diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..ff0e467
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,4 @@
+*.mat
+*.zip
+*.csv
+*.psd filter=lfs diff=lfs merge=lfs -text
diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000..e29243e
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,3 @@
+{
+    "python.pythonPath": "C:\\Users\\bncha\\miniconda3\\python.exe"
+}
\ No newline at end of file
diff --git a/Segment/final-Copy1.ipynb b/Segment/final-Copy1.ipynb
index 73b2abf..a21020c 100644
--- a/Segment/final-Copy1.ipynb
+++ b/Segment/final-Copy1.ipynb
@@ -1492,4 +1492,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
\ No newline at end of file
diff --git a/checkpoint_cnn_best/checkpoint b/checkpoint_cnn_best/checkpoint
new file mode 100644
index 0000000..5be71fc
--- /dev/null
+++ b/checkpoint_cnn_best/checkpoint
@@ -0,0 +1,2 @@
+model_checkpoint_path: "checkpoint"
+all_model_checkpoint_paths: "checkpoint"
diff --git a/checkpoint_cnn_best/checkpoint.data-00000-of-00001 b/checkpoint_cnn_best/checkpoint.data-00000-of-00001
new file mode 100644
index 0000000..d807416
Binary files /dev/null and b/checkpoint_cnn_best/checkpoint.data-00000-of-00001 differ
diff --git a/checkpoint_cnn_best/checkpoint.index b/checkpoint_cnn_best/checkpoint.index
new file mode 100644
index 0000000..a4c46fd
Binary files /dev/null and b/checkpoint_cnn_best/checkpoint.index differ
diff --git a/no_0.png b/no_0.png
new file mode 100644
index 0000000..0423fc1
Binary files /dev/null and b/no_0.png differ
diff --git a/no_1.png b/no_1.png
new file mode 100644
index 0000000..7049265
Binary files /dev/null and b/no_1.png differ
diff --git a/no_3.png b/no_3.png
new file mode 100644
index 0000000..87af026
Binary files /dev/null and b/no_3.png differ
diff --git a/no_3_1.png b/no_3_1.png
new file mode 100644
index 0000000..4996bf0
Binary files /dev/null and b/no_3_1.png differ
diff --git a/no_5.png b/no_5.png
new file mode 100644
index 0000000..78ba984
Binary files /dev/null and b/no_5.png differ
diff --git a/number_recoginition_capstone.ipynb b/number_recoginition_capstone.ipynb
index 36f46fe..4808f15 100644
--- a/number_recoginition_capstone.ipynb
+++ b/number_recoginition_capstone.ipynb
@@ -26,25 +26,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {
     "colab": {},
     "colab_type": "code",
     "id": "O3vI8jSIz_Fs"
    },
-   "outputs": [
-    {
-     "output_type": "error",
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'tensorflow'",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-3-f8a1348d6492>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mtensorflow\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mtf\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mscipy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mio\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mloadmat\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'matplotlib'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'tensorflow'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import tensorflow as tf\n",
     "from scipy.io import loadmat\n",
@@ -57,30 +45,6 @@
     "import pandas as pd"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "output_type": "stream",
-     "name": "stdout",
-     "text": [
-      "Collecting scipy\n",
-      "  Downloading scipy-1.6.2-cp39-cp39-win_amd64.whl (32.7 MB)\n",
-      "Collecting numpy<1.23.0,>=1.16.5\n",
-      "  Downloading numpy-1.20.2-cp39-cp39-win_amd64.whl (13.7 MB)\n",
-      "Installing collected packages: numpy, scipy\n",
-      "  WARNING: Failed to write executable - trying to use .deleteme logic\n",
-      "ERROR: Could not install packages due to an OSError: [WinError 2] The system cannot find the file specified: 'c:\\\\python39\\\\Scripts\\\\f2py.exe' -> 'c:\\\\python39\\\\Scripts\\\\f2py.exe.deleteme'\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    " !pip install scipy"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -99,35 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 54
-    },
-    "colab_type": "code",
-    "id": "r8BHW8P_2wxw",
-    "outputId": "659d5ac1-f605-43c7-c114-d262c082e800"
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Run this cell to connect to your Drive folder\n",
-    "\n",
-    "from google.colab import drive\n",
-    "drive.mount('/content/gdrive')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": 3,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -137,8 +73,8 @@
    "source": [
     "# Load the dataset from your Drive folder\n",
     "\n",
-    "train = loadmat('/content/gdrive/My Drive/train_32x32.mat')\n",
-    "test = loadmat('/content/gdrive/My Drive/test_32x32.mat')"
+    "train = loadmat('C:/Users/bncha/Downloads/train_32x32.mat')\n",
+    "test = loadmat('C:/Users/bncha/Downloads/test_32x32.mat')"
    ]
   },
   {
@@ -167,7 +103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 6,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -209,7 +145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": 7,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -247,7 +183,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 8,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -260,14 +196,13 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1152x1152 with 10 Axes>"
       ]
      },
      "metadata": {
-      "needs_background": "light",
-      "tags": []
+      "needs_background": "light"
      },
      "output_type": "display_data"
     }
