MNIST-MIX-LeNet-tf2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow import keras\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping\n",
    "from tensorflow.keras import backend as K\n",
    "from tensorflow.keras.layers import *\n",
    "from tensorflow.keras.models import Model\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "import numpy as np\n",
    "from sklearn import metrics\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# K.set_image_dim_ordering('tf')\n",
    "keras.backend.set_image_data_format('channels_last')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define weighted f1 and balanced accuarcy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate(predicted_outcome, expected_outcome):\n",
    "    from sklearn import metrics\n",
    "    f1_score = metrics.f1_score(expected_outcome, predicted_outcome, average='weighted')\n",
    "    balanced_accuracy_score = metrics.balanced_accuracy_score(expected_outcome, predicted_outcome)\n",
    "    return f1_score, balanced_accuracy_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read data and split validation set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_dataset_with_processing(input_train_test_fn, num_classes=10):\n",
    "    data = np.load(input_train_test_fn)\n",
    "    X_train, X_test, y_train, y_test = data['X_train'], data['X_test'], data['y_train'], data['y_test']\n",
    "    \n",
    "    # split validation set\n",
    "    from sklearn.model_selection import train_test_split\n",
    "    X_train, X_vali, y_train, y_vali = train_test_split(X_train, y_train, stratify=y_train, test_size=0.2)\n",
    "    \n",
    "    X_train = np.array(X_train, dtype=\"float\") / 255.0\n",
    "    X_train = X_train.reshape(X_train.shape[0], 28, 28,1 )\n",
    "    print(X_train.shape)\n",
    "    \n",
    "    X_vali = np.array(X_vali, dtype=\"float\") / 255.0\n",
    "    X_vali = X_vali.reshape(X_vali.shape[0], 28, 28,1 )\n",
    "    print(X_vali.shape)\n",
    "    \n",
    "    X_test = np.array(X_test, dtype=\"float\") / 255.0\n",
    "    X_test = X_test.reshape(X_test.shape[0], 28, 28,1 )\n",
    "    print(X_test.shape)\n",
    "    \n",
    "    y_train = keras.utils.to_categorical(y_train, num_classes)\n",
    "    y_vali = keras.utils.to_categorical(y_vali, num_classes)\n",
    "    y_test = keras.utils.to_categorical(y_test, num_classes)\n",
    "    \n",
    "    return X_train, y_train, X_vali, y_vali, X_test, y_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Build a data generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def myGenerator(X_train, y_train, batch_size):    \n",
    "    total_size = X_train.shape[0]\n",
    "    \n",
    "    while True:\n",
    "        permutation = list(np.random.permutation(total_size))\n",
    "        for i in range(total_size//batch_size):\n",
    "            index = permutation[i * batch_size : (i + 1) * batch_size]\n",
    "            X_batch = X_train[index]\n",
    "            y_batch = y_train[index]\n",
    "                    \n",
    "            yield X_batch, y_batch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Build the lenet model with pretrained weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_input (InputLayer)    [(None, 28, 28, 1)]       0         \n",
      "_________________________________________________________________\n",
      "conv2d (Conv2D)              (None, 28, 28, 20)        520       \n",
      "_________________________________________________________________\n",
      "activation (Activation)      (None, 28, 28, 20)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D) (None, 14, 14, 20)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_1 (Conv2D)            (None, 14, 14, 50)        25050     \n",
      "_________________________________________________________________\n",
      "activation_1 (Activation)    (None, 14, 14, 50)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 7, 7, 50)          0         \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 2450)              0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 500)               1225500   \n",
      "_________________________________________________________________\n",
      "activation_2 (Activation)    (None, 500)               0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 10)                5010      \n",
      "=================================================================\n",
      "Total params: 1,256,080\n",
      "Trainable params: 5,010\n",
      "Non-trainable params: 1,251,070\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "def build_model(input_shape, num_classes):\n",
    "    # initialize the model\n",
    "    model = Sequential()\n",
    "    model.add(Conv2D(20, (5, 5), padding=\"same\", input_shape=input_shape))\n",
    "    model.add(Activation(\"relu\"))\n",
    "    model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))\n",
    "    # second set of CONV => RELU => POOL layers\n",
    "    model.add(Conv2D(50, (5, 5), padding=\"same\"))\n",
    "    model.add(Activation(\"relu\"))\n",
    "    model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))\n",
    "    # first (and only) set of FC => RELU layers\n",
    "    model.add(Flatten())\n",
    "    model.add(Dense(500))\n",
    "    model.add(Activation(\"relu\"))\n",
    "    \n",
    "    for layer in model.layers:\n",
    "        layer.trainable = False  # freeze the previous layers\n",
    "    \n",
    "    X = model.output\n",
    "    # softmax classifier\n",
    "    predictions = Dense(10, activation='softmax')(X)\n",
    "    old_model = Model(inputs=model.input, outputs=predictions)\n",
    "    \n",
    "    # load weights\n",
    "    old_model.load_weights('./pretrained_mnist/lenet.hdf5')\n",
    "\n",
    "    X = model.output\n",
    "    # softmax classifier\n",
    "    predictions = Dense(num_classes, activation='softmax')(X)\n",
    "    new_model = Model(inputs=model.input, outputs=predictions)\n",
    "\n",
    "    new_model.summary()\n",
    "    \n",
    "    return new_model\n",
    "    \n",
    "input_shape = (28, 28, 1)\n",
    "num_classes = 10\n",
    "model = build_model(input_shape, num_classes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the training function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_fn(X_train, y_train, X_vali, y_vali, input_shape, num_classes, loss, optimizer, metrics, checkpoint_dir, batch_size, epochs):\n",
    "    import os\n",
    "    if os.path.exists(checkpoint_dir) is False:\n",
    "        os.makedirs(checkpoint_dir)\n",
    "\n",
    "    model = build_model(input_shape, num_classes)\n",
    "    \n",
    "    checkpoint = ModelCheckpoint(checkpoint_dir + 'best.hdf5', monitor='val_accuracy', verbose=1, save_best_only=True, mode='auto')\n",
    "    es = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=30)\n",
    "\n",
    "    \n",
    "    #Compile Keras Model \n",
    "    model.compile(loss=loss,\n",
    "                  optimizer=optimizer,\n",
    "                  metrics=metrics)\n",
    "    \n",
    "    datagen = myGenerator(X_train, y_train, batch_size)\n",
    "    \n",
    "    history = model.fit_generator(datagen,\n",
    "                        steps_per_epoch = len(X_train) // batch_size,\n",
    "                        epochs=epochs,\n",
    "                        callbacks=[es, checkpoint],\n",
