    os.getcwd()\n",
    "    img_ds=rasterio.open(dronedata)\n",
    "    data = np.zeros((img_ds.height, img_ds.width, img_ds.count))\n",
    "                   \n",
    "\n",
    "    for b in range(data.shape[2]):\n",
    "        data[:, :, b] = np.array(img_ds.read(b+1))\n",
    "    crs=img_ds.crs\n",
    "    \n",
    "    geoTransform = img_ds.transform\n",
    "    return data, crs, geoTransform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def visRGB(img1, img2, img3,\n",
    "           title = 'RGB image',\n",
    "           scale1 = [],\n",
    "           scale2 = [],\n",
    "           scale3 = [],\n",
    "           flag = 0, outall = ''):\n",
    "    \"\"\"\n",
    "    Visualise the RGB of a single acquisition\n",
    "    \"\"\"           \n",
    "    if scale1 == []:\n",
    "       scale1 = img1\n",
    "    if scale2 == []:\n",
    "       scale2 = img2\n",
    "    if scale3 == []:\n",
    "       scale3 = img3\n",
    "\n",
    "    size = np.shape(img1)           \n",
    "    iRGB = np.zeros([size[0],size[1],3])\n",
    "    iRGB[:,:,0] = np.abs(img1)/(np.abs(scale1).mean()*1.5)\n",
    "    iRGB[:,:,1] = np.abs(img2)/(np.abs(scale2).mean()*1.5)\n",
    "    iRGB[:,:,2] = np.abs(img3)/(np.abs(scale3).mean()*1.5)\n",
    "    iRGB[np.abs(iRGB) > 1] = 1\n",
    "            \n",
    "#    plt.figure()\n",
    "\n",
    "    fig = plt.figure(figsize=(8,8))\n",
    "    ax2 = fig.add_subplot(1,1,1)\n",
    "    plot = plt.imshow(iRGB); \n",
    "    plt.title('(RGB image)'); \n",
    "    cbar = plt.colorbar(plot,aspect=20); plt.set_cmap('gist_earth'); \n",
    "    cbar.set_label('Reflectance',rotation=90,labelpad=20); \n",
    "    ax2.ticklabel_format(useOffset=False, style='plain') #do not use scientific notation \n",
    "    rotatexlabels = plt.setp(ax2.get_xticklabels(),rotation=90) #rotate x tick labels 90 degrees\n",
    "\n",
    "    if flag == 1:\n",
    "        fig.savefig(outall)\n",
    "\n",
    "    return       \n",
    "           "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "GTdirectory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "datadirectory='/space/vak/Weedwatch/Patancheru/Drone/Images/'\n",
    "GTdirectory='/space/vak/Weedwatch/Patancheru/Drone/GT/Anoop Labels/Rasterized/'\n",
    "\n",
    "imagefile_1 = 'Orthomosaic_28Jan2021_PatanCheru_AOI.tif'\n",
    "GTfile_1 = 'GT_Orthophoto_28Jan2021_5cm_AOI.tif'\n",
    "(img1, crs, geoTransform) = read_band_image(datadirectory,imagefile_1)\n",
    "(gt1,crs, geoTransform) = read_band_image(GTdirectory,GTfile_1)\n",
    "\n",
    "\n",
    "imagefile_2 = 'Orthomosaic_15Feb2021_PatanCheru_AOI.tif'\n",
    "GTfile_2 = 'GT_Orthophoto_15Feb2021_5cm_AOI.tif'\n",
    "(img2, crs, geoTransform) = read_band_image(datadirectory,imagefile_2)\n",
    "(gt2,crs, geoTransform) = read_band_image(GTdirectory,GTfile_2)\n",
    "\n",
    "imagefile_3 = 'Orthomosaic_26Mar2021_PatanCheru_AOI.tif'\n",
    "GTfile_3 = 'GT_Orthophoto_26Mar2021_5cm_AOI.tif'\n",
    "(img3, crs, geoTransform) = read_band_image(datadirectory,imagefile_3)\n",
    "(gt3,crs, geoTransform) = read_band_image(GTdirectory,GTfile_3)\n",
    "\n",
    "imagefile_4 = 'Orthomosaic_06June2021_Patancheru_AOI.tif'\n",
    "GTfile_4 = 'GT_Orthophoto_06Jun2021_5cm_AOI.tif'\n",
    "(img4, crs, geoTransform) = read_band_image(datadirectory,imagefile_4)\n",
    "(gt4,crs, geoTransform) = read_band_image(GTdirectory,GTfile_4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((25907, 17101, 6), (25907, 17101, 6), (25907, 17101, 6))"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img1.shape, img2.shape, img4.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "visRGB(img1[:,:,0], img1[:,:,4], img1[:,:,1],\n",
    "           title = 'RGB image',\n",
    "           scale1 = [0,10000],\n",
    "           scale2 = [0,20000],\n",
    "           scale3 = [0,10000],\n",
    "           flag = 0, outall = '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "visRGB(img2[:,:,0], img2[:,:,4], img2[:,:,1],\n",
    "           title = 'RGB image',\n",
    "           scale1 = [0,10000],\n",
    "           scale2 = [0,20000],\n",
    "           scale3 = [0,10000],\n",
    "           flag = 0, outall = '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "visRGB(img4[:,:,0], img4[:,:,4], img4[:,:,1],\n",