@@ -278,7 +213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": 11,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -295,7 +230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 7,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -307,15 +242,741 @@
    },
    "outputs": [
     {
-     "output_type": "error",
-     "ename": "NameError",
-     "evalue": "name 'plot_random_images' is not defined",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-3-2646c350119a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mplot_random_images\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgrayscale_train_images\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mtrain_labels\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;31mNameError\u001b[0m: name 'plot_random_images' is not defined"
-     ]
+     "data": {
+      "image/png": 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+      ],
+      "text/plain": [
+       "<Figure size 1152x1152 with 10 Axes>"
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    "source": [
@@ -342,7 +1003,7 @@
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   {
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-   "execution_count": 0,
+   "execution_count": 8,
    "metadata": {
     "colab": {},
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@@ -374,7 +1035,7 @@
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   {
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-   "execution_count": 136,
+   "execution_count": 9,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -389,21 +1050,21 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model: \"sequential_45\"\n",
+      "Model: \"sequential\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "dense_112 (Dense)            (None, 32, 32, 64)        128       \n",
+      "dense (Dense)                (None, 32, 32, 64)        128       \n",
       "_________________________________________________________________\n",
-      "dense_113 (Dense)            (None, 32, 32, 64)        4160      \n",
+      "dense_1 (Dense)              (None, 32, 32, 64)        4160      \n",
       "_________________________________________________________________\n",
-      "flatten_56 (Flatten)         (None, 65536)             0         \n",
+      "flatten (Flatten)            (None, 65536)             0         \n",
       "_________________________________________________________________\n",
-      "dense_114 (Dense)            (None, 128)               8388736   \n",
+      "dense_2 (Dense)              (None, 128)               8388736   \n",
       "_________________________________________________________________\n",
-      "dense_115 (Dense)            (None, 128)               16512     \n",
+      "dense_3 (Dense)              (None, 128)               16512     \n",
       "_________________________________________________________________\n",
-      "dense_116 (Dense)            (None, 11)                1419      \n",
+      "dense_4 (Dense)              (None, 11)                1419      \n",
       "=================================================================\n",
       "Total params: 8,410,955\n",
       "Trainable params: 8,410,955\n",
@@ -419,7 +1080,7 @@
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+   "execution_count": 10,
    "metadata": {
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@@ -435,45 +1096,45 @@
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      "text": [
       "Epoch 1/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 1.5435 - accuracy: 0.4757\n",
-      "Epoch 00001: val_accuracy improved from -inf to 0.66048, saving model to /content/checkpoint_mlp_best/checkpoint\n",
-      "1946/1946 [==============================] - 219s 112ms/step - loss: 1.5435 - accuracy: 0.4757 - val_loss: 1.0738 - val_accuracy: 0.6605\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 1.6253 - accuracy: 0.4408\n",
+      "Epoch 00001: val_accuracy improved from -inf to 0.65784, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 233s 120ms/step - loss: 1.6253 - accuracy: 0.4408 - val_loss: 1.1043 - val_accuracy: 0.6578\n",
       "Epoch 2/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.9566 - accuracy: 0.7035\n",
-      "Epoch 00002: val_accuracy improved from 0.66048 to 0.71426, saving model to /content/checkpoint_mlp_best/checkpoint\n",
-      "1946/1946 [==============================] - 219s 113ms/step - loss: 0.9566 - accuracy: 0.7035 - val_loss: 0.9218 - val_accuracy: 0.7143\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 1.0069 - accuracy: 0.6870\n",
+      "Epoch 00002: val_accuracy improved from 0.65784 to 0.70907, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 244s 126ms/step - loss: 1.0069 - accuracy: 0.6870 - val_loss: 0.9389 - val_accuracy: 0.7091\n",
       "Epoch 3/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.8506 - accuracy: 0.7385\n",
-      "Epoch 00003: val_accuracy improved from 0.71426 to 0.73628, saving model to /content/checkpoint_mlp_best/checkpoint\n",
-      "1946/1946 [==============================] - 220s 113ms/step - loss: 0.8506 - accuracy: 0.7385 - val_loss: 0.8617 - val_accuracy: 0.7363\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.8827 - accuracy: 0.7282\n",
+      "Epoch 00003: val_accuracy improved from 0.70907 to 0.73164, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 254s 131ms/step - loss: 0.8827 - accuracy: 0.7282 - val_loss: 0.8736 - val_accuracy: 0.7316\n",