    "                        verbose=2,\n",
    "                        validation_data=(X_vali, y_vali))\n",
    "    \n",
    "    plt.plot(history.history['loss'], label='train')\n",
    "    plt.plot(history.history['val_loss'], label='validation')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    \n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the testing function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_fn(X_test, y_test, input_shape, num_classes, loss, optimizer, metrics, pretrained_weights):\n",
    "    model = build_model(input_shape, num_classes)\n",
    "\n",
    "    # Compile Keras Model \n",
    "    model.compile(loss=loss,\n",
    "                  optimizer=optimizer,\n",
    "                  metrics=metrics)\n",
    "    \n",
    "    # load weights\n",
    "    model.load_weights(pretrained_weights)\n",
    "    \n",
    "    score = model.evaluate(X_test, y_test, verbose=0)\n",
    "    \n",
    "    testPredict = model.predict(X_test)\n",
    "    y_test_tmp = np.argmax(y_test, axis=1)\n",
    "    y_pred_tmp = np.argmax(testPredict, axis=1)\n",
    "    f1_score, balanced_accuracy_score = evaluate(y_pred_tmp, y_test_tmp)\n",
    "    \n",
    "    return score[1], f1_score, balanced_accuracy_score  # return accuracies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we train the LeNet model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(395688, 28, 28, 1)\n",
      "(98922, 28, 28, 1)\n",
      "(107158, 28, 28, 1)\n",
      "Model: \"model_7\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_6_input (InputLayer)  [(None, 28, 28, 1)]       0         \n",
      "_________________________________________________________________\n",
      "conv2d_6 (Conv2D)            (None, 28, 28, 20)        520       \n",
      "_________________________________________________________________\n",
      "activation_9 (Activation)    (None, 28, 28, 20)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_6 (MaxPooling2 (None, 14, 14, 20)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_7 (Conv2D)            (None, 14, 14, 50)        25050     \n",
      "_________________________________________________________________\n",
      "activation_10 (Activation)   (None, 14, 14, 50)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_7 (MaxPooling2 (None, 7, 7, 50)          0         \n",
      "_________________________________________________________________\n",
      "flatten_3 (Flatten)          (None, 2450)              0         \n",
      "_________________________________________________________________\n",
      "dense_9 (Dense)              (None, 500)               1225500   \n",
      "_________________________________________________________________\n",
      "activation_11 (Activation)   (None, 500)               0         \n",
      "_________________________________________________________________\n",
      "dense_11 (Dense)             (None, 100)               50100     \n",
      "=================================================================\n",
      "Total params: 1,301,170\n",
      "Trainable params: 50,100\n",
      "Non-trainable params: 1,251,070\n",
      "_________________________________________________________________\n",
      "Epoch 1/10\n",
      "\n",
      "Epoch 00001: val_accuracy improved from -inf to 0.93791, saving model to ./LeNet_MNIST_MIX/best.hdf5\n",
      "3091/3091 - 15s - loss: 0.9364 - accuracy: 0.9198 - val_loss: 0.8729 - val_accuracy: 0.9379\n",
      "Epoch 2/10\n",
      "\n",
      "Epoch 00002: val_accuracy improved from 0.93791 to 0.94503, saving model to ./LeNet_MNIST_MIX/best.hdf5\n",
      "3091/3091 - 15s - loss: 0.8386 - accuracy: 0.9445 - val_loss: 0.9241 - val_accuracy: 0.9450\n",
      "Epoch 3/10\n",
      "\n",
      "Epoch 00003: val_accuracy improved from 0.94503 to 0.94638, saving model to ./LeNet_MNIST_MIX/best.hdf5\n",
      "3091/3091 - 14s - loss: 0.7979 - accuracy: 0.9511 - val_loss: 0.9890 - val_accuracy: 0.9464\n",
      "Epoch 4/10\n",
      "\n",
      "Epoch 00004: val_accuracy improved from 0.94638 to 0.94751, saving model to ./LeNet_MNIST_MIX/best.hdf5\n",
      "3091/3091 - 15s - loss: 0.7687 - accuracy: 0.9546 - val_loss: 1.0551 - val_accuracy: 0.9475\n",
      "Epoch 5/10\n",
      "\n",
      "Epoch 00005: val_accuracy improved from 0.94751 to 0.95269, saving model to ./LeNet_MNIST_MIX/best.hdf5\n",
      "3091/3091 - 15s - loss: 0.7382 - accuracy: 0.9574 - val_loss: 1.0392 - val_accuracy: 0.9527\n",
      "Epoch 6/10\n",
      "\n",
      "Epoch 00006: val_accuracy did not improve from 0.95269\n",
      "3091/3091 - 14s - loss: 0.7325 - accuracy: 0.9591 - val_loss: 1.1425 - val_accuracy: 0.9479\n",
      "Epoch 7/10\n",
      "\n",
      "Epoch 00007: val_accuracy did not improve from 0.95269\n",
      "3091/3091 - 14s - loss: 0.7167 - accuracy: 0.9609 - val_loss: 1.1191 - val_accuracy: 0.9520\n",
      "Epoch 8/10\n",
      "\n",
      "Epoch 00008: val_accuracy improved from 0.95269 to 0.95349, saving model to ./LeNet_MNIST_MIX/best.hdf5\n",
      "3091/3091 - 15s - loss: 0.6973 - accuracy: 0.9617 - val_loss: 1.1080 - val_accuracy: 0.9535\n",
      "Epoch 9/10\n",
      "\n",
      "Epoch 00009: val_accuracy did not improve from 0.95349\n",
      "3091/3091 - 15s - loss: 0.6924 - accuracy: 0.9631 - val_loss: 1.1752 - val_accuracy: 0.9526\n",
      "Epoch 10/10\n",
      "\n",
      "Epoch 00010: val_accuracy did not improve from 0.95349\n",
      "3091/3091 - 15s - loss: 0.6815 - accuracy: 0.9640 - val_loss: 1.1635 - val_accuracy: 0.9532\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.engine.training.Model at 0x182ae5c98d0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_rows, img_cols = 28 , 28\n",
    "input_shape = (img_rows, img_cols, 1)\n",
    "num_classes = 100\n",
    "loss = 'categorical_crossentropy'\n",
    "optimizer = Adam(lr=0.01, clipnorm=0.001)\n",
    "metrics = ['accuracy']\n",
    "batch_size = 128\n",
    "epochs = 10\n",
    "\n",
    "checkpoint_dir = './LeNet_MNIST_MIX/'\n",
    "input_train_test_fn = './data/MNIST_MIX_train_test.npz'\n",
    "\n",
    "# load data\n",
    "X_train, y_train, X_vali, y_vali, X_test, y_test = load_dataset_with_processing(input_train_test_fn, num_classes=100)\n",
    "\n",
    "train_fn(X_train, y_train, X_vali, y_vali, input_shape, num_classes, loss, optimizer, metrics, checkpoint_dir, batch_size, epochs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we test the saved model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_9\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_8_input (InputLayer)  [(None, 28, 28, 1)]       0         \n",
      "_________________________________________________________________\n",
      "conv2d_8 (Conv2D)            (None, 28, 28, 20)        520       \n",
      "_________________________________________________________________\n",
      "activation_12 (Activation)   (None, 28, 28, 20)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_8 (MaxPooling2 (None, 14, 14, 20)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_9 (Conv2D)            (None, 14, 14, 50)        25050     \n",
      "_________________________________________________________________\n",
      "activation_13 (Activation)   (None, 14, 14, 50)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_9 (MaxPooling2 (None, 7, 7, 50)          0         \n",