    "           title = 'RGB image',\n",
    "           scale1 = [0,30000],\n",
    "           scale2 = [0,50000],\n",
    "           scale3 = [0,20000],\n",
    "           flag = 0, outall = '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-25 12:52:00.888709: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE4.1 SSE4.2 AVX AVX2 AVX512F AVX512_VNNI FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /tmp/ipykernel_570687/1332832982.py:2: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.config.list_physical_devices('GPU')` instead.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-25 12:52:04.754323: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE4.1 SSE4.2 AVX AVX2 AVX512F AVX512_VNNI FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tensorflow\n",
    "tensorflow.test.is_gpu_available()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "img3.shape, gt3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/space/vak/Weedwatch/Patancheru/Drone/Images'"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "np.savez('myfileforML_WH.npz', X=X, y=y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "GTdirectory='/space/vak/Weedwatch/Patancheru/Drone/GT/Anoop Labels/Rasterized/'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(GTdirectory)\n",
    "os.getcwd()\n",
    "data =load('myfileforML_WH.npz')\n",
    "\n",
    "X=data['X']\n",
    "y=data['y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((40385, 5), (40385,))"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape, y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "y[y > 3] = 0\n",
    "y[y == 1] = 0\n",
    "y[y == 3] = 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import AdaBoostClassifier, RandomForestClassifier, GradientBoostingClassifier, ExtraTreesClassifier\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.naive_bayes import GaussianNB, MultinomialNB, BernoulliNB\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn import svm\n",
    "from sklearn.linear_model import LogisticRegression, SGDClassifier\n",
    "from sklearn.model_selection import KFold, train_test_split\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.metrics import confusion_matrix, accuracy_score\n",
    "from sklearn.utils.multiclass import unique_labels\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import KFold\n",
    "\n",
    "# Split the data into a training set and a test set\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y,test_size=0.25, random_state=0)\n",
    "\n",
    "\n",
    "classifier='SGD'\n",
    "if classifier=='RF':\n",
    "    model = RandomForestClassifier(n_estimators=500, max_depth=20,oob_score=True)\n",
    "# Fit our model to training data\n",
    "elif classifier=='DT':\n",
    "    model = ExtraTreesClassifier(max_depth=6)\n",
    "elif classifier=='kNN':\n",
    "    model = KNeighborsClassifier(n_neighbors=8)\n",
    "elif classifier== 'LR':\n",
    "    model = LogisticRegression()\n",
    "elif classifier== 'SGD':\n",
    "    model = SGDClassifier()\n",
    "elif classifier=='GB':\n",
    "    model = GradientBoostingClassifier(n_estimators=1200)    \n",
    "elif classifier=='GNB':\n",
    "    model = GaussianNB()\n",
    "elif classifier== 'MNB':\n",
    "    model = MultinomialNB()\n",
    "\n",
    "elif classifier=='SVM':\n",
    "    model = svm.SVC(decision_function_shape = \"ovr\")# ovo\n",
    "elif classifier== 'MLP':\n",
    "    print('MLP')\n",
    "    model = MLPClassifier(hidden_layer_sizes=(150,100,50), max_iter=300,activation = 'relu',solver='adam',random_state=1)\n",
    "\n",
    " # Fit our model to training data\n",
    "model = model.fit(X_train, y_train) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our OOB prediction of accuracy is: 95.48335974643423%\n"
     ]
    }
   ],
   "source": [