       "Epoch 4/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.7865 - accuracy: 0.7589\n",
-      "Epoch 00004: val_accuracy improved from 0.73628 to 0.74747, saving model to /content/checkpoint_mlp_best/checkpoint\n",
-      "1946/1946 [==============================] - 222s 114ms/step - loss: 0.7865 - accuracy: 0.7589 - val_loss: 0.8228 - val_accuracy: 0.7475\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.8145 - accuracy: 0.7509\n",
+      "Epoch 00004: val_accuracy improved from 0.73164 to 0.73655, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 250s 128ms/step - loss: 0.8145 - accuracy: 0.7509 - val_loss: 0.8578 - val_accuracy: 0.7366\n",
       "Epoch 5/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.7446 - accuracy: 0.7732\n",
-      "Epoch 00005: val_accuracy improved from 0.74747 to 0.76376, saving model to /content/checkpoint_mlp_best/checkpoint\n",
-      "1946/1946 [==============================] - 221s 114ms/step - loss: 0.7446 - accuracy: 0.7732 - val_loss: 0.7744 - val_accuracy: 0.7638\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.7623 - accuracy: 0.7660\n",
+      "Epoch 00005: val_accuracy improved from 0.73655 to 0.75312, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 259s 133ms/step - loss: 0.7623 - accuracy: 0.7660 - val_loss: 0.8117 - val_accuracy: 0.7531\n",
       "Epoch 6/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.7051 - accuracy: 0.7849\n",
-      "Epoch 00006: val_accuracy did not improve from 0.76376\n",
-      "1946/1946 [==============================] - 222s 114ms/step - loss: 0.7051 - accuracy: 0.7849 - val_loss: 0.7801 - val_accuracy: 0.7618\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.7200 - accuracy: 0.7816\n",
+      "Epoch 00006: val_accuracy improved from 0.75312 to 0.76349, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 253s 130ms/step - loss: 0.7200 - accuracy: 0.7816 - val_loss: 0.7769 - val_accuracy: 0.7635\n",
       "Epoch 7/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.6750 - accuracy: 0.7943\n",
-      "Epoch 00007: val_accuracy improved from 0.76376 to 0.77013, saving model to /content/checkpoint_mlp_best/checkpoint\n",
-      "1946/1946 [==============================] - 222s 114ms/step - loss: 0.6750 - accuracy: 0.7943 - val_loss: 0.7652 - val_accuracy: 0.7701\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.6870 - accuracy: 0.7912\n",
+      "Epoch 00007: val_accuracy did not improve from 0.76349\n",
+      "1946/1946 [==============================] - 254s 131ms/step - loss: 0.6870 - accuracy: 0.7912 - val_loss: 0.7934 - val_accuracy: 0.7590\n",
       "Epoch 8/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.6491 - accuracy: 0.8014\n",
-      "Epoch 00008: val_accuracy improved from 0.77013 to 0.78342, saving model to /content/checkpoint_mlp_best/checkpoint\n",
-      "1946/1946 [==============================] - 224s 115ms/step - loss: 0.6491 - accuracy: 0.8014 - val_loss: 0.7330 - val_accuracy: 0.7834\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.6575 - accuracy: 0.7998\n",
+      "Epoch 00008: val_accuracy improved from 0.76349 to 0.77923, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 253s 130ms/step - loss: 0.6575 - accuracy: 0.7998 - val_loss: 0.7486 - val_accuracy: 0.7792\n",
       "Epoch 9/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.6253 - accuracy: 0.8097\n",
-      "Epoch 00009: val_accuracy did not improve from 0.78342\n",
-      "1946/1946 [==============================] - 222s 114ms/step - loss: 0.6253 - accuracy: 0.8097 - val_loss: 0.7432 - val_accuracy: 0.7759\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.6316 - accuracy: 0.8075\n",
+      "Epoch 00009: val_accuracy improved from 0.77923 to 0.78606, saving model to /content/checkpoint_mlp_best\\checkpoint\n",
+      "1946/1946 [==============================] - 270s 139ms/step - loss: 0.6316 - accuracy: 0.8075 - val_loss: 0.7351 - val_accuracy: 0.7861\n",
       "Epoch 10/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.6064 - accuracy: 0.8137\n",
-      "Epoch 00010: val_accuracy did not improve from 0.78342\n",
-      "1946/1946 [==============================] - 222s 114ms/step - loss: 0.6064 - accuracy: 0.8137 - val_loss: 0.7791 - val_accuracy: 0.7649\n"
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.6104 - accuracy: 0.8145\n",
+      "Epoch 00010: val_accuracy did not improve from 0.78606\n",
+      "1946/1946 [==============================] - 248s 127ms/step - loss: 0.6104 - accuracy: 0.8145 - val_loss: 0.7439 - val_accuracy: 0.7826\n"
      ]
     }
    ],
@@ -493,7 +1154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 11,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -506,14 +1167,1015 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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   },
   {
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+   "execution_count": 12,
    "metadata": {
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@@ -548,14 +2210,902 @@
    "outputs": [