      "_________________________________________________________________\n",
      "flatten_4 (Flatten)          (None, 2450)              0         \n",
      "_________________________________________________________________\n",
      "dense_12 (Dense)             (None, 500)               1225500   \n",
      "_________________________________________________________________\n",
      "activation_14 (Activation)   (None, 500)               0         \n",
      "_________________________________________________________________\n",
      "dense_14 (Dense)             (None, 100)               50100     \n",
      "=================================================================\n",
      "Total params: 1,301,170\n",
      "Trainable params: 50,100\n",
      "Non-trainable params: 1,251,070\n",
      "_________________________________________________________________\n",
      "Accuracy:  0.9034416675567627\n",
      "Weighted F1:  0.9021917662284732\n",
      "Balanced Accuracy:  0.8317692564647722\n"
     ]
    }
   ],
   "source": [
    "pretrained_weights = './LeNet_MNIST_MIX/best.hdf5'\n",
    "accuracies = test_fn(X_test, y_test, input_shape, num_classes, loss, optimizer, metrics, pretrained_weights)\n",
    "print('Accuracy: ', accuracies[0])\n",
    "print('Weighted F1: ', accuracies[1])\n",
    "print('Balanced Accuracy: ', accuracies[2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the confusion matrix for different languages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "languages = ['Arabic', 'Bangla', 'Devanagari', 'English', 'Farsi', 'Kannada', 'Swedish', 'Telugu', 'Tibetan', 'Urdu']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_11\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_10_input (InputLayer) [(None, 28, 28, 1)]       0         \n",
      "_________________________________________________________________\n",
      "conv2d_10 (Conv2D)           (None, 28, 28, 20)        520       \n",
      "_________________________________________________________________\n",
      "activation_15 (Activation)   (None, 28, 28, 20)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_10 (MaxPooling (None, 14, 14, 20)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_11 (Conv2D)           (None, 14, 14, 50)        25050     \n",
      "_________________________________________________________________\n",
      "activation_16 (Activation)   (None, 14, 14, 50)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_11 (MaxPooling (None, 7, 7, 50)          0         \n",
      "_________________________________________________________________\n",
      "flatten_5 (Flatten)          (None, 2450)              0         \n",
      "_________________________________________________________________\n",
      "dense_15 (Dense)             (None, 500)               1225500   \n",
      "_________________________________________________________________\n",
      "activation_17 (Activation)   (None, 500)               0         \n",
      "_________________________________________________________________\n",
      "dense_17 (Dense)             (None, 100)               50100     \n",
      "=================================================================\n",
      "Total params: 1,301,170\n",
      "Trainable params: 50,100\n",
      "Non-trainable params: 1,251,070\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = build_model(input_shape, num_classes)\n",
    "\n",
    "# Compile Keras Model \n",
    "model.compile(loss=loss,\n",
    "              optimizer=optimizer,\n",
    "              metrics=metrics)\n",
    "    \n",
    "# load weights\n",
    "model.load_weights(pretrained_weights)\n",
    "    \n",
    "testPredict = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test_tmp = np.floor(np.argmax(y_test, axis=1) / 10).astype(int)\n",
    "y_pred_tmp = np.floor(np.argmax(testPredict, axis=1) / 10).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 'Arabic',\n",
       " 1: 'Bangla',\n",
       " 2: 'Devanagari',\n",
       " 3: 'English',\n",
       " 4: 'Farsi',\n",
       " 5: 'Kannada',\n",
       " 6: 'Swedish',\n",
       " 7: 'Telugu',\n",
       " 8: 'Tibetan',\n",
       " 9: 'Urdu'}"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_mapping = {i:languages[i] for i in range(10)}\n",
    "label_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_true = [label_mapping[i] for i in y_test_tmp]\n",
    "y_pred = [label_mapping[i] for i in y_pred_tmp]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Arabic']"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_true[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Urdu',\n",
       " 'Farsi',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Farsi',\n",
       " 'Arabic',\n",
       " 'Arabic',\n",
       " 'Farsi',\n",
       " 'Bangla',\n",
       " 'Arabic']"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "import pandas as pd\n",
    "import seaborn as sn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "\n",
    "data = confusion_matrix(y_true, y_pred)\n",
    "df_cm = pd.DataFrame(data, columns=np.unique(y_true), index = np.unique(y_true))\n",
    "df_cm.index.name = 'Actual Language'\n",
    "df_cm.columns.name = 'Predicted Language'\n",
    "plt.figure(figsize = (12, 9))\n",
    "sn.set(font_scale=1.4)  # for label size\n",
    "sn.heatmap(df_cm, cmap=\"Blues\", annot=True, fmt='d', annot_kws={\"size\": 18})  # font size\n",
    "plt.savefig('languages-confusion-matrix.pdf', dpi=400, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the confusion matrix for different numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test_tmp = np.floor(np.argmax(y_test, axis=1) % 10).astype(int)\n",
    "y_pred_tmp = np.floor(np.argmax(testPredict, axis=1) % 10).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: '0',\n",
       " 1: '1',\n",
       " 2: '2',\n",
       " 3: '3',\n",
       " 4: '4',\n",
       " 5: '5',\n",
       " 6: '6',\n",
       " 7: '7',\n",
       " 8: '8',\n",
       " 9: '9'}"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_mapping = {i:str(i) for i in range(10)}\n",
    "label_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_true = [label_mapping[i] for i in y_test_tmp]\n",
    "y_pred = [label_mapping[i] for i in y_pred_tmp]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['6', '5', '4', '5', '5', '2', '8', '0', '1', '4']"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_true[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['6', '5', '4', '5', '5', '2', '8', '0', '5', '4']"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "import pandas as pd\n",
    "import seaborn as sn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "\n",
    "data = confusion_matrix(y_true, y_pred)\n",
    "df_cm = pd.DataFrame(data, columns=np.unique(y_true), index = np.unique(y_true))\n",
    "df_cm.index.name = 'Actual Number'\n",
    "df_cm.columns.name = 'Predicted Number'\n",
    "plt.figure(figsize = (12, 9))\n",
    "sn.set(font_scale=1.4)  # for label size\n",
    "sn.heatmap(df_cm, cmap=\"Blues\", annot=True, fmt='d', annot_kws={\"size\": 18})  # font size\n",
    "plt.savefig('numbers-confusion-matrix.pdf', dpi=400, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some further exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_true = np.argmax(y_test, axis=1).astype(int)\n",