    "print('Our OOB prediction of accuracy is: {oob}%'.format(oob=model.oob_score_ * 100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'MLPClassifier' object has no attribute 'feature_importances_'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[12], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m bands \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m4\u001b[39m, \u001b[38;5;241m5\u001b[39m,]\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m b, imp \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(bands, \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfeature_importances_\u001b[49m):\n\u001b[1;32m      4\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBand \u001b[39m\u001b[38;5;132;01m{b}\u001b[39;00m\u001b[38;5;124m importance: \u001b[39m\u001b[38;5;132;01m{imp}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(b\u001b[38;5;241m=\u001b[39mb, imp\u001b[38;5;241m=\u001b[39mimp))\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'MLPClassifier' object has no attribute 'feature_importances_'"
     ]
    }
   ],
   "source": [
    "bands = [1, 2, 3, 4, 5,]\n",
    "\n",
    "for b, imp in zip(bands, model.feature_importances_):\n",
    "    print('Band {b} importance: {imp}'.format(b=b, imp=imp))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the plotting function\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def plot_confusion_matrix(cm, classes,\n",
    "                          normalize=False,\n",
    "                          title='Confusion matrix',\n",
    "                          cmap=plt.cm.Blues, ylabel='True label', xlabel='Predicted label', filename=None):\n",
    "    \"\"\"\n",
    "    This function prints and plots the confusion matrix.\n",
    "    Normalization can be applied by setting `normalize=True`.\n",
    "    \"\"\"\n",
    "    np.set_printoptions(precision=2, suppress=True)\n",
    "\n",
    "    if normalize:\n",
    "        cm = cm.astype('float') / (cm.sum(axis=1)\n",
    "                                   [:, np.newaxis] + np.finfo(np.float).eps)\n",
    "\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap, vmin=0, vmax=1)\n",
    "    plt.title(title, fontsize=20)\n",
    "    # plt.colorbar()\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45, fontsize=20)\n",
    "    plt.yticks(tick_marks, classes, fontsize=20)\n",
    "\n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max() / 2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, format(cm[i, j], fmt),\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\",\n",
    "                 fontsize=12)\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.ylabel(ylabel, fontsize=20)\n",
    "    plt.xlabel(xlabel, fontsize=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predict     0     2    All\n",
      "truth                     \n",
      "0        5851  1245   7096\n",
      "2         665  2336   3001\n",
      "All      6516  3581  10097\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Setup a dataframe -- just like R\n",
    "df = pd.DataFrame()\n",
    "df['truth'] = y_test\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "df['predict'] = y_pred\n",
    "\n",
    "# Cross-tabulate predictions\n",
    "print(pd.crosstab(df['truth'], df['predict'], margins=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predict     1     2     3     4     5     6     7    All\n",
      "truth                                                   \n",
      "1        1432     3     0    36     9     3     1   1484\n",
      "2          15  1656    96    39     9     0   116   1931\n",
      "3           0    86   973     1     0     0    10   1070\n",
      "4          58    85    10  1396    23    17   164   1753\n",
      "5          11     4     0    21   839   273    30   1178\n",
      "6           4     1     0    18   178   957    23   1181\n",
      "7           0   156    22   108    24    32  1158   1500\n",
      "All      1520  1991  1101  1619  1082  1282  1502  10097\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Setup a dataframe -- just like R\n",
    "df = pd.DataFrame()\n",
    "df['truth'] = y_test\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "df['predict'] = y_pred\n",
    "\n",
    "# Cross-tabulate predictions\n",
    "print(pd.crosstab(df['truth'], df['predict'], margins=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 6, 4, ..., 6, 2, 5], dtype=uint8)"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Misc\n",
    "import pickle\n",
    "import sys\n",
    "import os\n",
    "import datetime\n",
    "import itertools\n",
    "# from tqdm import tqdm_notebook as tqdm\n",
    "import enum\n",
    "import matplotlib as mpl\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "class LULC(enum.Enum):\n",