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EJHr4FgTOuRHOuVznXC7wFPCPzrnn/KoHoHB0NnWNTSzbVu5nGSIip1U4Tx99HHgXGGNmJWZ2s5ndambhnzijm6bnZtInLoZ3NE4gIlEknGcNnfheb0e3XRCuOk5GUp9YpudmasBYRKKKrixupzA/wKY9VezRdBMiEiUUBO0037VMrQIRiRYKgnbGDkwlkKLpJkQkeigI2omJMc4ZFeCdzd50EyIivZ2CoAOF+dmUH6pjw+5Kv0sREQk7BUEHNN2EiEQTBUEH+qclMnagppsQkeigIOhEYX6AlcUHqKlr8LsUEZGwUhB0ojC/ebqJ/X6XIiISVgqCTkwf4U03sfhjjROISO+mIOhEYnwsM0ZkapxARHo9BcFxFOYH2Ly3mt0Vh/0uRUQkbBQEx9E83YRmIxWR3kxBcBzedBMJup5ARHo1BcFxmBlz8gO8U6TpJkSk91IQnEDh6AD7Nd2EiPRiCoITmD3Km25ikc4eEpFeSkFwAv1Tg9NN6HoCEemlFARdMGd0Niu379d0EyLSKykIuqAwP0B9o2PZVk03ISK9j4KgC87KzSQhLkbjBCLSKykIuiAxPpbpIzJ1PYGI9EoKgi6ak59N0d5qSg9qugkR6V0UBF1UONo7jVTTTYhIb6Mg6KIxA1LJTk3QOIGI9DoKgi4yMwqD0000aroJEelFFAQnYU5+Ngdr6llfWuF3KSIiIaMgOAnN003o7CER6U0UBCchOzWBcYPSdNcyEelVFAQnqXB0gFXbD3DoiKabEJHeQUFwkubkZ3vTTWwr97sUEZGQUBCcpGnD+3nTTWg2UhHpJRQEJykxPpYZeVkaJxCRXkNB0A1z8gNs2XeIXZpuQkR6gbAFgZk9ZGZ7zezDTtZfZ2YfmNk6M1tqZpPCVUuoFeZnA/COWgUi0guEs0XwCDDvOOu3AZ9yzk0Afgr8Poy1hNToASn0T01gka4nEJFeIGxB4JxbBHR6Jxfn3FLn3IHgn+8BQ8JVS6h5001ks0TTTYhIL9BTxghuBl7ubKWZ3WJmK81s5b59PaM7Zs7oAAdr6vlwl6abEJHI5nsQmNm5eEHw3c62cc793jlX4JwryM7OPn3FHcfR6SZ6RjCJiHSXr0FgZhOBB4FLnHMRdYVWICWB8TlpGicQkYjnWxCY2TDgGeB659zHftVxKgrzs1m9/QDVmm5CRCJYOE8ffRx4FxhjZiVmdrOZ3WpmtwY3+RGQBdxvZmvMbGW4agmXOfkBGpocy7ZGVGNGRKSNuHDt2Dk3/wTrvwx8OVyvfzpMy+1HYnwMizeXcd4ZA/wuR0SkW3wfLI5kCXGxzMzL0u0rRSSiKQhOUWF+Nlv3HaLkQI3fpYiIdIuC4BQV5nunkb6js4dEJEIpCE5Rfv8UBqQl6PaVIhKxFASnqHm6iXc03YSIRCgFQQgU5geoOFzPOk03ISIRSEEQAuc0Tzfxsc4eEpHIoyAIgayUBM4cnKZxAhGJSAqCECnMz2b1jgNU1db7XYqIyElREIRIYXC6ife2dnoLBhGRHklBECLThvcjKT5W01KLSMRREISIN91EpsYJRCTidCkIzCzZzGKCv482s4vNLD68pUWewvxstpUdYud+TTchIpGjqy2CRUCimQ0GXgOux7s5vbQyZ3RwuokitQpEJHJ0NQjMOVcDXAbc75y7EhgfvrIi08jsFAalJ2qcQEQiSpeDwMzOBq4DXgwuiw1PSZHLm24iwDubNd2EiESOrgbBt4A7gWedc+vNLA94K3xlRa7C/Gwqaxv4oOSg36WIiHRJl+5Q5pz7O/B3gOCgcZlz7hvhLCxSzR4VwAwWby5jyrB+fpcjInJCXT1r6DEzSzOzZOBDYIOZ3RHe0iJTZnIfzsxJ1ziBiESMrnYNjXPOVQKXAi8DI/DOHIocR6rg77+Exoawv1RhfoDVOw5qugkRiQhdDYL44HUDlwLPO+fqgcgaDd34Irz1M3hqATQcCetLFeZn09jkeHdLeVhfR0QkFLoaBP8PKAaSgUVmNhyoDFdRYTHpGjj/X+GjF2DhtVAXvou+pg7PoG+fWF1lLCIRoUtB4Jz7jXNusHPuQufZDpwb5tpC7+x/hC/8BoregEevgNrwZJk33USWxglEJCJ0dbA43cx+ZWYrg4//wGsdRJ5pN8LlD8LOZfA/l0BNeGYLLcwPUFxew45yTTchIj1bV7uGHgKqgKuCj0rg4XAVFXYTroCr/wx71sMjn4eqPSF/icL8bAAWF6lVICI9W1eDYKRz7m7n3Nbg48dAXjgLC7sxF8B1T8KBYnh4HhzcGdLdj8xOJic9kcUfa5xARHq2rgbBYTM7p/kPM5sNHA5PSadR3ly4/jk4VA4PXwDlW0K2a2+6iWyWbCmjobEpZPsVEQm1rgbBrcBvzazYzIqB/wK+GraqTqdhM2DBC1BfAw/N87qLQqRwdICq2gbWllSEbJ8iIqHW1bOG1jrnJgETgYnOuSnAp8Na2ek0aBJ86WWIifXGDHatCsluZ4/0ppt4R6eRikgPdlJ3KHPOVQavMAb45zDU45/sMV4YJKTBHy+B4iWnvMt+yX2YOFjTTYhIz3Yqt6q0kFXRU2SOgJtegbRB8OfLYfPrp7zLwvxs3t95kEpNNyEiPdSpBEFkTTHRVWk5XssgMAoevwY2/PWUdndOfkDTTYhIj3bcIDCzKjOr7OBRBeScphpPv+QA3Pg3yJkCf1kAax7v9q6mDusXnG5C3UMi0jMdNwicc6nOubQOHqnOuePey8DMHjKzvWb2YSfrzcx+Y2ZFZvaBmU09lQMJuaQMuP5ZyC2E526F5Q90azd94mI4Oy9L8w6JSI91Kl1DJ/IIMO846y8A8oOPW4DfhbGW7klIgWufhNEXwEvfhnfu69ZuCvMDbC+vYXv5oRAXKCJy6sIWBM65RcDxJvK5BPif4CR27wEZZjYoXPV0W3wiXP0nOPNyeP1ueOOn4E5ueKRwdHC6CbUKRKQHCmeL4EQGA63ndSgJLjuGmd3SPOHdvn0+9LXHxsNlD8DUG2DxvfDK96Cp61cL5wWSGZyRpHECEemR/AyCLnPO/d45V+CcK8jOzvaniJhYbwrrmf8Iy/4bXvg6NDV26anedBMBlhaVa7oJEelx/AyCXcDQVn8PCS7ruczg/P8Dc74D7/8Znr4ZGuq69NTC/GyqjjSwtuRgmIsUETk5fgbB88ANwbOHZgIVzrndPtbTNWbw6e/DZ38C65+FJ/4B6k88/97sUVmYwSLNRioiPUzYgsDMHgfeBcaYWYmZ3Wxmt5rZrcFNXgK2AkXAA8A/hquWsJj9Tfj8r2Dza/DolXCk+ribZ/Ttw8QhGRonEJEe57jXApwK59z8E6x3wNfC9fqnxVk3Q58UeO42+NOlcN1fIKlfp5vPyQ/w27eKqDhcT3pS/GksVESkcxExWNyjTboarvojlK6BR74A1Z1/4y/Mz6bJoekmRKRHURCEwhlfgGsXQnmRd4Obio7HvKcMyyBZ002ISA+jIAiVUZ+B65+Bqk+8W1/u33rMJvGxMZw9MsCbG/eyt6rWhyJFRI6lIAil4bPgxufhSBU8dAHs3XjMJv8wcxj7D9Xx2V8t4tn3S3AneZWyiEioKQhCbfBUWPAS4OCRC72xg1bmjunPS98sZFT/FG5/Yi1f/uNK9lSqdSAi/lEQhMOAcd49DeL7wh+/ADvea7N6ZHYKT371bH540TiWbCnjs7/6O39ZuVOtAxHxhYIgXLJGenc7S+kPf/oibHmrzerYGOPmc0bwyjfnMHZgGnc89QFfemQFpQdPfHGaiEgoKQjCKX2I1zLoNwIeuwo2vnjMJrmBZBbeMpMfXzyeZVv3c/5/LmLh8h1qHYjIaaMgCLeU/rDgbzBwAjxxPax76phNYmKMG2fl8uq35jB+cBrfe2YdNzy0nJIDNT4ULCLRRkFwOvTNhBv+CsPOhqe/DO/9d4eT1Q3L6stjX57JTy89k9XbD3D+fy7iz+9tp6lJrQMRCR+LtC6IgoICt3LlSr/L6J66GnjyBij6X+ibBROugsnXwqCJx2y6c38Ndz6zjneKyjg7L4tfXDGRoZl9fShaRHoDM1vlnCvocJ2C4DRraoSiN2DNo7DpJWisgwETvECYcCWkHL3fgnOOhSt28vMXP6LJOb47byzXzxxOTIz5eAAiEokUBD1VzX748GlY8xiUroaYOMg/3wuF/M9BXB8Adh08zJ3PrGPRx/uYPiKTX1w+kdxAss/Fi0gkURBEgr0feYHwwRNQveeYriPnHH9ZVcJP/7aB+sYm7jh/LAtm5RKr1oGIdIGCIJI0NsCWN9t1HZ0Z7Dq6ik8aU7nr2XW8uXEv04b34xdXTGRkdorfVYtID6cgiFQddh19DjdpPs/VnMk9LxZRW9/Iv3xuNDefk6fWgYh0SkHQG+zdCGsfg7ULva6jpExqxl7GvXsLeGhLKpOH9uPeKycyqn+q35WKSA+kIOhNGhtg61te19HGF6Gxjoq0MTxQNZOn6mdxw2cKuKUwj7hYXSIiIkcpCHqrmv2w/hmv62jXKhqJ5c3GyazImMfl19zMmMFZflcoIj2EgiAaBLuOalc9RmLtPva7FHYO/jzjLryN+MGTwTR+IBLNFATRpLGByvWvsfm1/8eZVe+QYA3UZo4lseB6mHiVN/eRiEQdBUGUemP1Ryz/2x+4oOFNJsdswVkslv8571TU0fNaLlgTkd5PQRDFDhyq454X1rN+7XJuSVvGF2MXE1+zF5Iy4YyLYPg5kDvbmzJbRHotBYHwvxv2cNez66g4dJh/nVTGpfY2sVvegiMV3gYZw2D4bO++y8NnQ2aexhVEehEFgQBwsKaOn/xtA8+s3sXoASn87OJxnNW3FNu+FLYvge1Loabc2zhlYDAUgsGQPRZidEqqSKRSEEgbb27cw13PfMgnlbWMHZjKdTOGccmUwaQlxEHZx0dDoXgJVJV6T0rqB8NmHQ2HgRMhNs7fAxGRLlMQyDGqjzTw1zW7eGzZDtaXVpIUH8sXJg1i/vRhTB6agZmBc3Cg2AuF5lbDgW3eDvqkwrAZR1sMOVMgLsHXYxKRzikI5Lg+KDnI48t38Nc1pdTUNbZtJSTGt924srRVMCyFfR95y+MSYchZR4NhyFnQRzfSEekpFATSJVW19Ty/tvT4rYT2DpXBjnePthg+WQeuyZsgL2fq0WAYNgMS00//QYkIoCCQbjipVkJrtRWwc7kXCsVLvFlTmxrAYrzptHPP8cJh2NmQHDh9ByQS5RQE0m3txxIS42P4wsQcrp1xnFZCa3U1ULLiaIuhZAU01Hrrssd6oZA3F0Z+GhI0c6pIuCgIJCTWlVTw2PLtbVoJ184YxqUnaiW01nAEStcEz0xaAjuWQV0VxPaB3EIYc4F31XPG0PAejEiUURBISJ1yK6G1xnrY8R58/Apsehn2b/GWD5gAY+bB6Au8M5J0DYPIKfEtCMxsHvBrIBZ40Dn3b+3WDwP+CGQEt/mec+6l4+1TQdCzdNZKuGTyYNKTuthKaK1ss3eLzk2vwM73vIHnlAEw+nwvFPLm6mwkkW7wJQjMLBb4GPgsUAKsAOY75za02ub3wPvOud+Z2TjgJedc7vH2qyDomTprJcyfMYwpJ9tKaFazHza/5rUUit7wupDiEr0wGD3Pe6QNCvWhiPRKxwuCcF4aOh0ocs5tDRaxELgE2NBqGwekBX9PB0rDWI+EUUpCHNfNGM51M4a3aSX8ZVVJ91sJfTNh0jXeo6HOG1PY9DJ8/LLXlQQwaDKMudDrRho4UfMjiXRDOFsEVwDznHNfDv59PTDDOfdPrbYZBLwG9AOSgc8451Z1sK9bgFsAhg0bNm379u1hqVlCq/pIA8+vKeWx5dv5cFeIWgngXfG89yMvEDa9DCUrAQdpg70upDEXegPP8YkhPR6RSOZX11BXguCfgzX8h5mdDfwBONM519TZftU1FJm8VsIOnl+zi0OhGEtorXofbH7VC4Utb0J9DcQnw8hzg11I5+uGPBL1/AqCs4F7nHPnB/++E8A596+ttlmPFxY7g39vBWY65/Z2tl8FQWTrqJUwd3R/Zo/KYtaoAHmB5O63FADqa6F4cbAL6RWo3AUYDCnwQmHMBdB/nLqQJOr4FQRxeIC/x2EAABB1SURBVIPF5wG78AaLr3XOrW+1zcvAE865R8zsDOANYLA7TlEKgt5jXUkFj6/Ywdsb91Ja4V1kNjAtkVmjspg9MsDsUQEGpp9C945z3pQXzeMKpe97yzOGeWcgjZnn3ZgnXHdqa2qE+sPeBXStf9YfhobDXmi1/9lU7900KGWA14pJGeBdgR17iq0miWwNR2D3Wu//jcCobu3Cz9NHLwTuwzs19CHn3M/N7CfASufc88EzhR4AUvAGjr/jnHvtePtUEPQ+zjmKy2tYUlTGu1vKWbqljAM19QDkZScHQyGLmXlZZPQ9hQ/tyt1eK+HjV2Dr294Hc59UGHWe132U1O84H9S1HX+oN9R6XVEdbdtUH5o3CPMGzluHQ0p/SO7fbtkA7xh0zUXkq9wNJcu96Vp2Lofda6CxDs7+Jzj/593apS4ok4jS1OT46JNKlhaVs2RLGcu37aemrhEzODMnnVmjspg1MsD03EyS+sR270XqamDb371rFj5+Far3dL6txUBckjf4fMzPRIhPOvHP+KSu7SMmDg7v98Y9qvcEH3u9n4faLWueqqO1mDhIzj5xYKRkQ0Kaush6gsZ6r+VasgJ2LoOdK6Bih7cuNsG7oHLoWTBkOgyb2e3xLgWBRLS6hibWlhxkSVEZS4vKeX/nAeobHfGxxpRh/VpaDJOGZhAf241vw01NsHeD942row/x2D497wPTOThSdTQkmsPh0N624VG9z1vW1HDsPuIS24ZDcvbRwEgbDIMmQuqgnnfske5QWfCb/jLvw3/Xaq81CZCaA0OnBx8zYOCEkN3nQ0EgvUpNXQPLt+1n6ZZylhSVsWF3Jc5Bcp9Ypo/IZPaoALNGBhg7MJWYGH2I0dQEhw8cDYz2LYuWx57grUpbfSYk9/e+keZM9n4OmqyL+E5GU6P3JaO5i6dkOezf6q2LiYNBk7xv+s0f/ulDwlaKgkB6tQOH6nh3qxcKS7eUs63sEACZyX04e2RWS4thWGbfUzsjKRo01nvfWA/u8PqlS9d4g+xlm7zpPsC7n3XrYMiZDKkD/a27pzh8wLuupfkb/65VUFftrUvO9r7lDznL+5kz2WtxniYKAokqpQcPs3RLOUuLyliypYw9lUcAGJyRxKyRWV6LYVQW/VN1wVmX1R3y+rGbg2H3Gti3iZbWQ+qgYCi0aj309ms3mpq8e3yXLD/at1+2yVvXfP+NodOPfuPvl+trN5uCQKKWc44t+w6xdEtZy1lJlbVef3l+/5RgN1IWM0dmdX0qbfEcqfbCYXcwHErXeB+MLeGQc2y3Ukq2ryWfktpK7xt+86BuyQrvRkzgna01ZLo3qDt0hnd3voQUf+ttR0EgEtTY5FhfWsGSIu801RXF+6mtbyLGYHxOOjPzMpkxIouzRmSe+hXP0ehIVbDl8P7R1kN5ES3hkDbEC4bWrQe/7lTX2OB9kNceDP5s/3sFHD7oLdu3yevrd02AeTdVaj2omzWqxw+qKwhEOnGkoZHV2w/y7pYy3tu6nzU7D1LX2IQZnDEwjRnBYJgxIpN+yWG68Ky3O1IFuz842qXUEg5B6UO9QdPmYBg0BZKzTrzfpiY4Utn2g7vDD/JO1jf33XfGYiEpw7vXdsZw7wN/6HTvKvUIvP+2gkCki2rrG3l/x0GWbStn2db9rN5xgCMN3iDpmAGpR4MhL5NASmhO64tKtRVeOLTuVmq+KRFA+jDImeSFRG1lqw/w1h/slbQ5w+kYBolp3od2YjokZrT7mX70g7798sR06JPc47/lnwwFgUg3HWlo5IOSCpZtLWfZtv2sLD7A4fpGAEZmJzMjz2stzMzLYkCaBp9PSW2FN41Cc5dS6fveqa6tP5yP+0Hebl1Cmq6ybkVBIBIi9Y1NrNtVwbKt+1m2rZyVxQeoPuINPudm9WVmXlZLqyEn4/SdGihyIgoCkTBpaGxiw+7KlmBYvm1/y1lJQzOTWsYXZuZlMaRfkq5jEN8oCEROk8Ymx8ZP2gZD8wR6OemJLV1JM/KyyM3SBW5y+igIRHzS1OTYvLe6ZfB52bZyyqrrABiQlsD0lhZDJiOzUxQMEjYKApEeovkCt9bB0HzlcyClD9NHZHLm4HTG56QzblAa2ak6M0lCw6+b14tIO2bGqP4pjOqfwnUzhuOcY3t5TUswLC/ez0vrPmnZPjs1gXGD0hiXk9byMzcrmVhNpichpCAQ8ZGZkRtIJjeQzNVnDQOg4nA9H+2uZENpJRuCPx9cvJX6Rq/1nhQfy9hBqW0CYuzAtO7fm0GinrqGRCJAXUMTRXurW4Jhw+4KNpRWtpyhFGMwIpDMuGCXUnNAqGtJmqlrSCTC9YmL8T7cc9JgmrfMOceug4fbtBze33GAF9aWtjxPXUvSFQoCkQhlZgzp15ch/fryufFH7wegriU5WeoaEokCJ9u1NHZQKvn9U8hJT9Jd3noJdQ2JRLnudi317RPLyOyUljOdRvVPIb9/CsMy+xLXnftDS4+kIBCJUp12LdXUs/GTSor2VVO013u8t7WcZ9/f1bJNn9gYcgN9ye+fyshWATEikExivLqYIo2CQETaSO8b702Fkdf2ngDVRxrYsreazXuPBsT60gpe/nA3TcEe5hiDoZl9ye+f4gVEdgr5A1IZmZ1Mqu4A12MpCESkS1IS4pg0NINJQzPaLK+tb2Rb2aGWcGh+LPq4jLrGppbtBqYlkj8ghZHZKeQP8EJiVP8UsnRfB98pCETklCTGx3LGoDTOGJTWZnlDYxM79td4wbCvmqI93s8nV+6kpq6xZbvM5D6MyvZaEPmtxiIGpSdq7qXTREEgImERFxtDXnYKedkpfK7V8qYmx+7K2lathyqK9lbz8oe7eTw4Uyt4LZC87GTyAsmMCKQwIvh7biCZlAR9dIWS3k0ROa1iYozBGUkMzkjiU6OzW5Y75yg/VEdRcBxiy95qtuyrZkXxAf66tpTWZ7r3T01gRCCZvOxkRjQHRSCZYZl96ROns5lOloJARHoEMyOQkkAgJYGZ7Qaqa+sb2V5ew7ayaraWHWLbvkNsKzvEa+v3UH6ormW72BhjaL+ko+HQ0qJIZmBaoq6J6ISCQER6vMT4WMYMTGXMwNRj1lXU1LOt/BDbyqrZtu+QFxRlh1i2bX+bsYjE+Bhys45tReQFkumX3Od0Hk6PoyAQkYiW3jeeyX0zmNzubCbnHHsqj7C1rJptrVoRG3dX8dr6PTQ0He1r6tc3viUcjgZFMrlZyVEx9YaCQER6JTNjYHoiA9MTmTUy0GZdfWMTJQcOe11NwYDYVnaIpVvKeHp1SZttc9ITGZbVl5zguEZO8DE4I5FB6Ukk94KB68g/AhGRkxQfG9Pyrf/TY9uuq6lraAmG5q6mkgM1LNu6n08qa2lsajs/W0bfeHLSj4ZDTpuwSCI7NaHHz/aqIBARaaVvnzjG53i3C22vobGJvVVHKD14mF0HD1N6sJbSg4cpPXjYC4tt5VQFJ/JrFhfjtUyOtigSGZzRN/gziUEZSb6fDhvWVzezecCvgVjgQefcv3WwzVXAPYAD1jrnrg1nTSIi3RUXG9Pybb/DaTyBytp6dgcDYlcwJEqDobF8W8etivSk+E5aFN7f/VMTw9qqCFsQmFks8Fvgs0AJsMLMnnfObWi1TT5wJzDbOXfAzPqHqx4RkdMhLTGetIHxHZ7hBNDY5NhbVRtsRbRvVRxm+bb9LdODN4uNMQamJfKl2bl8uTAv5DWHs0UwHShyzm0FMLOFwCXAhlbbfAX4rXPuAIBzbm8Y6xER8V1sjDEoPYlB6UlMG97xNlW19eyuqD2mRRGuW4+GMwgGAztb/V0CzGi3zWgAM1uC1310j3PulfY7MrNbgFsAhg0bFpZiRUR6itTEeFIT4xk9oONWRaj5fS12HJAPzAXmAw+YWUb7jZxzv3fOFTjnCrKzs9uvFhGRUxDOINgFDG3195DgstZKgOedc/XOuW3Ax3jBICIip0k4g2AFkG9mI8ysD3AN8Hy7bZ7Daw1gZgG8rqKtYaxJRETaCVsQOOcagH8CXgU+Ap50zq03s5+Y2cXBzV4Fys1sA/AWcIdzrjxcNYmIyLHMOXfirXqQgoICt3LlSr/LEBGJKGa2yjnX4eUPfg8Wi4iIzxQEIiJRTkEgIhLlIm6MwMz2Adu7+fQAUBbCciKd3o+29H4cpfeird7wfgx3znV4IVbEBcGpMLOVnQ2WRCO9H23p/ThK70Vbvf39UNeQiEiUUxCIiES5aAuC3/tdQA+j96MtvR9H6b1oq1e/H1E1RiAiIseKthaBiIi0oyAQEYlyURMEZjbPzDaZWZGZfc/vevxkZkPN7C0z22Bm683sm37X5DczizWz983sb37X4jczyzCzp8xso5l9ZGZn+12TX8zs9uC/kQ/N7HEzS/S7pnCIiiBodf/kC4BxwHwzG+dvVb5qAP7FOTcOmAl8LcrfD4Bv4s2SK/Br4BXn3FhgElH6vpjZYOAbQIFz7ky8uyhe429V4REVQUCr+yc75+qA5vsnRyXn3G7n3Org71V4/9AH+1uVf8xsCPB54EG/a/GbmaUDc4A/ADjn6pxzB/2tyldxQJKZxQF9gVKf6wmLaAmCju6fHLUffK2ZWS4wBVjmbyW+ug/4DtDkdyE9wAhgH/BwsKvsQTNL9rsoPzjndgH3AjuA3UCFc+41f6sKj2gJAumAmaUATwPfcs5V+l2PH8zsImCvc26V37X0EHHAVOB3zrkpwCEgKsfUzKwfXs/BCCAHSDazf/C3qvCIliDoyv2To4qZxeOFwKPOuWf8rsdHs4GLzawYr8vw02b2Z39L8lUJUOKca24hPoUXDNHoM8A259w+51w98Awwy+eawiJagqAr90+OGmZmeH3AHznnfuV3PX5yzt3pnBvinMvF+//iTedcr/zW1xXOuU+AnWY2JrjoPGCDjyX5aQcw08z6Bv/NnEcvHTiP87uA08E512BmzfdPjgUecs6t97ksP80GrgfWmdma4LK7nHMv+ViT9BxfBx4NfmnaCnzJ53p84ZxbZmZPAavxzrR7n1461YSmmBARiXLR0jUkIiKdUBCIiEQ5BYGISJRTEIiIRDkFgYhIlFMQiLRjZo1mtqbVI2RX1ppZrpl9GKr9iYRCVFxHIHKSDjvnJvtdhMjpohaBSBeZWbGZ/cLM1pnZcjMbFVyea2ZvmtkHZvaGmQ0LLh9gZs+a2drgo3l6glgzeyA4z/1rZpbk20GJoCAQ6UhSu66hq1utq3DOTQD+C2/WUoD/C/zROTcReBT4TXD5b4C/O+cm4c3X03w1ez7wW+fceOAgcHmYj0fkuHRlsUg7ZlbtnEvpYHkx8Gnn3NbgpH2fOOeyzKwMGOScqw8u3+2cC5jZPmCIc+5Iq33kAv/rnMsP/v1dIN4597PwH5lIx9QiEDk5rpPfT8aRVr83orE68ZmCQOTkXN3q57vB35dy9BaG1wGLg7+/AdwGLfdETj9dRYqcDH0TETlWUqtZWcG7f2/zKaT9zOwDvG/184PLvo53R6878O7u1Txb5zeB35vZzXjf/G/Du9OVSI+iMQKRLgqOERQ458r8rkUklNQ1JCIS5dQiEBGJcmoRiIhEOQWBiEiUUxCIiEQ5BYGISJRTEIiIRLn/D+wmZ+dvaioBAAAAAElFTkSuQmCC\n",