    "y_pred = np.argmax(testPredict, axis=1).astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can compare the confusion matrix between two numbers from one/two languages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred):\n",
    "    index1 = languages.index(language1) * 10 + number1\n",
    "    index2 = languages.index(language2) * 10 + number2\n",
    "    pairs = [(i, j) for i, j in zip(y_true, y_pred) if i in (index1, index2) and j in (index1, index2)]\n",
    "    y_true_tmp, y_pred_tmp = zip(*pairs)\n",
    "    \n",
    "    label_mapping = {index1: language1 + ': ' + str(number1),\n",
    "                     index2: language2 + ': ' + str(number2)}\n",
    "    \n",
    "    y_true = [label_mapping[i] for i in y_true_tmp]\n",
    "    y_pred = [label_mapping[i] for i in y_pred_tmp]\n",
    "    \n",
    "    \n",
    "    data = confusion_matrix(y_true, y_pred)\n",
    "    df_cm = pd.DataFrame(data, columns=np.unique(y_true), index=np.unique(y_true))\n",
    "    df_cm.index.name = 'Actual Number'\n",
    "    df_cm.columns.name = 'Predicted Number'\n",
    "    plt.figure(figsize = (12, 9))\n",
    "    sn.set(font_scale=1.4)  # for label size\n",
    "    sn.heatmap(df_cm, cmap=\"Blues\", annot=True, fmt='d', annot_kws={\"size\": 18})  # font size\n",
    "    plt.savefig('%s-%s-%s-%s-confusion-matrix.pdf' % (language1, number1, language2, number2), dpi=400, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 4\n",
    "language1 = 'Bangla'\n",
    "number2 = 8\n",
    "language2 = 'English'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 7\n",
    "language1 = 'Bangla'\n",
    "number2 = 9\n",
    "language2 = 'English'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 9\n",
    "language1 = 'Swedish'\n",
    "number2 = 9\n",
    "language2 = 'English'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we want to find out which number pairs are the most difficult to distinguish:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import metrics\n",
    "def pair_comparison(number1, language1, number2, language2, languages, full_cm):\n",
    "    index1 = languages.index(language1) * 10 + number1\n",
    "    index2 = languages.index(language2) * 10 + number2\n",
    "    \n",
    "    tmp_cm = full_cm[[index1, index2], :][:, [index1, index2]]\n",
    "\n",
    "    accuracy = sum(np.diag(tmp_cm)) / sum(tmp_cm.flatten())\n",
    "    return number1, language1, number2, language2, accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(9, 'Swedish', 9, 'English', 0.9925999013320178)\n"
     ]
    }
   ],
   "source": [
    "number1 = 9\n",
    "language1 = 'Swedish'\n",
    "number2 = 9\n",
    "language2 = 'English'\n",
    "full_cm = confusion_matrix(y_true, y_pred)\n",
    "print(pair_comparison(number1, language1, number2, language2, languages, full_cm))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = []\n",
    "# calculate full confusion matrix\n",
    "full_cm = confusion_matrix(y_true, y_pred)\n",
    "for i1 in range(len(languages)):\n",
    "    for i2 in range(i1, len(languages)):\n",
    "        language1 = languages[i1]\n",
    "        language2 = languages[i2]\n",
    "        for number1 in range(10):\n",
    "            for number2 in range(number1, 10):\n",
    "                if language1 == language2 and number1 == number2:\n",
    "                    continue\n",
    "                results.append(pair_comparison(number1, language1, number2, language2, languages, full_cm))\n",
    "results = sorted(results, key=lambda x:x[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(4, 'Devanagari', 4, 'Telugu', 0.7159090909090909),\n",
       " (1, 'Bangla', 9, 'Bangla', 0.8728763913298184),\n",
       " (4, 'Arabic', 6, 'Kannada', 0.8750495834986116),\n",
       " (8, 'Farsi', 8, 'Urdu', 0.8808743169398907),\n",
       " (0, 'Devanagari', 1, 'Telugu', 0.8850574712643678),\n",
       " (5, 'Devanagari', 6, 'Urdu', 0.916083916083916),\n",
       " (8, 'Arabic', 8, 'Farsi', 0.91816223977028),\n",
       " (0, 'Telugu', 1, 'Telugu', 0.918918918918919),\n",
       " (1, 'Devanagari', 9, 'Urdu', 0.9285714285714286),\n",
       " (0, 'Bangla', 0, 'Tibetan', 0.9324561403508772)]"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 4\n",
    "language1 = 'Devanagari'\n",
    "number2 = 4\n",
    "language2 = 'Telugu'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 1\n",
    "language1 = 'Bangla'\n",
    "number2 = 9\n",
    "language2 = 'Bangla'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 4\n",
    "language1 = 'Arabic'\n",
    "number2 = 6\n",
    "language2 = 'Kannada'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 8\n",
    "language1 = 'Farsi'\n",
    "number2 = 8\n",
    "language2 = 'Urdu'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 0\n",
    "language1 = 'Devanagari'\n",
    "number2 = 1\n",
    "language2 = 'Telugu'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 5\n",
    "language1 = 'Devanagari'\n",
    "number2 = 6\n",
    "language2 = 'Urdu'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArYAAAIiCAYAAAA99Iu5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzdeXxTdbrH8W/ShVJCWUuLLGWpFFBZZBMHyzKKjsBIRVCkCIIU2UFQEVTqCOJKscMiXEAQAdkZBVFHBEdUliKOLAUqYkUoLVKhlJaGtrl/MERqChygOU3D531feb3I75ycPAkz9z5875PfsTgcDocAAACAEs5a3AUAAAAARYHGFgAAAF6BxhYAAABegcYWAAAAXoHGFgAAAF6BxhYAAABewbe4CygqzSduLO4SAJQAm8e2L+4SAJQQAR7SJZVuOtSt18/eOc2t1zcTiS0AAACuyaxZs9SzZ88Ca0899ZQiIiIKPCIjI53H8/PzFR8fr7vuukuNGzdWv379lJycXOAaiYmJ6t27t5o0aaJ27dpp7ty5huqhsQUAAPBkFqt7H9do0aJFiouLc1nfv3+/hg8frs2bNzsfa9ascR6fPn26lixZookTJ2rp0qXy8fFR//79lZOTI0lKT09X3759FRYWppUrV2rEiBGKj4/XsmXLrliTh4TsAAAAKAlSU1M1YcIEbd26VbVr1y5wzG636+eff9Ztt92m4OBgl9fa7XbNmzdPY8aMUdu2bSVJcXFxatOmjdavX6+uXbtq2bJl8vPzU2xsrHx9fVW3bl0lJydr9uzZ6tGjx2VrI7EFAADwZBaLex9Xac+ePSpTpow+/PBDNW7cuMCxgwcPKjc3V+Hh4YW+NjExUVlZWbrjjjucazabTQ0bNlRCQoIkKSEhQc2bN5ev7x/5a6tWrXT48GGlpqZetjYSWwAAABjWoUMHdejQodBj+/fvl6+vr2bNmqWvvvpKPj4+atu2rUaMGKGyZcs6G9OQkJACr6tSpYpSUlIknU+E/9wYV6lSRZKUkpLi8tqL0dgCAAB4suuYgzUiIyNDGRkZLutBQUEKCgq6qmslJSVJkqpXr6533nlHycnJeu2117Rv3z699957ys7OliT5+/sXeJ2/v7/sdrsk6ezZs4Uel+Scw70UGlsAAIAb2IIFCzRtmuuWX0OHDtWwYcOu6lqjR4/WwIEDnQ1xvXr1VLlyZT3yyCP6/vvvFRAQIOn8rO3FzavdbldgYKAkKSAgwNnkXnxckvOcS6GxBQAA8GTXMAd7Nfr06aOoqCiX9atNayXJarW6vC4iIkLS+TGCGjVqSJLS0tJks9mc56SlpTnHD0JDQ5WWllbgGheeh4aGXvb9aWwBAABuYNcycnApQ4YMUX5+vmbOnOlc++GHHyRJ4eHhql27tmw2m7Zt26Y6depIkjIzM7V37149+uijkqQWLVpo0aJFys3Ndf6AbMuWLapVq1ahOy1cjF0RAAAAPJmH7mNbmPvvv19ffPGFZs+erV9++UWbNm3SuHHjdO+99yoiIkL+/v6Kjo5WXFycPv/8c+3bt0+jRo1SSEiIOnbsKEnq1q2bsrOzNW7cOP34449as2aN5s+fr4EDB17x/UlsAQAAUCQ6deqk/Px8zZkzR9OnT1fZsmXVqVMnjRo1ynnO8OHDlZeXpxdffFHZ2dlq1qyZ5syZ45y5rVSpkubOnatJkyYpKipKwcHBGj16tB588MErvr/F4XA43PbpTNR84sbiLgFACbB5bPviLgFACRHgIfFf6VZPu/X62VvfcOv1zcQoAgAAALyCh/xbBAAAAIVy8z623oRvCgAAAF6BxBYAAMCTuXkfW29CYgsAAACvQGILAADgyZixNYxvCgAAAF6BxBYAAMCTMWNrGIktAAAAvAKJLQAAgCdjxtYwGlsAAABPxiiCYfwTAAAAAF6BxBYAAMCTMYpgGN8UAAAAvAKJLQAAgCcjsTWMbwoAAABegcQWAADAk1nZFcEoElsAAAB4BRJbAAAAT8aMrWF8UwAAAPAKJLYAAACejDuPGUZiCwAAAK9AYgsAAODJmLE1jG8KAAAAXoHEFgAAwJMxY2sYiS0AAAC8AoktAACAJ2PG1jC+KQAAAHgFElsAAABPxoytYSS2AAAA8AoktgAAAJ6MGVvD+KYAAADgFUhsAQAAPBkztobR2AIAAHgyRhEM45sCAACAVyCxBQAA8GSMIhhGYgsAAACvQGILAADgyZixNYxvCgAAAF6BxBYAAMCTkdgaxjcFAAAAr0BiCwAA4MnYFcEwElsAAAB4BRJbAAAAT8aMrWF8UwAAAPAKJLYAAACejBlbw0hsAQAA4BVIbAEAADwZM7aG8U0BAADAK5DYAgAAeDJmbA0jsQUAAIBXILEFAADwYBYSW8NIbAEAAOAVSGwBAAA8GImtcTS2AAAAnoy+1jBGEQAAAOAVSGwBAAA8GKMIxpHYAgAAwCuQ2AIAAHgwElvjSGwBAADgFUhsAQAAPBiJrXEktgAAAPAKJLYAAAAejMTWOBJbAAAAeAUSWwAAAE9GYGsYiS0AAAC8AoktAACAB2PG1jgSWwAAAHgFElsAAAAPRmJrHIktAAAAvAKJLQAAgAcjsTWOxBYAAABegcQWAADAg5HYGkdiCwAAAK9AYgsAAODJCGwNo7EFAADwYIwiGMcoAgAAALwCiS0AAIAHI7E1jsQWAAAAXoHEFgAAwIOR2BpHYgsAAACvQGILAADgyQhsDSOxBQAAgFcgsQUAAPBgzNgaR2ILAAAAr0BjCwAA4MEsFotbH9dj1qxZ6tmzZ4G1b7/9Vo888ohuv/12RUZG6oUXXtDJkyedx/Pz8xUfH6+77rpLjRs3Vr9+/ZScnFzgGomJierdu7eaNGmidu3aae7cuYbqobEFAADAVVu0aJHi4uIKrO3Zs0cDBgxQixYttHLlSr311lv6/vvvNWzYMDkcDknS9OnTtWTJEk2cOFFLly6Vj4+P+vfvr5ycHElSenq6+vbtq7CwMK1cuVIjRoxQfHy8li1bdsWamLEFAADwYJ42Y5uamqoJEyZo69atql27doFjS5cuVUREhEaPHi1Jql27tiZMmKBevXopOTlZN910k+bNm6cxY8aobdu2kqS4uDi1adNG69evV9euXbVs2TL5+fkpNjZWvr6+qlu3rpKTkzV79mz16NHjsrWR2AIAAMCwPXv2qEyZMvrwww/VuHHjAsceffRRxcbGFvq6U6dOKTExUVlZWbrjjjuc6zabTQ0bNlRCQoIkKSEhQc2bN5ev7x/5a6tWrXT48GGlpqZetjYSWwAAAA/m7sQ2IyNDGRkZLutBQUEKCgpyWe/QoYM6dOhQ6LXq16/vsjZ79mwFBwerYcOG2rhxoyQpJCSkwDlVqlRRSkqKpPOJcHh4uMtxSUpJSXF57cVobAEAAG5gCxYs0LRp01zWhw4dqmHDhl3zdR0Oh1555RX95z//0bRp0+Tn56fs7GxJkr+/f4Fz/f39ZbfbJUlnz54t9Lgk5xzupdDYAgAAeDI3j9j26dNHUVFRLuuFpbVG2e12jRs3TuvWrdPLL7+su+++W5IUEBDgPH5x82q32xUYGOg850KTe/FxSc5zLoXGFgAA4AZ2qZGDa3Xy5EkNHjxYu3fvVnx8vO655x7nsapVq0qS0tLSZLPZnOtpaWnO8YPQ0FClpaUVuOaF56GhoZd9b348BgAA4ME8eR/bP8vKylK/fv30448/av78+QWaWun8DK7NZtO2bduca5mZmdq7d69atmwpSWrRooV27Nih3Nxc5zlbtmxRrVq1FBwcfNn3p7EFAABAkZgyZYr27dunyZMnq0aNGjp+/LjzcWH8IDo6WnFxcfr888+1b98+jRo1SiEhIerYsaMkqVu3bsrOzta4ceP0448/as2aNZo/f74GDhx4xfdnFAEAAMCDedo+tpfz4YcfKi8vT4MHD3Y59u677+rOO+/U8OHDlZeXpxdffFHZ2dlq1qyZ5syZ45y5rVSpkubOnatJkyYpKipKwcHBGj16tB588MErvr/FceE2ECVc84kbi7sEACXA5rHti7sEACVEgIfEfzWG/Mut1z88/QG3Xt9MjCIAAADAK3jIv0UAAABQqJIziVDsSGwBAADgFUhsAQAAPFhJ+vFYcaOxRYkwvlOEalYsrYELvy+wflP5AI28O1zNwspLkjYnnVDc5z/qZNa5Auc1r1VeT7atrZur2HQmJ0+fJ6Zp5qZDyj6XJ0mqWi5AHw1rfdkaBi7cqR3JJ4vwUwEobl9v/kr/N2umEvfukcViVaPGjTV0+Eg1atykuEsDcA1obOHxHmhSVVFNb9KO5N8LrJcr7at3opvIz8eq9775RT5Wi3q3rqHwKmXUZ94O5eaf3/CjWVh5TX+0ifalnNa0L35SSFApPdKyuhreVFYDFuyUQ9LvWXa9sGavy3uX8rPq6Xtv1u9nzulAaqYZHxeASRK2b9OQJweobvjNGjp8lPLycrX0g8Xq1yda7763WLc1alTcJQKSSGyvBo0tPJbVIvVrU0sxkbUKPd6rVQ1VCSqlR2Zt188nsiRJu49maEavJurcOFRrdqZIkkbeHa5jGWcVs3CncnLzJUnHMs5q7N8i1LpuRX1zMF1nz+Vr/e5Ul/d46p5w+Vqten7NXp0+m+tyHEDJ9fqrryg0tKreX7JMpUuXliR1+XtXde1yv6bFx2nWnHeLuUIAV4sfj8Ej+ftY9f4TLfRk29r6eNcxpWacdTmn4y0h2pF80tnUStK2Q7/r59/OqGPDEOd1fs+ya83OFGdTK0nf/W+k4OYqNl1K3eAyerhFda39IUXfHz5VVB8NgAfIOHVKB/bvU8f77nM2tZJUqXJlNWvRQt9/v7MYqwMKKkm31C1uJLbwSP6+VpUp5aOxK3fr88Tj+nDoHQWOlw3wVfUKpbUhMc3ltfuOZapNeCVJkj0vX8OX/OByTr3QspLOJ7eXMqR9HeXk5mnGpkPX81EAeKAyNpv+te6TAk3tBSd//12+Pj7FUBWA62VaY5uWlqbvvvtODRs2VM2aNZWYmKi3335bycnJqlWrlp588kk1btzYrHLg4c7k5OrB6VuVd4kb41UpW0qSlHY6x+XYb5k5sgX4qkwpH53JyStwLLRcKTUPq6CRd4frx7RMbdz3W6HXD69SRpH1Kmvht7/oRKb9Oj8NAE/j4+OjsLBaLusH9u/T9zu/051/aWN+UcAleFuq6k6mjCLs3LlTf/vb3zRy5Eh16dJFX3zxhaKjo3X69Gm1b99edrtdjz76qLZv325GOSgBHNIlm1pJCvQ/n6acPZfvcuzCyEFpv4KJS1CAr9YOu1Oxf2+gUr5WvfFpkux5rq+XpIeaVVNufr6WJvx6jZ8AQEmTdeaMnn/uWUlSvydiirkaANfClMT2zTff1P33369nn31Wy5cv14gRI9StWzfFxsY6z5k6daqmTJmiJUuWmFESSjirgX+9/rkvdkh6btUe+flY9HCL6preq7HGr9qrDfuOFzivlK9Vf7s1RP85cELHTrkmwgC8T3Z2toYPHaT9+/ep/4CBat6iZXGXBPyBwNYwUxLbxMREDRgwQDabTX369FF+fr66d+9e4JyoqCgdOHDAjHLgBc7Yz+9QUMrX9T/CF9YunHPB6bO5+vfeNH28K1Ux7+3UsVM5GnVPuMvrm4eVV5lSvoXO7wLwPhkZGXpyQD9t37ZVXR/spmEjRhV3SQCukSmNbbly5fTrr+f/X7opKSnKy8tTWlrBpuHYsWMqV66cGeXAC1xIUivb/F2OBZctpYzsc4WOKVyQk5uvr5J+U2i5AJUr7Vfg2F/CK8mem6/NSSeKtmgAHufEiRN64vHH9P3O79St+8OK/cck5hnhcdgVwThTRhE6d+6sZ555Rl26dNGmTZsUHh6uWbNmyWaz6dZbb9X+/fv10ksvqX379maUAy+QmZOrX3/PVsT/dje4WESITYkppyVJYZUC9c+ejfTet79oxY6jBc4r4++rfIdD5/40Z9u4RjntTcnQGXvBH54B8C5nzmRqUEx/7d+XqOjH+urpZ58r7pIAXCdTGtvhw4fLarXqiy++UJUqVfTCCy/owIEDevzxx5WXd755uP322zVy5EgzyoGX+GLfcT3asrrCKgUq+X972basXUG1KpfRwi2HJUm/pmfLVspX3W6vpjU7U5x3IwstV0od6gfru+STyrqogfWxWlS7chmt3nnU9Q0BeJVXJv5D+/clqlf0YzS18Gjelqq6kymNrZ+fn0aNGqVRo/6YWwoPD1fTpk31ww8/KDQ0VI0aNeIvDlflvW9/UafbQjWzVxMt2npY/r5WPda6hvYezdDHu45JOr+zwhufJunlrg01+7GmWr8rVeUC/dSjeTU5dP7YxULLlZK/r1XHTl16f1sAJd9PBw9q7Yf/UtmyZRVRv4HWfvQvl3M6d3mgGCoDcD2K9QYNVatWVdWqVYuzBJRgJ7POKea97/RUx5s1sG0tnT2Xr037f9PbGw7qXN4fWyKs352qc3n56nNnmEbdE67sc3nafuh3zdj0k35Jzy5wzfL/m7dlDAHwbgkJ2yRJp0+f1ovPF57W0tjCU5D7GWdxOC6zWWgJ0nzixuIuAUAJsHkss/wAjAnwkPuzho9Z79br//jm39x6fTN5yF8ZAAAACsOopnGmbPcFAAAAuBuJLQAAgAcjsDXO9MR2zZo1stvtLus5OTlas2aN2eUAAAB4NG7QYJzpje3YsWN1+vRpl/XTp09r7NixZpcDAAAAL2H6KMKGDRtUoUIFl/WKFStqw4YNZpcDAADg0bwsVHUr0xPbatWqyWq16syZM861gwcPymq1qlq1amaXAwAAAC9hemObmpqqBx98UDNnznSu9ezZUw8//LBOnDhhdjkAAAAezWq1uPXhTUxvbCdNmqTAwED16NHDubZ06VL5+vrqtddeM7scAAAAeAnTZ2y3bt2qhQsXqmbNms612rVra/z48erXr5/Z5QAAAHg0ZmyNMz2xzc/PV25urmshVmuh24ABAAAARpje2N5xxx166623lJGR4Vw7ffq0pk6dqpYtW5pdDgAAgEdjH1vjTB9FePbZZ/Xoo4+qbdu2znGEX375RRUqVNDcuXPNLgcAAABewvTGtnr16vr444+1du1aJSUlyc/PT9HR0erSpYsCAgLMLgcAAMCjeVmo6lamN7aSZLPZ9MgjjxTHWwMAAMBLmdLY9urVSzNnzlRQUJB69ep12XMXLVpkRkkAAAAlgrfNwbqTKY1tzZo1ZbVanX8GAAAAipopje3kyZML/TMAAAAuj8TWuGKZsU1JSdHixYuVlJQkf39/1atXT9HR0SpfvnxxlAMAAAAvYPo+tj/88IPuvfderVu3Tn5+fsrNzdWyZct07733au/evWaXAwAA4NEsFvc+vInpiW1sbKweeOABxcbGysfHR5Jkt9v13HPPaeLEiVq8eLHZJQEAAMALmJ7YJiUlqV+/fs6mVpL8/f01aNAg7d692+xyAAAAPBp3HjPO9Ma2Tp06OnDggMv6zz//rOrVq5tdDgAAALyEKaMI3377rfPP9913n1588UWlpaWpSZMm8vHx0d69exUXF6chQ4aYUQ4AAECJ4WWhqltZHA6Hw91vUr9+fVksFl3prSwWixITE6/pPZpP3HhNrwNwY9k8tn1xlwCghAgolr2jXDV72b09zo4XvOd/L5ryV7ZhwwYz3gYAAAA3MFMa22rVqhk6Lysry82VAAAAlCyMIhhnesienp6uGTNmaP/+/crPz5ckORwO2e12HTx4UDt37jS7JAAAAHgB03dFiI2N1dq1axUSEqKdO3fqpptu0tmzZ7V7924NGjTI7HIAAAA8Gtt9GWd6Yrtlyxa9/vrrateunRITE/XEE08oIiJCL7zwgn788UezywEAAICXMD2xzcrKUkREhKTze9pe2AUhOjpaW7duNbscAAAAj8YtdY0zvbENCQnRkSNHJElhYWHat2+fJCkgIECnTp0yuxwAAAB4CdMb244dO+qZZ55RQkKC7rzzTq1evVrr1q3T22+/rbCwMLPLAQAA8GjM2Bpn+oztqFGjlJubq5SUFHXp0kUdO3bU6NGjVbZsWcXHx5tdDgAAALyE6Y3thx9+qEGDBqlixYqSpJdfftnZ2Pr4+JhdDgAAgEfzslDVrUwfRXjttdf0+++/F1grX748TS0AAACui+mNbd26dbVr1y6z3xYAAKBEYsbWONNHEcLDwzVu3DjNmzdPtWrVUkBAQIHjr7/+utklAQAAwAuY3tgmJyerWbNmkuQyknDixAmzywEAAPBoXhaqupXpje3ChQtd1rZu3aolS5bo+++/N7scAAAAeAnTG9sLTp8+rdWrV+uDDz7QoUOH5O/vr6ioqOIqBwAAwCN52xysO5ne2O7atUsffPCBPv74Y2VnZ8tiseixxx7TwIEDnVuAAQAAAFfLlMb27NmzWrt2rZYsWaI9e/aoTJky6tixo+6//34NGTJE3bt3p6kFAAAoBIGtcaY0tpGRkcrPz1dkZKQGDhyodu3ayd/fX5LkcDjMKAEAAABezpTGNjc3V2XLllVAQIDOnTun3NxcZ2MLAACAS2PG1jhTGtuvv/5an3zyiVasWKFVq1YpICBAbdu21f33389fFgAAwGXQKxlnyp3HSpcuraioKC1atEiffPKJoqOj9d1332nEiBHKy8vT3LlzdfDgQTNKAQAAgJcy/Za6tWrV0pgxY/Tll19qxowZ+utf/6qPPvpInTt31uOPP252OQAAAB7NYnHvw5sU2z62VqtVHTp0UIcOHZSenq7Vq1dr1apVxVUOAAAASjjTE9vCVKxYUf3799e6deuKuxQAAACPYrFY3PrwJh7R2AIAAADXq9hGEQAAAHBlXhaquhWJLQAAALwCiS0AAIAH87Y5WHcisQUAAIBXILEFAADwYAS2xpHYAgAAwCuQ2AIAAHgwK5GtYSS2AAAA8AoktgAAAB6MwNY4ElsAAAB4BUON7SOPPKJNmza5uRQAAAD8mcVicevDmxhqbPfv3y9/f3931wIAAABcM0ONbYcOHfTBBx8oKyvL3fUAAADgIlaLex/exNCPx3x9ffXpp5+qZcuWqlatmipXrlzguMVi0fvvv++WAgEAAAAjDDW2R48eVdOmTd1dCwAAAP7E2+Zg3clQY7tw4UJ31wEAAIBCeFJfe+bMGU2ZMkWff/65MjMz1apVK40dO1Y1a9aUJCUmJuqVV17Rrl27VL58efXu3Vv9+/d3vj4/P1/Tpk3T8uXLlZGRoWbNmmnChAkKCwsrkvquarsvu92uhIQErVu3TqdOndKxY8eKpAgAAAB4vpEjR+rTTz/Viy++qGXLlqlixYrq2bOnfv/9d6Wnp6tv374KCwvTypUrNWLECMXHx2vZsmXO10+fPl1LlizRxIkTtXTpUvn4+Kh///7KyckpkvoM36BhyZIlmjp1qk6dOiWLxaIVK1ZoypQpkqRp06apdOnSRVIQAAAA/mCRZ0S2+/bt03/+8x/NnDlTHTp0kCS99NJL2r59uxYvXiwfHx/5+fkpNjZWvr6+qlu3rpKTkzV79mz16NFDdrtd8+bN05gxY9S2bVtJUlxcnNq0aaP169era9eu112jocR2zZo1eumll3Tvvfdq1qxZcjgckqSoqCh99913mjZt2nUXAgAAAM/1888/S5JatGjhXPPx8VH9+vW1bds2JSQkqHnz5vL1/SM3bdWqlQ4fPqzU1FQlJiYqKytLd9xxh/O4zWZTw4YNlZCQUCQ1Gkps58yZo549e2rChAnKy8tzrnfu3FnHjh3TkiVL9PTTTxdJQQAAAPiDu7fkysjIUEZGhst6UFCQgoKCnM+Dg4Mlnd9UICIiwrn+66+/ym63S5LCw8MLXKNKlSqSpJSUFKWlpUmSQkJCXM5JSUkpgk9iMLFNTk5W+/btCz12yy236Pjx40VSDAAAAMy1YMEC/fWvf3V5LFiwoMB5jRo1Unh4uGJjY3X06FHnaMG+fftkt9t19uxZlxt6XXiek5Oj7OzsAmsXn3OhMb5ehhLbypUra//+/YqMjHQ5lpSU5LKvLQAAAIqGu7f76tOnj6KiolzWL05rJcnPz0/Tpk3T2LFj1b59e/n6+qpdu3Z66KGHtHv3btntdpcG9cLzwMBABQQEONcubm7tdrsCAwOL5LMYamw7deqkGTNmKCQkxDksbLFY9P3332vWrFlFMuwLAAAA8/155OByateuraVLlzo3EwgKCtKIESNUq1YtZWRkOMcNLrjwPDQ01PkbrbS0NNlstgLn/HmE4VoZGkUYPny4WrZsqWeeecY5MNyrVy/17NlTdevW1fDhw4ukGAAAABRksbj3YVRmZqaio6O1a9culStXTkFBQcrMzNQ333yju+66Sy1atNCOHTuUm5vrfM2WLVtUq1YtBQcHq379+rLZbNq2bVuBa+7du1ctW7Ysku/KUGLr7++vWbNm6ZtvvtG3336rkydPqmzZsmrVqpUiIyO5IwYAAICXs9lsslgseuWVVxQbGyuHw6GJEyfqpptuUufOnXXq1CnNmTNH48aNU0xMjHbv3q358+drwoQJks73k9HR0YqLi1PlypVVvXp1vfXWWwoJCVHHjh2LpEaL40IuXMI1n7ixuEsAUAJsHlv4D2EB4M8CDO/2714Pzt3h1uuv6t/M8LlpaWmaOHGivv32W1mtVrVv317PPPOMKlasKEnatWuXJk2apD179ig4OFh9+/bVY4895nx9Xl6e4uLitGrVKmVnZzvvPFajRo0i+SyGG9sDBw5o5syZ+uabb3T69GlVrFhRrVq10uDBg1W3bt0iKeZ60NgCMILGFoBRNLYlj6G/sm+++UYxMTEqX7687r77blWqVEnHjx/Xpk2b9MUXX2jRokVq2LChu2sFAAC44TDxaZyhxnbKlClq1qyZZs+erVKlSjnXMzMz1b9/f02ePFkLFy50W5EAAADAlRjaFeHAgQPq06dPgaZWOj9EPGDAAP3www9uKQ4AAOBGZ7FY3PrwJoYa22rVqunIkSOFHjt9+rTzdmkAAABAcblkY5ufn+98jBkzRtOmTdPHH3+svLw85zlffTNnT4AAACAASURBVPWV3n77bT399NOmFAsAAHCj8ZR9bEuCS+6KUL9+/QLxtMPhkMVikY+Pj8qXL6+MjAydO3dOvr6+KleunDZv3mxa0YVhVwQARrArAgCjPGVXhO7zv3Pr9Zf3vd2t1zfTJf/KhgwZ4nVzFwAAACWNlX7MsEs2tsOGDTOzDgAAAOC6GA7Zz549q59++kmnTp0q9Hjr1q2LrCgAAACcR15rnKHG9ttvv9VTTz2lkydP6uKRXIvF4py9TUxMdFuRAAAAwJUYamwnT56s8uXLa8KECapQoQKztwAAACah7zLOUGObnJysN998U/fcc4+76wEAAMBFrPS1hhm6QUOdOnWUmZnp7loAAACAa2YosR09erRiY2MVHBysJk2aKDAw0OUcq9VQjwwAAICrwCiCcYYa22rVqsnHx0cDBgwo9LjFYtHevXuLtDAAAADgahhqbJ977jmlp6ere/fuqlKlirtrAgAAwP8Q2BpnqLFNTEzUpEmT1LlzZ3fXAwAAAFwTQ41tSEiI/P393V0LAAAA/oQZW+MM/eJr4MCBio+PV1JSkrvrAQAAAK6JocR27dq1OnbsmP7+97+rTJkyKlOmTIF/PVgsFm3cuNFtRQIAANyo2MfWOEONbWhoqEJDQ91dCwAAAHDNDN9SFwAAAOZjxtY47qoAAAAAr2Aosa1fv/4V/7WQmJhYJAUBAADgD+S1xhlqbAcOHOjS2GZmZmrbtm367bffNGrUKLcUBwAAABhlqLG9XOM6fPhwtgEDAABwEysztoZd94ztQw89pLVr1xZFLQAAAMA1M5TYXs7x48eVnZ1dFLUAAADgTwhsjTPU2K5YscJlLT8/X0ePHtXixYvVqlWrIi8MAAAAuBqGGtvnn3/+kseaNWt22eMAAAC4duxja5yhxnbDhg0uaxaLRTabTUFBQUVeFAAAAHC1DDW21apVc3cdAAAAKASBrXGXbGzXrFlzVRfq2rXrdRcDAACAgtjuy7hLNrZjx4694osvnvmgsQUAAEBxumRj+9lnn132hdu3b9err76qzMxMPfLII0VeGAAAABhFuBqXbGxr1qxZ6LrdbteUKVP03nvvKTQ0VPHx8WrdurXbCgQAAACMuKobNPzwww969tlndejQIT300EMaO3asbDabu2oDAAC44bHdl3GGGttz584pPj5e7777ripVqqTZs2crMjLS3bVdlSUD7ijuEgCUABVaDC3uEgCUENk7pxV3CbhKV2xs9+zZo7FjxyopKUkPPPCAnn/+eZUtW9aM2gAAAG541uIuoAS5ZGObl5enGTNmaNasWapQoYJmzpyp9u3bm1kbAAAAYNglG9uHHnpI+/btU1BQkPr27asTJ05oxYoVl7zQQw895JYCAQAAbmTM2Bp3ycY2MTFRknTq1Cm98cYbl72IxWKhsQUAAECxumRju2HDBjPrAAAAQCGsBLaGXbKxrVatmpl1AAAAANflqvaxBQAAgLlIbI1jBwkAAAB4BRJbAAAAD8auCMaR2AIAAMArkNgCAAB4MGZsjbtkY9urVy/DF7FYLHr//feLpCAAAADgWlyysbVamVIAAAAobozYGnfJxnbhwoVm1gEAAABclyKJZQ8cOFAUlwEAAMCfWC0Wtz68iaEfj/3++++aMmWKtm3bJrvdLofDIUnKz89Xdna2MjMzlZiY6NZCAQAAbkQMhxpn6Lt69dVXtWrVKtWuXVv+/v4qX768mjRpIofDoTNnzujll192d50AAADAZRlqbL/66isNHjxY77zzjnr27KnQ0FBNnTpV69ev180338woAgAAgJtYLO59eBNDjW1GRoZuv/12SdLNN9+s3bt3S5JsNpsef/xxffnll+6rEAAAADDA0IxthQoVlJGRIUkKCwvTiRMn9Pvvv6tChQoKCQlRamqqW4sEAAC4UXnbD7zcyVBi27p1a82aNUvJycmqXr26KlasqDVr1kiSvvjiC1WoUMGtRQIAAABXYqixHTFihE6ePKmxY8dKkmJiYvTaa6+pWbNmev/999WtWze3FgkAAHCjYsbWOEOjCNWqVdP69et16NAhSVKfPn1UsWJFfffdd2rcuLG6du3q1iIBAACAKzHU2EpSqVKlVL9+fefzLl26qEuXLm4pCgAAAOdZvSxVdSdDje20adOueM7QoUOvuxgAAADgWl13Y1umTBlVrlyZxhYAAMAN2BXBOEON7Z49e1zWMjMztXXrVk2aNEmTJk0q8sIAAACAq2GosfXx8XFZK1eunDp27KjffvtNr732mpYvX17kxQEAANzoCGyNM7Td1+XUqlWLW+oCAACg2BneFaEwOTk5+uCDDxQcHFxU9QAAAOAi7IpgnKHGtm3btrL8KQfPy8vTyZMnde7cOY0fP94txQEAAABGGWpsW7du7dLYSpLNZlOHDh3UunXrIi8MAAAAkkVEtkYZamxfffXVyx7Pzc2Vr+91TTUAAAAA18XQj8f++te/au/evYUe27Fjh/7yl78UaVEAAAA4z2px78ObXDJmnT17trKzsyVJR44c0cKFCxUaGupy3n//+1/l5+e7r0IAAADAgEs2tvn5+Zo5c6YkyWKxaPXq1S7nWK1WlS1bViNHjnRfhQAAADcwb0tV3emSje2TTz6pJ598UpJUv359LVq0SM2aNTOtMAAAAKjQH/CjcIZmbDds2KBGjRopOTnZuZaenq6EhAS3FQYAAABcDUONbenSpdW7d2898cQTzrVdu3YpOjpa/fr1U2ZmptsKBAAAuJHx4zHjDDW2b7zxho4ePaoXXnjBuXbXXXdp3rx5+umnnzR16lS3FQgAAAAYYaix/eqrrzRmzBhFRkb+8UKrVXfeeaeGDx+uf//7324rEAAA4EZmsbj34U0MNbZnzpxRYGBgoccqVKigkydPFmlRAAAAwNUy1NjecsstWr58eaHHVqxYoQYNGhRpUQAAADjParG49eFNDN0H98knn1RMTIy6dOmijh07qlKlSkpPT9eGDRu0b98+zZ492911AgAAAJdlqLFt06aN3nnnHf3zn//UjBkz5HA4ZLFY1KBBA73zzjtq0qSJu+sEAAC4IXnbzgXuZKixlaTIyEhFRkYqJydHJ0+eVNmyZfXTTz/pgw8+0MiRI7Vz50531gkAAABclqEZ2z/7+uuv1adPH3Xv3p0ZWwAAADfytF0R1qxZo/vvv1+33XabOnXqpPXr1zuPJSYmqnfv3mrSpInatWunuXPnFnhtfn6+4uPjddddd6lx48bq169fgRuAXS/Dje2hQ4c0efJkRUZGavz48Tpx4oSefPJJffbZZ1q8eHGRFQQAAADP9K9//Uvjxo3Tww8/rLVr16pz58566qmntGPHDqWnp6tv374KCwvTypUrNWLECMXHx2vZsmXO10+fPl1LlizRxIkTtXTpUvn4+Kh///7KyckpkvouO4qQl5enzz//XEuWLNHWrVvl5+entm3b6vPPP9ebb76p22+/vUiKAAAAQOGs8owhW4fDobffflvR0dHq06ePJGnQoEFKSEjQli1btH37dvn5+Sk2Nla+vr6qW7eukpOTNXv2bPXo0UN2u13z5s3TmDFj1LZtW0lSXFyc2rRpo/Xr16tr167XXeMlG9v4+HgtX75cx48f1y233KLnn39eXbp0kY+Pj5o1a3bdbwwAAICS46efftKRI0fUuXPnAusXxg2eeOIJNW/eXL6+f7SXrVq10syZM5Wamqpjx44pKytLd9xxh/O4zWZTw4YNlZCQ4N7GdsaMGYqIiFB8fLyaNm3qXM/KyrruNwUAAIAxnrLV7M8//yxJstvtiomJ0a5du1S9enUNGjRIHTp0UGpqqsLDwwu8pkqVKpKklJQUpaWlSZJCQkJczklJSSmSGi85Y9u9e3cdOXJEvXv3Vp8+fbR69WplZ2cXyZsCAADAM2RkZOjXX391eWRkZBQ4LzMzU5L0zDPP6N5779W8efPUpk0bDR48WF9//bXOnj0rf3//Aq+58DwnJ8fZRxZ2jt1uL5LPcsnE9uWXX9b48eO1fv16rVy5Us8995xefvlldejQQRaLRRZP+ecDAACAF3P3PrYLFizQtGnTXNaHDh2qYcOGOZ/7+flJkh5//HF169ZNktSgQQPt3r1b8+bNU0BAgEuDeuF5YGCgAgICnGsXN7d2u12BgYFF8lku++OxgIAARUVFKSoqSsnJyVqxYoXWrFkjh8Oh0aNHq1OnTurUqZPq169fJMUAAADAXH369FFUVJTLelBQUIHnoaGhkqR69eoVWL/55pu1YcMG1axZ0zlucMGF56GhoXI4HM41m81W4Jw/jzBcK8PbfYWFhWn06NH68ssv9c4776hBgwZ69913FRUVpU6dOhVJMQAAACjIarG49REUFKTq1au7PP7c2DZs2FBlypTRrl27CqwfOHBANWvWVIsWLbRjxw7l5uY6j23ZskW1atVScHCw6tevL5vNpm3btjmPZ2Zmau/evWrZsmWRfFeG7zx2gdVqVbt27dSuXTulp6dr9erVWrVqVZEUAwAAAM8UEBCgJ554QjNmzFCVKlXUpEkTrVu3Tps3b9a7776revXqac6cORo3bpxiYmK0e/duzZ8/XxMmTJB0fpY2OjpacXFxqly5sqpXr6633npLISEh6tixY5HUaHFcyIVLuKRUftgG4Moa3fd0cZcAoITI3uk6d1oc/m9r0d2ZqzADWoVd1fnz58/X+++/r2PHjqlOnToaNmyY7rnnHknSrl27NGnSJO3Zs0fBwcHq27evHnvsMedr8/LyFBcXp1WrVik7O1vNmjXThAkTVKNGjSL5LDS2AG4oNLYAjKKxLXmuehQBAAAA5rGyE5VhNLYAAAAejL7WOMO7IgAAAACejMQWAADAg5FCGsd3BQAAAK9AYgsAAODBLAzZGkZiCwAAAK9AYgsAAODByGuNI7EFAACAVyCxBQAA8GDcoME4ElsAAAB4BRJbAAAAD0ZeaxyJLQAAALwCiS0AAIAHY8TWOBJbAAAAeAUSWwAAAA/GnceMI7EFAACAVyCxBQAA8GCkkMbxXQEAAMArkNgCAAB4MGZsjSOxBQAAgFcgsQUAAPBg5LXG0dgCAAB4MEYRjGMUAQAAAF6BxBYAAMCDkUIax3cFAAAAr0BiCwAA4MGYsTWOxBYAAABegcQWAADAg5HXGkdiCwAAAK9AYgsAAODBGLE1jsQWAAAAXoHEFgAAwINZmbI1jMQWAAAAXoHEFgAAwIMxY2sciS0AAAC8AoktAACAB7MwY2sYiS0AAAC8AoktAACAB2PG1jgSWwAAAHgFElsAAAAPxj62xpHYAgAAwCuQ2AIAAHgwZmyNo7EFAADwYDS2xjGKAAAAAK9AYgsAAODBuEGDcSS2AAAA8AoktgAAAB7MSmBrGIktAAAAvAKJLQAAgAdjxtY4ElsAAAB4BRJbAAAAD8Y+tsaR2AIAAMArkNgCAAB4MGZsjSOxBQAAgFcgsUWJsWPbN1r63v/p4P5EWawWRTRspN5PDFH9Wxpd1TmSdOpkuhbM/qe2ff2lcnJyVLdeffUdOMLlPAAly/QXeiq8ZhXdO+DtAutfLRyj5rfWcjl/9ec79ejTc53P727dQGOfuFdNG9RUvsOhbbsO6aXpa7Vt189X/Z5AUWEfW+NobFEi7Po+QbFPD1HNWnXVe8AQ5eXl6ePVyzR2eH+99s95imh4m6FzJCkr64yeHdpf6SeO64HuvWQrG6S1qz7Q+JExemvW+6pVJ7yYPy2Aa9Gna2v1e/Av+k9CksuxiNqh+vCL/2r1hu8LrB9OSXf+uU2zcP1r2iDtPXhMsdM/kq+PVTE97tJnc0bo7n5TlbAn+areE4D5aGxRIvzfP99Q5SqhemvWQgUElJYkdbi3iwb1jtLCOdM0ccosQ+dI0opF83Tk8M+a/PYc3dqkmSQpssO9euKRzlq5ZL5Gj59YPB8SwDWxWi169ol79fzA+ws9HnZTJZUtE6CPNv2gDz7efsnrvDGmm35NPanIx95Q9tlzkqRFa7dp56rnFTu0izoPmmb4PYGixIytcTS28HiZpzN06McDinq4t7NhlaQKFSvp1ibNtHP7t4bOkSSHw6ENn3yk5q3vcja1klShUmX1GzxKPr78VwIoSUr5++o/C8eoUb3qev+jrWrfsp7LOQ3rVpUk7T907