    "    NO_DATA = (0,  'Others',           'white')\n",
    "    W=    (1,  'W',         'xkcd:Blue')\n",
    "    WH1 = (2,  'WH',         'xkcd:Green')\n",
    "    WH2 = (3,  'WH2',  'xkcd:Lime')\n",
    "    OV =  (4,  'OV',           'xkcd:Blue')\n",
    "    B = (5,  'B',        'xkcd:Blue')\n",
    "    S= (6,  'S',        'xkcd:Blue')\n",
    "    TV = (7,  'TV',        'xkcd:Blue')\n",
    "    def __init__(self, val1, val2, val3):\n",
    "        self.id = val1\n",
    "        self.class_name = val2\n",
    "        self.color = val3\n",
    "\n",
    "\n",
    "# example usecase\n",
    "# LULC.BARELAND.id   # return 9\n",
    "# Reference colormap things\n",
    "lulc_cmap = mpl.colors.ListedColormap([entry.color for entry in LULC])\n",
    "lulc_norm = mpl.colors.BoundaryNorm(np.arange(-0.5, 8, 1), lulc_cmap.N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "class_labels = np.unique(y_test)\n",
    "class_names = [entry.class_name for entry in LULC]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_570935/3900164669.py:17: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
      "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
      "  [:, np.newaxis] + np.finfo(np.float).eps)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "class_labels = np.unique(y_test)\n",
    "class_names = [entry.class_name for entry in LULC]\n",
    "fig = plt.figure(figsize=(9, 9), dpi=100)\n",
    "\n",
    "conf_matrix_gbm = metrics.confusion_matrix(np.float64(y_test), np.float64(y_pred))\n",
    "plot_confusion_matrix(conf_matrix_gbm,\n",
    "                      classes=[name for idx, name in enumerate(\n",
    "                          class_names) if idx in class_labels],\n",
    "                      normalize=True,\n",
    "                      ylabel='Truth (LAND COVER)',\n",
    "                      xlabel='Predicted (SGD) ',\n",
    "                      title=' Confusion matrix')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_275399/3900164669.py:17: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
      "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
      "  [:, np.newaxis] + np.finfo(np.float).eps)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "class_labels = np.unique(y_test)\n",
    "class_names = [entry.class_name for entry in LULC]\n",
    "fig = plt.figure(figsize=(9, 9), dpi=100)\n",
    "\n",
    "conf_matrix_gbm = metrics.confusion_matrix(y_test, y_pred)\n",
    "plot_confusion_matrix(conf_matrix_gbm,\n",
    "                      classes=[name for idx, name in enumerate(\n",
    "                          class_names) if idx in class_labels],\n",
    "                      normalize=True,\n",
    "                      ylabel='Truth (LAND COVER)',\n",
    "                      xlabel='Predicted (RF) ',\n",
    "                      title=' Confusion matrix')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.94      0.96      0.95      1484\n",
      "           2       0.83      0.86      0.84      1931\n",
      "           3       0.88      0.91      0.90      1070\n",
      "           4       0.86      0.80      0.83      1753\n",
      "           5       0.77      0.71      0.74      1178\n",
      "           6       0.75      0.81      0.78      1181\n",
      "           7       0.77      0.77      0.77      1500\n",
      "\n",
      "    accuracy                           0.83     10097\n",
      "   macro avg       0.83      0.83      0.83     10097\n",
      "weighted avg       0.83      0.83      0.83     10097\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.96      0.97      7096\n",
      "           2       0.92      0.93      0.92      3001\n",
      "\n",
      "    accuracy                           0.95     10097\n",
      "   macro avg       0.94      0.95      0.95     10097\n",
      "weighted avg       0.95      0.95      0.95     10097\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kappa coeff. 0.804\n",
      "Classification accuracy 83.3%\n",
      "Classification F1-score 83.2%\n",
      "             Class              =  F1  | Recall | Precision | IoU\n",
      "         --------------------------------------------------------\n",
      "         * W                    = 95.3 |  96.5  | 94.2    | 91.1\n",