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       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
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      },
      "metadata": {
-      "needs_background": "light",
-      "tags": []
+      "needs_background": "light"
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      "output_type": "display_data"
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@@ -572,7 +3122,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 13,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -587,9 +3137,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "814/814 [==============================] - 22s 27ms/step - loss: 0.9530 - accuracy: 0.7319\n",
-      "Test loss: 0.9530481696128845\n",
-      "Test accuracy: 0.7318684458732605\n"
+      "814/814 [==============================] - 27s 33ms/step - loss: 0.9151 - accuracy: 0.7503\n",
+      "Test loss: 0.9151020050048828\n",
+      "Test accuracy: 0.7503457069396973\n"
      ]
     }
    ],
@@ -619,7 +3169,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 0,
+   "execution_count": 4,
    "metadata": {
     "colab": {},
     "colab_type": "code",
@@ -655,7 +3205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 123,
+   "execution_count": 12,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -670,31 +3220,31 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model: \"sequential_38\"\n",
+      "Model: \"sequential\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "conv2d_107 (Conv2D)          (None, 32, 32, 64)        640       \n",
+      "conv2d (Conv2D)              (None, 32, 32, 64)        640       \n",
       "_________________________________________________________________\n",
-      "conv2d_108 (Conv2D)          (None, 32, 32, 64)        36928     \n",
+      "conv2d_1 (Conv2D)            (None, 32, 32, 64)        36928     \n",
       "_________________________________________________________________\n",
-      "max_pooling2d_53 (MaxPooling (None, 16, 16, 64)        0         \n",
+      "max_pooling2d (MaxPooling2D) (None, 16, 16, 64)        0         \n",
       "_________________________________________________________________\n",
-      "batch_normalization_34 (Batc (None, 16, 16, 64)        256       \n",
+      "batch_normalization (BatchNo (None, 16, 16, 64)        256       \n",
       "_________________________________________________________________\n",
-      "conv2d_109 (Conv2D)          (None, 16, 16, 128)       73856     \n",
+      "conv2d_2 (Conv2D)            (None, 16, 16, 128)       73856     \n",
       "_________________________________________________________________\n",
-      "max_pooling2d_54 (MaxPooling (None, 8, 8, 128)         0         \n",
+      "max_pooling2d_1 (MaxPooling2 (None, 8, 8, 128)         0         \n",
       "_________________________________________________________________\n",
-      "dropout_3 (Dropout)          (None, 8, 8, 128)         0         \n",
+      "dropout (Dropout)            (None, 8, 8, 128)         0         \n",
       "_________________________________________________________________\n",
-      "flatten_49 (Flatten)         (None, 8192)              0         \n",
+      "flatten (Flatten)            (None, 8192)              0         \n",
       "_________________________________________________________________\n",
-      "dense_91 (Dense)             (None, 64)                524352    \n",
+      "dense (Dense)                (None, 64)                524352    \n",
       "_________________________________________________________________\n",
-      "dense_92 (Dense)             (None, 64)                4160      \n",
+      "dense_1 (Dense)              (None, 64)                4160      \n",
       "_________________________________________________________________\n",
-      "dense_93 (Dense)             (None, 11)                715       \n",
+      "dense_2 (Dense)              (None, 11)                715       \n",
       "=================================================================\n",
       "Total params: 640,907\n",
       "Trainable params: 640,779\n",
@@ -710,7 +3260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 124,
+   "execution_count": 16,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -726,41 +3276,45 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.7756 - accuracy: 0.7552\n",
-      "Epoch 00001: val_accuracy improved from -inf to 0.86341, saving model to /content/checkpoint_cnn_best/checkpoint\n",
-      "1946/1946 [==============================] - 594s 305ms/step - loss: 0.7756 - accuracy: 0.7552 - val_loss: 0.4789 - val_accuracy: 0.8634\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.7535 - accuracy: 0.7612\n",
+      "Epoch 00001: val_accuracy improved from -inf to 0.86113, saving model to /content/checkpoint_cnn_best\\checkpoint\n",
+      "1946/1946 [==============================] - 521s 268ms/step - loss: 0.7535 - accuracy: 0.7612 - val_loss: 0.4573 - val_accuracy: 0.8611\n",