JLXKV+2tBrVq6a3F37hbGolKS39tDbv+FF/bV3/qt4TQPHg/4rD45UOLKN33l+jgNKlXY5lnDopHx9fQ+dIUmrKUZ04nqZuPftKOt/ons3OVunAQHWKetitnwNA0Qvw91NQmQBFPzNXK/+9U/vWveRyTsO6oZKkfYdSJUmBAf7KOmsvcE7GmbNqFPWysrLtLq+vVL6McnPzr+o9gaLEPrbGFVtjm5+fr88//1w///yz6tSpo3bt2smXtAyF8PHxUbUaYS7rhw4eUOKu73V7yzsNnSNJR389PyNXrkJFzZsxRZ98tEpZZzJVtVoNPTF0jFr9pa17PwyAIpVx5qxufeAfysvLv+Q5DevepIzMbL02+kE91PF2lS0ToJ8OH1fs9LVa/ukOSVJ+vkMHfznu8tpbb75JrZvU0b+/Tbyq9wRQPEzpJE+fPq3x48frq6++UtOmTTVlyhQNGzZM27dvV4UKFXTy5ElFRERo3rx5qlixohkloYTLzsrSlEnPS5Ie6vW44XPOZJ6WJL0/Z7p8ff0UM/xpWa0+WrVkgSaNH6V/vDlDTZrfYcInAFAUHA6H8vIclz2nQd2qCrKVVvmypfXEC++pXNlADXm0nd579XH5+lq1ZF3hc7dlSvtrzsuPSZLefPffV/WeQFEisDXOlMb29ddf1/79+/XUU0/ps88+U+/evSVJn332mWrWrKnU1FSNGDFCb775pl555RUzSkIJdvZstl5+boQO/XhA3aP76bYmzQ2fc+7c+dm5M5mZmr34X7KVDZIktbwzUgN6dtGC2fE0toCXmbfqa/lYrZq17D/OteWf7tCO5eP0ysgoLV2foPz8go1q6QA/rZg6UI0jquv1uZ9q844fzS4bwDUw5QYNGzdu1OTJk9W7d2+9/fbbSkpK0rPPPquaNWtKkkJCQjR27Fht3rzZjHJQgmWeztCLowfph53bdc/9XfXYgGFXdc6FH5bdGdnB2dRKkq1skFr9pa1+3J+o7Kws938QAKaZs2JzgaZWks7mnNPiddsVWjlIDepULXCsnK201s4YqnYtIzR/zTeaMO0jM8sFXFgtFrc+vIkpiW1OTo4qVKggSbLZbLJarSpfvnyBc4KCgpSTk2NGOSihTv6erhfHDNJPSft1X5duGjLmeVn+9F/IK51TKbiKpPMztn9WrnzF//2YLEulAwPd+2EAFLvj6edHk2yBpZxrwRVs+nDGEDWpX0NzVmzWsEkfFFd5gJN3tZ7uZUpi27RpU7311ltKSkrSG2+8oYCAAC1cuFD5+X8M3r/77rtq0KCBGeWgBMrKOuNsWB/oEa2hT7/g0tQaOSesdrj8/P31y6GDLu+ReuyI/P1LKah8Bbd+FgDmuSm4nHasGK/nYu5zORZRO0SS9POR3ySdb3AvNLXx739BUwuUQKYkts8995xiYmLUpUsXWa1WjR8/XomJifrb3/6m+vXrKykpSUeOHNHChQvNKAcl0My4yfopab/+/tCjGjB0zDWfE1C6tFr9pa22fLVRyYd+VFjt83cZO3b0iLZ+/aXuaNNePj4+bvscAMx19PgplbMFqF/UXzRt0SadPnNWklQ9pLyiu7TSpm37lXrifHI79bkealK/hqYt2qhn31pVnGUDBRHZGmZKY1u7dm2tW7dOBw4cUIUKFVStWjXZ7XbNnz9f3333nVq0aKGpU6eqXj02uYarwz//pI2frlUZm011bo7Qxs/WuZwTXq/BFc9p37GTJOnxJ0dq184EjRsxQH9/6FH5+vnpwxWL5e9fSn1iXGd2AZRso15drmVxMdo4/ym9u+ob2cqU0pMPt1VuXr5GvrpM0vn0tlfnVjp5Okv/3f+rHrm/hct1LnfXMgCewbSNY/39/XXrrbcWeB4TE2PW26ME2/Xf8/tMnsnM1NTJEwo9Z/Do8Vc850JjG1K1mt56Z6HefWeqVn2wQA6HdEujpuo3aJRCb6ruhk8AoDh9tOkHdR81S8/0u1cTRzyg7Jxz+iohSS/880Md+Pn8TRvuanazJKl82UD93z96F3odGlsUF26pa5zF4XB4xWZ8SanZxV0CgBKg0X1PF3cJAEqI7J3TirsESdLWg6fcev1Wdcu59fpm4lZfAAAAHszLduRyK1N2RQAAAADcjcQWAADAgxHYGkdiCwAAAK9gemPboEEDnThxwmX9t99+4wYNAAAAf2Zx88OLmN7YDhkyRIGF3K40MDBQQ4YMMbscAAAAeAm2+wJwQ2G7LwBGecp2XwmHMtx6/ea1g9x6fTOZ8uOxw4cPq3r16rJYLDp8+PBlz61Ro4YZJQEAAMDLmNLYduzYUZs3b1alSpV0zz33yFLIhmwOh0MWi0WJiYlmlAQAAFAisI+tcaY0tgsWLFC5cufvavHee++Z8ZYAAAC4wZjS2LZs2bLQP19w/PhxVa5cudAkFwAA4EZGd2Sc6bsinDp1Ss8995z2798vh8OhmJgYRUZG6r777rvi/C0AAABwKaY3tpMnT1ZCQoJ8fX31ySefaMuWLXrzzTdVp04dvfrqq2aXAwAA4NnYx9Yw02+p++WXX2rGjBmqW7euZs+erTvvvFOdOnVSvXr19Oijj5pdDgAAALyE6Yltdna2qlatKkn65ptvdOedd0qS/P39lZeXZ3Y5AAAAHs3i5v/xJqY3tnXr1tWmTZu0ceNGHT9+XJGRkZKk5cuXKzw83OxyAAAAYFBqaqqeeuoptWrVSk2bNlVMTIySkpKcxxMTE9W7d281adJE7dq109y5cwu8Pj8/X/Hx8brrrrvUuHFj9evXT8nJyUVWn+mN7fDhwzVp0iQNHjxYnTt3Vq1atfTKK69o/vz53FIXAADgTywW9z6McjgcGjBggI4dO6a5c+dqxYoVCggIUN++fXXmzBmlp6erb9++CgsL08qVKzVixAjFx8dr2bJlzmtMnz5dS5Ys0cSJE7V06VL5+Piof//+ysnJKZLvyvQZ20aNGunLL79UWlqa6tevL0m677771KNHDxJbAACAP/GUYYHffvtNdevW1fDhw1W7dm1J0uDBg/XAAw/owIED2rp1q/z8/BQbGytfX1/VrVtXycnJmj17tnr06CG73a558+ZpzJgxatu2rSQpLi5Obdq00fr169W1a9frrtH0xLZbt246evSos6mVpNtvv52mFgAAwIMFBwcrLi7O2dT+9ttvmjt3rqpUqaJ69eopISFBzZs3l6/vH7lpq1atdPjwYaWmpioxMVFZWVm64447nMdtNpsaNmyohISEIqnR9MTWbrcrICDA7LcFAAAomdwc2WZkZCgjI8NlPSgoSEFBQYW+ZuzYsVq9erX8/f01c+ZMlSlTRqmpqS5BZZUqVSRJKSkpSktLkySFhIS4nJOSklIUH8X8xrZ3794aMmSIevbsqbCwMJcmt3Xr1maXBAAAcMNasGCBpk2b5rI+dOhQDRs2rNDX9O/fX7169dLixYs1ZMgQLVq0SGfPnpW/v3+B8y48z8nJUXZ2doG1i8+x2+1F8VHMb2zj4uIkqdCbMVgsFiUmJppdEgAAgMdy95Zcffr0UVRUlMv6pdJaSbr55pslSZMmTdJ///tfLVy4UAEBAS4N6oXngYGBzjDTbrcXaG7tdrsCAwOv+3NIxdDYbtiwwey3BAAAwCVcbuTgYmlpadq6das6d+4sy/+2U7BarQoPD1dqaqpCQ0Od4wYXv0aSQkND5XA4nGs2m63AOUX1WyvTG9tq1apd8lhWVpaJlQAAAHi+q9mSy51SUlI0ZswYVa1aVc2bN5cknTt3Tnv37lXbtm0VEhKiRYsWKTc31/kDsi1btqhWrVoKDg5WuXLlZLPZtG3bNtWpU0eSlJmZqb179xbZ3WdNb2zT09M1Y8YM7d+/X/n5+ZLO74tmt9t18OBB7dy50+ySAAAAcAW33XabWrVqpRdffFH/+Mc/FBQUpHfeeUcnT55U3759FRgYqDlz5mjcuHGKiYnR7t27NX/+fE2YMEHS+Vna6OhoxcXFqXLlyqpevbreeusthYSEqGPHjkVSo+nbfcXGxmrt2rUKCQnRzp07ddNNN+ns2bPavXu3Bg0aZHY5AAAAHs3i5odRVqtV//znP9WsWTONHDlS3bt316lTp7Ro0SLVqFFDlSpV0ty5c/XLL78oKipK8fHxGj16tB588EHnNYYPH67u3bvrxRdfVM+ePeVwODRnzhyXH5RdK4vjwsCDSVq2bKnXX39d7dq1U6dOnTRlyhRFRETohRdeUE5Ojl5//fVrum5SanYRVwrAGzW67+niLgFACZG903WngOKw+9dMt17/1uq2K59UQpie2GZlZSkiIkKSVKdOHecuCNHR0dq6davZ5QAAAHg2T4lsSwDTG9uQkBAdOXJEkhQWFqb/b+/Og6o67zCOP4C7YMVo3JKgMXgVQUVRFIkiRVJL0WjqgoapyaC4YbQookhjNBrBqsgSrGMk7hpFTauoU03jSIlat9jGFbe6l6pgXCio9A/GW28Ae10gN8fvJ3Nn4J7zvuc9h3j48fCel2PHjkmSqlWrpry8vIoeDgAAAAyiwgvbwMBARUVFad++ffLx8dGGDRu0efNmzZ8/Xy4uLhU9HAAAAJtmV87/GUmFr4owbtw43bt3T5cvX1ZwcLACAwMVGRkpJycnJSYmVvRwAAAAYBAV/vBYaXJzc+Xk5CQHB4en7oOHxwBYg4fHAFjLVh4eO3Lpdrn279aoZrn2X5EqZCpCbGysbt8u+4tSu3btZypqAQAAgAopbNetW6f8/HyL90JCQnT16tWKODwAAMBPZBX2HgAAFe5JREFUFosiWK9CCtvSZjscO3ZMBQUFFXF4AAAAvAAq/OExAAAAPAGjxarlqMKX+wIAAADKQ4UltnZ2/LgBAADwpIy21mx5qrDC9qOPPlLVqlXNnxcWFiouLk41atSw2C8+Pr6ihgQAAGDzyAatVyGFbYcOHXT9+nWL9zw9PZWXl8ef0QUAAMBzUSGF7bJlyyriMAAAAIZDYGs9Hh4DAACAIbDcFwAAgC0jsrUaiS0AAAAMgcQWAADAhrHcl/VIbAEAAGAIJLYAAAA2jHVsrUdiCwAAAEMgsQUAALBhBLbWI7EFAACAIZDYAgAA2DIiW6uR2AIAAMAQSGwBAABsGOvYWo/EFgAAAIZAYgsAAGDDWMfWeiS2AAAAMAQSWwAAABtGYGs9ElsAAAAYAoktAACALSOytRqFLQAAgA1juS/rMRUBAAAAhkBiCwAAYMNY7st6JLYAAAAwBBJbAAAAG0Zgaz0SWwAAABgCiS0AAIANY46t9UhsAQAAYAgktgAAADaNyNZaJLYAAAAwBBJbAAAAG8YcW+uR2AIAAMAQSGwBAABsGIGt9UhsAQAAYAgktgAAADaMObbWI7EFAACAIZDYAgAA2DA7ZtlajcQWAAAAhkBiCwAAYMsIbK1GYgsAAABDILEFAACwYQS21qOwBQAAsGEs92U9piIAAADAEEhsAQAAbBjLfVmPxBYAAACGQGILAABgywhsrUZiCwAAAEMgsQUAALBhBLbWI7EFAACAIZDYAgAA2DDWsbUeiS0AAAAMgcQWAADAhrGOrfVIbAEAAGAIJLYAAAA2jDm21iOxBQAAgCFQ2AIAAMAQKGwBAABgCMyxBQAAsGHMsbUeiS0AAAAMgcQWAADAhrGOrfVIbAEAAGAIJLYAAAA2jDm21iOxBQAAgCGQ2AIAANgwAlvrUdgCAADYMipbqzEVAQAAAIZAYgsAAGDDWO7LeiS2AAAAMAQSWwAAABvGcl/WI7EFAACAIZDYAgAA2DACW+uR2AIAAMAQSGwBAABsGZGt1UhsAQAAYAgktgAAADaMdWytR2ILAAAAQyCxBQAAsGGsY2s9u6KioqIfexAAAADAs2IqAgAAAAyBwhYAAACGQGELAAAAQ6CwBQAAgCFQ2AIAAMAQKGwBAABgCBS2AAAAMAQKWwAAABgChS0AAAAMgcIWFe7OnTtq166dvLy8dOfOnWfu78KFCzKZTMrKyipzn+joaIWEhDzzsR4qKCjQnDlz5OfnJ09PTw0aNEgHDhx4bv0DsBQaGiqTyVTqKyYmptyOu2fPHplMJp07d87qNqdPn9bQoUPl5eUlX19fTZkyRTdv3iy3MQL4n0o/9gDw4tm6dascHR1169Ytbd68Wf369Sv3Y8bExOj+/fvPrb+UlBSlp6crLi5Or776qhYtWqSwsDBt2bJF9evXf27HAfA/b731lmJjY0u8X7169XI7pqenpzIzM1WnTh2r9i8oKNCwYcPk6uqqNWvW6MaNG4qJidHkyZOVnJxcbuMEUIzEFhVu3bp16tKli7p27apVq1ZVyDGdnJxUu3bt59bfjh071KtXL7355ptq0qSJoqOjdfv2be3fv/+5HQOApSpVqqhevXolXo6OjuV+TAcHB6v2P378uM6fP6+xY8eqWbNm8vLy0uDBg7Vr165yGyOA/6GwRYU6e/as9u/fLx8fH/Xs2VPfffedDh8+bN4eGhqqmJgYDRgwQO3bt9fatWtVUFCguLg4+fv7y93dXR06dNCYMWN07do1i74PHTqkXr16yd3dXX379tW3335r3vbDqQjnz59XRESEvLy81LFjR0VEROjKlSuS/je1Yf369WWeR506dfSXv/xFFy5c0P3797V27VpVqVJFbm5uz+tSAXhC/+9e8fDf9oIFC+Tr6ys/Pz9dv35dO3fuVN++fdWmTRt16tRJEydOVG5urqSSUxGSkpJkMpnKHIOzs7Ps7OzM967r16/rz3/+s9q2bVv+FwAAhS0q1rp161S1alV1795dfn5+qlmzZonUNj09XQMGDNCaNWvk7++v+Ph4bd26VZ988om2bdumuLg47dmzRykpKRbt0tLSNHz4cH355Zdyc3PTu+++q4sXL5YYw/fff6/Bgwfr1q1bSktL09KlS3X9+nUNHz5cktSwYUNlZmbql7/8ZZnnERsbq0qVKunnP/+5PDw8NGfOHM2bN09NmjR59osE4KlYe69IT0/X4sWLlZiYKEkaNWqU3nnnHWVkZCglJUX79u3TrFmzSj3G+++/r8zMzDLH8Morr2jKlClKT09XmzZt1LlzZ924cUPz5s17ficKoEzMsUWFuX//vjZu3Khu3bqZf3UYEBCgjIwMRUdH62c/+5kkydXVVX379jW38/DwUGBgoDp27ChJaty4sXx9fXXixAmL/keNGmUuRqdOnaqsrCytXLlSEyZMsNhv8+bNysvL09y5c+Xs7CxJmjFjhr744gvdunVLjo6Oqlev3mPP5eTJk3J0dFRKSorq16+vtWvXKioqSsuWLVOrVq2e4SoBKMuWLVu0Y8cOi/dMJpNWr14tyfp7RUhIiJo3by5JOnr0qAoLC9WgQQM1btxYjRs31oIFC8qck1+zZk3VrFmzzDEWFBTo6NGjCggIUGhoqHJzcxUXF6cPPvhAaWlpqlSJb7tAeeJfGCrMzp07lZOTY5GEBgUF6csvv9SGDRs0ZMgQSZKLi4tFu169eikrK0uzZ8/WuXPndPr0aZ05c6bEr/batWtn/rhSpUpyc3NTdnZ2iXGcOHFCr732mrmolaQmTZooKirKqvO4dOmSoqKitGjRInXq1ElS8TfU7OxsJSYm6g9/+INV/QB4Mt26ddPEiRMt3qtSpYr5Y2vvFY/eY1q2bKlf/epXGjlypOrVqycfHx/5+fnpF7/4xVON8fPPP9fevXu1ZcsWcxHr4uKiwMBAbd++/an7BWAdpiKgwqSnp0uSIiMj5ebmJjc3N40YMUKSzImLJFWrVs2i3e9+9zuNGzdOhYWF8vf319y5cxUUFFSif3t7y/+d79+/b/FN76HKlSs/03kcPnxYhYWF8vDwsHi/TZs2Onv27DP1DaBsNWrUkIuLi8WrYcOG5u3W3it+uIrCnDlztGXLFoWFhSkvL08TJ07UsGHDVFRU9MRj3L9/v1q2bGmRzLq4uMjZ2fmJlgwD8HRIbFEhrl27pp07d6p3794KCwuz2LZu3TotWbJEu3fvLtHuxo0b+uKLLzR79mz16tXL/P7p06dLFK1Hjx6Vu7u7pOJfB/7jH/8odSmxZs2aafXq1crLyzNPfzhz5oz69++vVatW6Y033njsuTRo0EBS8dPPj6bEJ06cUNOmTR/bFkD5eJJ7xaP279+vrVu3KiYmRq+//rqGDBmiTZs2KTIyUv/617+eeBz169fX3r179eDBA/MP21evXlVubi5z8IEKQGKLCrFx40YVFhZq6NChat68ucUrPDxcVatWLXXpLycnJzk5Oemrr77S2bNndfz4ccXGxuq7775TQUGBxb5z587V9u3blZ2drUmTJik/P1/vvvtuiT6Dg4Pl7OysCRMm6OjRozpy5IhiYmLk4uKiZs2a6f79+8rJyVF+fn6p59K6dWu1b99ekydP1u7du3X27FklJCQoKytLw4YNez4XDMATeZJ7xaNq1aqlVatWafbs2Tp79qxOnjypTZs26dVXX1XdunVL7H/79m3l5OSU2d/gwYN18eJFxcbG6tSpUzp06JDGjBkjV1dXde/e/bmcK4CyUdiiQqSnp8vb21uurq4ltr300kvq3bu3duzYUeIbRqVKlTR//nydOnVKvXr1UlhYmO7evavf/va3On36tG7dumXed/To0ZozZ47efvttXbx4UYsXLy51UfXq1avrs88+kyQNGjRI7733nho2bKjU1FTZ2dnp8uXL8vX1VUZGRqnnYm9vr9TUVHXu3FmTJk1Snz59tHv3bqWlpVkkuAAqzpPcKx7l6uqqpKQk7dmzR3369NHAgQNlZ2enzz77rNS1axcvXixfX98yx2EymbRs2TKdP39eAwcO1OjRo9W0aVN9/vnnj02OATwfdkVPM4kIAAAAsDEktgAAADAEClsAAAAYAoUtAAAADIHCFgAAAIZAYQsAAABDoLAF8JPBIi4AgMehsAVeEKGhoTKZTBYvd3d3+fv7a+rUqcrNzS23Y1+4cEEmk0lr166VJO3Zs0cmk0lZWVlW97F27VrNnDnzuYwnKSlJJpNJ9+7dK3Mff39/eXp66vz586Vu79q1q6Kjo5/LeP6fp7leAPAi4k/qAi+Q5s2b68MPPzR/XlhYqCNHjighIUHHjh3TqlWrZGdnV+7jcHNz04oVK2Qymaxuk5qaWuF/AOPOnTuaPHmyli5dWiHXBQDwbChsgReIo6OjvLy8LN7r3Lmz8vPzlZiYqG+//VZt27Yt93E4OTmVGIctqlWrlvbu3aulS5fqN7/5zY89HADA/8FUBAByd3eXJF26dElS8bSFqKgoRUZGytPTUwMGDJAkFRQU6Pe//738/Pzk7u6uoKAgbdiwoUR/69atU8+ePdW6dWv169dP2dnZFttL+9X63//+d4WFhal9+/by9vZWRESEeRqAyWTSxYsX9ac//cki5c3Oztbw4cPVrl07eXp6Kjw8XKdPn7Y41vfff6/Y2Fh16tRJ7dq109SpU1VQUGDVdenWrZu6dOmiuXPn6syZM4/d19/fX+PHj7d4LysrSyaTSXv27JEkrV+/Xm5ubjp48KD69esnDw8PBQYGavv27frnP/+psLAwtW3bVn5+flqyZEmJY5w5c0ahoaHy8PBQQEBAqfukp6crODhY7u7u6tq1q+bMmWNxvklJSerRo4cWLlwob29v+fj46MqVK1ZdDwCwdRS2AMxF22uvvWZ+LyMjQ//5z3+UlJSk8PBwSVJERISWL1+ukJAQpaSkyMvLS9HR0VqxYoW53erVqxUTEyMvLy8lJSWpa9euGjdu3GOPf+zYMQ0aNEi5ubmaPn26pk2bplOnTum9997T3bt3tWLFCtWrV0++vr7mY507d04DBw7UpUuXNH36dH388ce6evWqQkJCdPnyZUnFD5sNHTpU27ZtU0REhOLj43X+/HmlpaVZfW1mzJihypUra9KkSXrw4IHV7cry4MEDffDBB+rTp4+Sk5NVrVo1TZgwQWFhYWrXrp0SEhLUokULzZw5U4cOHbJo+8knn6hFixZKSkpSly5dNHPmTK1cudK8fdGiRZo8ebI8PT2VkpKi0NBQLV26VBMmTLDo5/Lly9q4caPi4+M1fvx4NWjQ4JnPCwBsAVMRgBfMow9M5eXl6W9/+5tSU1Pl6empVq1ambcVFRVp1qxZcnR0lFScPn799deKi4vT22+/Lak40Xzw4IESEhL0zjvvqGrVqkpOTpa/v7+mT59u3sfBwUHz588vc0wLFiyQo6OjlixZopo1a0qSXn/9dQ0dOlSHDx+Wt7e3qlSpImdnZ/MUhqSkJDk4OGjp0qWqXbu2pOIHunr06KHU1FRNmzZNmZmZOnjwoJKTk9WjRw9JUvfu3RUUFPR/E9iHGjZsqOjoaMXExGjx4sUKCwuzql1ZioqKFBYWpkGDBkkqTpQjIyPVo0cPjRw5UpLUunVrde7cWQcOHLCYGtKnTx/FxMRIkvz8/JSTk6NPP/1U/fv3V35+vpKTk9W3b19NmzZNUvG1b9CggcaPH6+DBw/K09NTUvHc6okTJ6pbt27PdC4AYGtIbIEXyIEDB9SqVSvzy8fHR+PGjZO7u7vmzZtn8YBUo0aNzEWtJH3zzTeSin/lfu/ePfMrICBAN2/e1OHDh3XmzBnl5OSYi8iHgoODHzuuffv26c033zQXtZLk6uqqr7/+Wt7e3qW22b17t7y9veXo6GgeS/Xq1eXj46PMzExJ0t69e+Xg4KDu3bub2zk4OKhnz55WXrFiv/71r+Xn56f58+eXmFbxNNq3b2/+uF69epJkLjolydnZWVLxDx6PCgoKsvg8MDBQOTk5ys7O1sGDB3X37l0FBARYfH26d+8ue3t7/fWvf7Vo+yQP7gHATwWJLfACadGihT7++GNJkp2dnapWrapGjRpZFJQP1a1b1+LzGzduSJI6dOhQat9Xr15VpUrFt5Q6depYbHv55ZcfO64bN27opZdesu4kHmmzbds2i5T5ocqVK0uScnNzVatWLfO4rB1PaaZNm6bg4GBNnDhRa9aseeL2jyrteteoUcP8cVkrMDwsgh96eM1u3rxp/vo8TH1/6OrVqxaf//DrCwBGQGELvEBq1KghDw+Pp2rr5OSkatWqafny5aVuf+WVV8wJY05OjsW2h0XX4/oubZ9du3apWbNmatSoUaltvL29Hzs1oE6dOsrLy1NhYaG52LVmPKWpX7++YmJiFBUVpYULF5a6zw/n4N66davU/Z526bAfrjX873//W1JxgXvnzh1JUlxcnJo1a1ai7cMUGACMjKkIAKzi7e2t/Px8FRYWysPDw/w6d+6cEhISdPfuXTVp0kSNGzdWRkaGRdvt27c/tm8vLy/t2rVL+fn55vfOnTunsLAw84oC9vaWt6uOHTsqOztbLVq0sBjPsmXLtGnTJkmSj4+PHjx4oC1btli03bFjx1Ndg969eysgIECffvppiWkCjo6O5lUlHtq7d+9THacsX331lcXnmzZt0ssvv6ymTZuqTZs2qlKliq5cuWJxPRwdHRUXF6dTp04917EAgC0isQVgla5du6pjx44aPXq0wsPD5erqqiNHjig5OVmenp7mVHXChAkaN26cIiMjFRwcrJMnT2rRokWP7XvkyJEaMGCA3n//fQ0ZMkT37t1TSkqK3njjDb311luSiteUPX78uL755ht5e3tr9OjR5jaDBw9W9erVlZ6erm3btik+Pl5ScTHu5+enDz/8UNeuXVPTpk21fv36ZyryPvroIwUFBZVIT/39/ZWamqrExER5eXlp9+7d2rp161MfpzSrV682p+4ZGRnKzMzUrFmzZG9vL2dnZw0dOlTJycm6efOmOnfurGvXrik5OVn5+fnmJd0AwMhIbAFYxd7eXgsXLlTv3r2VlpamYcOGaeXKlQoJCVFycrJ5v549e2r+/Pk6efKkIiIi9Mc//lGzZ89+bN9ubm5avny5KleurKioKE2fPl0tW7bU4sWLzXNPw8PDlZOTo5EjR+rSpUtq3ry5Vq5cqRo1amjy5MkaO3asLl26pISEBPXu3dvcd2Jiovr3769FixZp7Nixsre314gRI576OtStW9fir7c9FB4erpCQEK1YsUKjRo3SyZMnlZiY+NTHKc2MGTO0c+dOjRw5UocOHdLs2bPVp08f8/YxY8ZoypQp2rVrl0aMGKH4+Hh5eHho5cqVTzyHGQB+iuyKioqKfuxBAAAAAM+KxBYAAACGQGELAAAAQ6CwBQAAgCFQ2AIAAMAQKGwBAABgCBS2AAAAMAQKWwAAABgChS0AAAAMgcIWAAAAhvBfUN3vtuoeR8wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 8\n",
    "language1 = 'Arabic'\n",
    "number2 = 8\n",
    "language2 = 'Farsi'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 0\n",
    "language1 = 'Telugu'\n",
    "number2 = 1\n",
    "language2 = 'Telugu'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 1\n",
    "language1 = 'Devanagari'\n",
    "number2 = 9\n",
    "language2 = 'Urdu'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "number1 = 0\n",
    "language1 = 'Bangla'\n",
    "number2 = 0\n",
    "language2 = 'Tibetan'\n",
    "plot_confusion_matrix(number1, language1, number2, language2, languages, y_true, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we want to make a visualization of these pairs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we get the images from the training set\n",
    "def get_image_to_plot(input_train_test_fn, pairs):\n",
    "    image_to_plot_line1 = []\n",
    "    image_to_plot_line2 = []\n",
    "    \n",
    "    data = np.load(input_train_test_fn)\n",
    "    X_train, X_test, y_train, y_test = data['X_train'], data['X_test'], data['y_train'], data['y_test']\n",
    "    \n",
    "    for pair in pairs:\n",
    "        number1, language1, number2, language2, _ = pair\n",
    "        index1 = languages.index(language1) * 10 + number1\n",
    "        index2 = languages.index(language2) * 10 + number2\n",
    "        \n",
    "        # find two images to plot\n",
    "        \n",
    "        for (i, j) in zip(X_train, y_train):\n",
    "            if j == index1:\n",
    "                image_to_plot_line1.append(i)\n",
    "                break\n",
    "        for (i, j) in zip(X_train, y_train):\n",
    "            if j == index2:\n",
    "                image_to_plot_line2.append(i)\n",
    "                break\n",
    "    return [image_to_plot_line1, image_to_plot_line2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pairs = results[:10]\n",
    "input_train_test_fn = './data/MNIST_MIX_train_test.npz'\n",
    "image_to_plot = get_image_to_plot(input_train_test_fn, pairs)\n",
    "len(image_to_plot[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 10, figsize=[12, 3])\n",
    "# plt.subplots_adjust(wspace=0, hspace=0)\n",
    "for i in range(2):\n",
    "    for j in range(10):\n",
    "        axes[i, j].imshow(255 - image_to_plot[i][j], cmap=plt.cm.gray)\n",
    "        axes[i, j].axis('off')\n",
    "plt.savefig('difficult_pairs.pdf', dpi=400, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}