      "         * WH1                  = 84.4 |  85.8  | 83.2    | 73.1\n",
      "         * WH2                  = 89.6 |  90.9  | 88.4    | 81.2\n",
      "         * OV                   = 82.8 |  79.6  | 86.2    | 70.6\n",
      "         * B                    = 74.2 |  71.2  | 77.5    | 59.0\n",
      "         * S                    = 77.7 |  81.0  | 74.6    | 63.5\n",
      "         * TV                   = 77.1 |  77.2  | 77.1    | 62.8\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import cohen_kappa_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import numpy as np\n",
    "\n",
    "# calculate confusion matrix\n",
    "conf_mat = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "iou_scores = []\n",
    "for i in range(len(class_labels)):\n",
    "    true_pos = conf_mat[i, i]\n",
    "    false_pos = np.sum(conf_mat[:, i]) - true_pos\n",
    "    false_neg = np.sum(conf_mat[i, :]) - true_pos\n",
    "    iou = true_pos / (true_pos + false_pos + false_neg)\n",
    "    iou_scores.append(iou)\n",
    "\n",
    "print('Kappa coeff. {:.3f}'.format(cohen_kappa_score(y_pred, y_test)))\n",
    "print('Classification accuracy {:.1f}%'.format(100 * metrics.accuracy_score(y_test, y_pred)))\n",
    "print('Classification F1-score {:.1f}%'.format(100 * metrics.f1_score(y_test, y_pred, average='weighted')))\n",
    "f1_scores = metrics.f1_score(y_test, y_pred, labels=class_labels, average=None)\n",
    "recall = metrics.recall_score(y_test, y_pred, labels=class_labels, average=None)\n",
    "precision = metrics.precision_score(y_test, y_pred, labels=class_labels, average=None)\n",
    "\n",
    "print('             Class              =  F1  | Recall | Precision | IoU')\n",
    "print('         --------------------------------------------------------')\n",
    "for idx, lulctype in enumerate([class_names[idx] for idx in class_labels]):\n",
    "    print('         * {0:20s} = {1:2.1f} |  {2:2.1f}  | {3:2.1f}    | {4:2.1f}'.format(lulctype,\n",
    "                                                                         f1_scores[idx] * 100,\n",
    "                                                                         recall[idx] * 100,\n",
    "                                                                         precision[idx] * 100,\n",
    "                                                                         iou_scores[idx] * 100))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kappa coeff. 0.740\n",
      "Classification accuracy 88.2%\n",
      "Classification F1-score 88.6%\n",
      "             Class              =  F1  | Recall | Precision | IoU\n",
      "         --------------------------------------------------------\n",
      "         * Others               = 91.0 |  85.2  | 97.8    | 83.5\n",
      "         * WH                   = 82.8 |  95.4  | 73.1    | 70.6\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import cohen_kappa_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import numpy as np\n",
    "\n",
    "# calculate confusion matrix\n",
    "conf_mat = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "iou_scores = []\n",
    "for i in range(len(class_labels)):\n",
    "    true_pos = conf_mat[i, i]\n",
    "    false_pos = np.sum(conf_mat[:, i]) - true_pos\n",
    "    false_neg = np.sum(conf_mat[i, :]) - true_pos\n",
    "    iou = true_pos / (true_pos + false_pos + false_neg)\n",
    "    iou_scores.append(iou)\n",
    "\n",
    "print('Kappa coeff. {:.3f}'.format(cohen_kappa_score(y_pred, y_test)))\n",
    "print('Classification accuracy {:.1f}%'.format(100 * metrics.accuracy_score(y_test, y_pred)))\n",
    "print('Classification F1-score {:.1f}%'.format(100 * metrics.f1_score(y_test, y_pred, average='weighted')))\n",
    "f1_scores = metrics.f1_score(y_test, y_pred, labels=class_labels, average=None)\n",
    "recall = metrics.recall_score(y_test, y_pred, labels=class_labels, average=None)\n",
    "precision = metrics.precision_score(y_test, y_pred, labels=class_labels, average=None)\n",
    "\n",
    "print('             Class              =  F1  | Recall | Precision | IoU')\n",
    "print('         --------------------------------------------------------')\n",
    "for idx, lulctype in enumerate([class_names[idx] for idx in class_labels]):\n",