       "Epoch 2/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.4716 - accuracy: 0.8581\n",
-      "Epoch 00002: val_accuracy improved from 0.86341 to 0.87888, saving model to /content/checkpoint_cnn_best/checkpoint\n",
-      "1946/1946 [==============================] - 594s 305ms/step - loss: 0.4716 - accuracy: 0.8581 - val_loss: 0.4080 - val_accuracy: 0.8789\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.4506 - accuracy: 0.8624\n",
+      "Epoch 00002: val_accuracy did not improve from 0.86113\n",
+      "1946/1946 [==============================] - 514s 264ms/step - loss: 0.4506 - accuracy: 0.8624 - val_loss: 0.4984 - val_accuracy: 0.8509\n",
       "Epoch 3/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.4169 - accuracy: 0.8732\n",
-      "Epoch 00003: val_accuracy improved from 0.87888 to 0.88052, saving model to /content/checkpoint_cnn_best/checkpoint\n",
-      "1946/1946 [==============================] - 593s 305ms/step - loss: 0.4169 - accuracy: 0.8732 - val_loss: 0.4001 - val_accuracy: 0.8805\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.3974 - accuracy: 0.8786\n",
+      "Epoch 00003: val_accuracy improved from 0.86113 to 0.87606, saving model to /content/checkpoint_cnn_best\\checkpoint\n",
+      "1946/1946 [==============================] - 554s 285ms/step - loss: 0.3974 - accuracy: 0.8786 - val_loss: 0.3995 - val_accuracy: 0.8761\n",
       "Epoch 4/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.3823 - accuracy: 0.8836\n",
-      "Epoch 00004: val_accuracy improved from 0.88052 to 0.88862, saving model to /content/checkpoint_cnn_best/checkpoint\n",
-      "1946/1946 [==============================] - 593s 305ms/step - loss: 0.3823 - accuracy: 0.8836 - val_loss: 0.3735 - val_accuracy: 0.8886\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.3600 - accuracy: 0.8904\n",
+      "Epoch 00004: val_accuracy improved from 0.87606 to 0.89180, saving model to /content/checkpoint_cnn_best\\checkpoint\n",
+      "1946/1946 [==============================] - 609s 313ms/step - loss: 0.3600 - accuracy: 0.8904 - val_loss: 0.3685 - val_accuracy: 0.8918\n",
       "Epoch 5/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.3576 - accuracy: 0.8907\n",
-      "Epoch 00005: val_accuracy improved from 0.88862 to 0.90081, saving model to /content/checkpoint_cnn_best/checkpoint\n",
-      "1946/1946 [==============================] - 593s 305ms/step - loss: 0.3576 - accuracy: 0.8907 - val_loss: 0.3440 - val_accuracy: 0.9008\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.3314 - accuracy: 0.8991\n",
+      "Epoch 00005: val_accuracy improved from 0.89180 to 0.90891, saving model to /content/checkpoint_cnn_best\\checkpoint\n",
+      "1946/1946 [==============================] - 645s 332ms/step - loss: 0.3314 - accuracy: 0.8991 - val_loss: 0.3094 - val_accuracy: 0.9089\n",
       "Epoch 6/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.3349 - accuracy: 0.8975\n",
-      "Epoch 00006: val_accuracy improved from 0.90081 to 0.90663, saving model to /content/checkpoint_cnn_best/checkpoint\n",
-      "1946/1946 [==============================] - 595s 306ms/step - loss: 0.3349 - accuracy: 0.8975 - val_loss: 0.3223 - val_accuracy: 0.9066\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.3104 - accuracy: 0.9049\n",
+      "Epoch 00006: val_accuracy did not improve from 0.90891\n",
+      "1946/1946 [==============================] - 632s 325ms/step - loss: 0.3104 - accuracy: 0.9049 - val_loss: 0.3592 - val_accuracy: 0.8950\n",
       "Epoch 7/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.3144 - accuracy: 0.9038\n",
-      "Epoch 00007: val_accuracy did not improve from 0.90663\n",
-      "1946/1946 [==============================] - 595s 306ms/step - loss: 0.3144 - accuracy: 0.9038 - val_loss: 0.3270 - val_accuracy: 0.9049\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.2948 - accuracy: 0.9112\n",
+      "Epoch 00007: val_accuracy improved from 0.90891 to 0.91300, saving model to /content/checkpoint_cnn_best\\checkpoint\n",
+      "1946/1946 [==============================] - 675s 347ms/step - loss: 0.2948 - accuracy: 0.9112 - val_loss: 0.3000 - val_accuracy: 0.9130\n",
       "Epoch 8/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.3006 - accuracy: 0.9087\n",
-      "Epoch 00008: val_accuracy did not improve from 0.90663\n",
-      "1946/1946 [==============================] - 593s 305ms/step - loss: 0.3006 - accuracy: 0.9087 - val_loss: 0.3340 - val_accuracy: 0.9023\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.2776 - accuracy: 0.9159\n",
+      "Epoch 00008: val_accuracy did not improve from 0.91300\n",
+      "1946/1946 [==============================] - 641s 330ms/step - loss: 0.2776 - accuracy: 0.9159 - val_loss: 0.3266 - val_accuracy: 0.9032\n",
       "Epoch 9/10\n",
-      "1946/1946 [==============================] - ETA: 0s - loss: 0.2815 - accuracy: 0.9136\n",
-      "Epoch 00009: val_accuracy did not improve from 0.90663\n",
-      "1946/1946 [==============================] - 595s 306ms/step - loss: 0.2815 - accuracy: 0.9136 - val_loss: 0.3365 - val_accuracy: 0.9058\n"
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.2622 - accuracy: 0.9201\n",
+      "Epoch 00009: val_accuracy improved from 0.91300 to 0.91373, saving model to /content/checkpoint_cnn_best\\checkpoint\n",
+      "1946/1946 [==============================] - 625s 321ms/step - loss: 0.2622 - accuracy: 0.9201 - val_loss: 0.2985 - val_accuracy: 0.9137\n",
+      "Epoch 10/10\n",