    "    print('         * {0:20s} = {1:2.1f} |  {2:2.1f}  | {3:2.1f}    | {4:2.1f}'.format(lulctype,\n",
    "                                                                         f1_scores[idx] * 100,\n",
    "                                                                         recall[idx] * 100,\n",
    "                                                                         precision[idx] * 100,\n",
    "                                                                         iou_scores[idx] * 100))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns; sns.set()\n",
    "\n",
    "\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "mat = confusion_matrix(y_test, y_pred)\n",
    "sns.heatmap(mat.T, square=True, annot=True, fmt='d', cbar=False)\n",
    "plt.xlabel('true label')\n",
    "plt.ylabel('predicted label');\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns; sns.set()\n",
    "\n",
    "\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "mat = confusion_matrix(y_test, y_pred)\n",
    "sns.heatmap(mat.T, square=True, annot=True, fmt='d', cbar=False)\n",
    "plt.xlabel('true label')\n",
    "plt.ylabel('predicted label');\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SVM Support Vector Machine Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import svm\n",
    "clf = svm.SVC(decision_function_shape = \"ovr\")# ovo\n",
    "model=clf.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predict     1     2     3     4    5     6     7    All\n",
      "truth                                                  \n",
      "1        1438     3     0    32    6     4     1   1484\n",
      "2          16  1606   134    56   29     0    90   1931\n",
      "3           0    59  1009     0    0     0     2   1070\n",
      "4         158   121    17  1205   19    10   223   1753\n",
      "5          35    11     0    49  702   350    31   1178\n",
      "6           6     2     0    19  124  1010    20   1181\n",
      "7           2   304    54   106   14    34   986   1500\n",
      "All      1655  2106  1214  1467  894  1408  1353  10097\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Setup a dataframe -- just like R\n",
    "df = pd.DataFrame()\n",
    "df['truth'] = y_test\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "df['predict'] = y_pred\n",
    "\n",
    "# Cross-tabulate predictions\n",
    "print(pd.crosstab(df['truth'], df['predict'], margins=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_275399/3900164669.py:17: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
      "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
      "  [:, np.newaxis] + np.finfo(np.float).eps)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "from sklearn import metrics\n",
    "class_labels = np.unique(y_test)\n",
    "class_names = [entry.class_name for entry in LULC]\n",
    "fig = plt.figure(figsize=(9, 9), dpi=100)\n",
    "\n",
    "conf_matrix_gbm = metrics.confusion_matrix(y_test, y_pred)\n",
    "plot_confusion_matrix(conf_matrix_gbm,\n",
    "                      classes=[name for idx, name in enumerate(\n",
    "                          class_names) if idx in class_labels],\n",
    "                      normalize=True,\n",
    "                      ylabel='Truth (LAND COVER)',\n",
    "                      xlabel='Predicted (SVM) ',\n",
    "                      title=' Confusion matrix')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kappa coeff. 0.751\n",
      "Classification accuracy 78.8%\n",
      "Classification F1-score 78.3%\n",
      "             Class              =  F1  | Recall | Precision | IoU\n",
      "         --------------------------------------------------------\n",
      "         * W                    = 91.6 |  96.9  | 86.9    | 84.5\n",
      "         * WH1                  = 79.6 |  83.2  | 76.3    | 66.1\n",
      "         * WH2                  = 88.4 |  94.3  | 83.1    | 79.1\n",
      "         * OV                   = 74.8 |  68.7  | 82.1    | 59.8\n",
      "         * B                    = 67.8 |  59.6  | 78.5    | 51.2\n",
      "         * S                    = 78.0 |  85.5  | 71.7    | 64.0\n",
      "         * TV                   = 69.1 |  65.7  | 72.9    | 52.8\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import cohen_kappa_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import numpy as np\n",
    "\n",
    "# calculate confusion matrix\n",
    "conf_mat = confusion_matrix(y_test, ysvcpred)\n",
    "\n",
    "iou_scores = []\n",
    "for i in range(len(class_labels)):\n",
    "    true_pos = conf_mat[i, i]\n",
    "    false_pos = np.sum(conf_mat[:, i]) - true_pos\n",
    "    false_neg = np.sum(conf_mat[i, :]) - true_pos\n",
    "    iou = true_pos / (true_pos + false_pos + false_neg)\n",
    "    iou_scores.append(iou)\n",
    "\n",
    "print('Kappa coeff. {:.3f}'.format(cohen_kappa_score(ysvcpred, y_test)))\n",
    "print('Classification accuracy {:.1f}%'.format(100 * metrics.accuracy_score(y_test, ysvcpred)))\n",
    "print('Classification F1-score {:.1f}%'.format(100 * metrics.f1_score(y_test, ysvcpred, average='weighted')))\n",
    "f1_scores = metrics.f1_score(y_test, ysvcpred, labels=class_labels, average=None)\n",
    "recall = metrics.recall_score(y_test, ysvcpred, labels=class_labels, average=None)\n",
    "precision = metrics.precision_score(y_test, ysvcpred, labels=class_labels, average=None)\n",
    "\n",
    "print('             Class              =  F1  | Recall | Precision | IoU')\n",
    "print('         --------------------------------------------------------')\n",
    "for idx, lulctype in enumerate([class_names[idx] for idx in class_labels]):\n",
    "    print('         * {0:20s} = {1:2.1f} |  {2:2.1f}  | {3:2.1f}    | {4:2.1f}'.format(lulctype,\n",
    "                                                                         f1_scores[idx] * 100,\n",
    "                                                                         recall[idx] * 100,\n",
    "                                                                         precision[idx] * 100,\n",
    "                                                                         iou_scores[idx] * 100))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train  0.6060486001056524\n",
      "test:  0.5929484005150044\n"
     ]
    }
   ],
   "source": [
    "mlp_model = MLPClassifier(activation='tanh', alpha = 0.01, hidden_layer_sizes = 5, solver = 'adam')\n",
    "mlp = mlp_model.fit(X_train, y_train)\n",
    "print(\"train \",mlp.score(X_train,y_train))\n",
    "\n",
    "print(\"test: \",mlp.score(X_test,y_test))\n",
    "y_mlppred = clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 7 artists>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AAAAAChCqAAAAAAAAFCBUAQAAAAAAKECoAgAAAAAAUMD/B+yrs0w9UjoqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20, 5))\n",
    "\n",
    "label_ids, label_counts = np.unique(y_train, return_counts=True)\n",
    "\n",
    "plt.bar(range(len(label_ids)), label_counts)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "class LULC(enum.Enum):\n",
    "    NO_DATA = (0,  'No data',           'white')\n",
    "    W=    (1,  'W',         'blue')\n",
    "    WH1 = (2,  'WH1',         'Green')\n",
    "    WH2 = (3,  'WH2',  'Black')\n",
    "    OV =  (4,  'OV',           'yellow')\n",
    "    B = (5,  'B',        'Red')\n",
    "    S= (6,  'S',        'Brown')\n",
    "    TV = (7,  'TV',        'Pink')\n",
    "    def __init__(self, val1, val2, val3):\n",
    "        self.id = val1\n",
    "        self.class_name = val2\n",
    "        self.color = val3\n",
    "\n",
    "\n",
    "# example usecase\n",
    "# LULC.BARELAND.id   # return 9\n",
    "# Reference colormap things\n",
    "lulc_cmap = mpl.colors.ListedColormap([entry.color for entry in LULC])\n",
    "lulc_norm = mpl.colors.BoundaryNorm(np.arange(-0.5, 8, 1), lulc_cmap.N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "index 1 is out of bounds for axis 1 with size 1",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[28], line 12\u001b[0m\n\u001b[1;32m      8\u001b[0m roc_auc \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m()\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m idx, lbl \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(class_labels):\n\u001b[1;32m     11\u001b[0m     fpr[idx], tpr[idx], _ \u001b[38;5;241m=\u001b[39m metrics\u001b[38;5;241m.\u001b[39mroc_curve(\n\u001b[0;32m---> 12\u001b[0m         \u001b[43mlabels_binarized\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[43m]\u001b[49m, scores_test[:, idx])\n\u001b[1;32m     13\u001b[0m     roc_auc[idx] \u001b[38;5;241m=\u001b[39m metrics\u001b[38;5;241m.\u001b[39mauc(fpr[idx], tpr[idx])\n",
      "\u001b[0;31mIndexError\u001b[0m: index 1 is out of bounds for axis 1 with size 1"
     ]
    }
   ],
   "source": [
    "class_labels = np.unique(np.hstack([y_test, y_train]))\n",
    "\n",
    "scores_test = model.predict_proba(X_test)\n",
    "labels_binarized = preprocessing.label_binarize(y_test, classes=class_labels)\n",
    "\n",
    "fpr = dict()\n",
    "tpr = dict()\n",
    "roc_auc = dict()\n",
    "\n",
    "for idx, lbl in enumerate(class_labels):\n",
    "    fpr[idx], tpr[idx], _ = metrics.roc_curve(\n",
    "        labels_binarized[:, idx], scores_test[:, idx])\n",
    "    roc_auc[idx] = metrics.auc(fpr[idx], tpr[idx])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "\n",
    "for idx, lbl in enumerate(class_labels):\n",
    "    if np.isnan(roc_auc[idx]):\n",
    "        continue\n",
    "    plt.plot(fpr[idx], tpr[idx], color=lulc_cmap.colors[lbl],\n",
    "             lw=2, label=class_names[lbl] + ' (%0.5f)' % roc_auc[idx])\n",
    "\n",
    "\n",
    "plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
    "plt.xlim([0.0, 0.99])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('False Positive Rate', fontsize=20)\n",
    "plt.ylabel('True Positive Rate', fontsize=20)\n",
    "plt.xticks(fontsize=20)\n",
    "plt.yticks(fontsize=20)\n",
    "plt.title('ROC Curve', fontsize=20)\n",
    "plt.legend(loc=\"center right\", prop={'size': 15})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "datadirectory='/space/vak/Weedwatch/Patancheru/Drone/Images/'\n",
    "imagefile_1 = 'Orthomosaic_26Mar2021_PatanCheru_AOI_10cm.tif'\n",
    "(img1, crs, geoTransform) = read_band_image(datadirectory,imagefile_1)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reshaped from (12954, 8550, 5) to (110756700, 5)\n"
     ]
    }
   ],
   "source": [
    "# Take our full image,  and reshape into long 2d array (nrow * ncol, nband) for classification\n",
    "img5 = img1[:,:, :5]\n",
    "new_shape = (img5.shape[0] * img5.shape[1], img5.shape[2])\n",
    "\n",
    "img_as_array = img5.reshape(new_shape)\n",
    "print('Reshaped from {o} to {n}'.format(o=img5.shape,\n",
    "                                        n=img_as_array.shape))\n",
    "\n",
    "# Now predict for each pixel\n",
    "class_prediction = model.predict(img_as_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reshape our classification map\n",
    "class_prediction = class_prediction.reshape(img5[:, :, 0].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [],
   "source": [
    "#class_prediction = class_prediction * mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Classification')"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x2500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize\n",
    "# Now show the classmap next to the image\n",
    "f = plt.figure(figsize=(20,25))\n",
    "ax1 = f.add_subplot(111)\n",
    "\n",
    "\n",
    "\n",
    "ax1.imshow(class_prediction,cmap=cmap)\n",
    "ax1.set_title('Classification')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR 1: PROJ: proj_create_from_name: /home/vak/anaconda3/envs/myenv/share/proj/proj.db lacks DATABASE.LAYOUT.VERSION.MAJOR / DATABASE.LAYOUT.VERSION.MINOR metadata. It comes from another PROJ installation.\n"
     ]
    }
   ],
   "source": [
    "import rasterio\n",
    "with rasterio.open(\n",
    "        \"/space/vak/Weedwatch/Patancheru/Drone/CLSs/26Mar2021_cls.tif\",\n",
    "        mode=\"w\",\n",
    "        driver=\"GTiff\",\n",
    "        height=class_prediction.shape[0],\n",
    "        width=class_prediction.shape[1],\n",
    "        count=1,\n",
    "        dtype=class_prediction.dtype,\n",
    "        crs=crs,\n",
    "        transform=geoTransform,\n",
    ") as new_dataset:\n",
    "        new_dataset.write(class_prediction, 1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/space/vak/Weedwatch/Patancheru/Drone/Images'"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.15"
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  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
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   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
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