+      "1946/1946 [==============================] - ETA: 0s - loss: 0.2498 - accuracy: 0.9240\n",
+      "Epoch 00010: val_accuracy did not improve from 0.91373\n",
+      "1946/1946 [==============================] - 713s 366ms/step - loss: 0.2498 - accuracy: 0.9240 - val_loss: 0.2917 - val_accuracy: 0.9126\n"
      ]
     }
    ],
@@ -775,7 +3329,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 125,
+   "execution_count": null,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -785,21 +3339,7 @@
     "id": "VytQECDVz_Gv",
     "outputId": "2dcb2ab2-3619-4617-feb5-dd12495c861e"
    },
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light",
-      "tags": []
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "try:\n",
     "    plt.plot(history.history['accuracy'])\n",
@@ -816,7 +3356,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 126,
+   "execution_count": null,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -826,21 +3366,7 @@
     "id": "60mJypwQz_Gx",
     "outputId": "7e1a0317-1578-47fe-c561-a46023e39ff9"
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light",
-      "tags": []
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plt.plot(history.history['loss'])\n",
     "plt.plot(history.history['val_loss'])\n",
@@ -853,7 +3379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 127,
+   "execution_count": null,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -863,17 +3389,7 @@
     "id": "w2v80qosz_G0",
     "outputId": "fa802da4-ddf1-4373-9a50-e1e48b2a9d2c"
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "814/814 [==============================] - 64s 79ms/step - loss: 0.3765 - accuracy: 0.8968\n",
-      "Test loss: 0.3764943778514862\n",
-      "Test accuracy: 0.8968192934989929\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "test_loss, test_accuracy = cnn_model.evaluate(grayscale_test_images, test_labels)\n",
     "print(f\"Test loss: {test_loss}\")\n",
@@ -895,7 +3411,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 137,
+   "execution_count": null,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -905,18 +3421,7 @@
     "id": "XMYYWs0oz_G5",
     "outputId": "ed72eb4a-ed5f-4322-865b-9cadd3fd0059"
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "814/814 [==============================] - 21s 26ms/step - loss: 0.9082 - accuracy: 0.7475\n",
-      "MLP best weights model \n",
-      "Test loss: 0.9081620573997498\n",
-      "Test accuracy: 0.7475031018257141\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model_best_epoch_file = tf.train.latest_checkpoint(\"checkpoint_mlp_best\")\n",
     "model = get_mlp_model(grayscale_train_images[0].shape)\n",
@@ -930,7 +3435,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 133,
+   "execution_count": 13,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -945,10 +3450,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "814/814 [==============================] - 62s 77ms/step - loss: 0.3639 - accuracy: 0.8937\n",
+      "814/814 [==============================] - 44s 54ms/step - loss: 0.3344 - accuracy: 0.9015\n",
       "CNN best weights model \n",
-      "Test loss: 0.36391595005989075\n",
-      "Test accuracy: 0.8937077522277832\n"
+      "Test loss: 0.3344075083732605\n",
+      "Test accuracy: 0.9015442728996277\n"
      ]
     }
    ],
@@ -965,7 +3470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 134,
+   "execution_count": 14,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -978,14 +3483,13 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1152x864 with 10 Axes>"
       ]
      },
      "metadata": {
-      "needs_background": "light",
-      "tags": []
+      "needs_background": "light"
      },
      "output_type": "display_data"
     }
@@ -1013,6 +3517,164 @@
     "    \n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import PIL\n",
+    "from PIL import Image, ImageEnhance, ImageDraw, ImageFont\n",
+    "from IPython.display import display\n",
+    "\n",
+    "img = Image.open('no_3.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "^C\n",
+      "Collecting package metadata (current_repodata.json): ...working... done\n",
+      "Solving environment: ...working... failed with initial frozen solve. Retrying with flexible solve.\n",
+      "Collecting package metadata (repodata.json): ...working... done\n",
+      "Solving environment: ...working... failed with initial frozen solve. Retrying with flexible solve.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "PackagesNotFoundError: The following packages are not available from current channels:\n",
+      "\n",
+      "  - cv2\n",
+      "  - pil\n",
+      "\n",
+      "Current channels:\n",
+      "\n",
+      "  - https://repo.anaconda.com/pkgs/main/win-64\n",
+      "  - https://repo.anaconda.com/pkgs/main/noarch\n",
+      "  - https://repo.anaconda.com/pkgs/r/win-64\n",
+      "  - https://repo.anaconda.com/pkgs/r/noarch\n",
+      "  - https://repo.anaconda.com/pkgs/msys2/win-64\n",
+      "  - https://repo.anaconda.com/pkgs/msys2/noarch\n",
+      "  - https://conda.anaconda.org/conda-forge/win-64\n",
+      "  - https://conda.anaconda.org/conda-forge/noarch\n",
+      "\n",
+      "To search for alternate channels that may provide the conda package you're\n",
+      "looking for, navigate to\n",
+      "\n",
+      "    https://anaconda.org\n",
+      "\n",
+      "and use the search bar at the top of the page.\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "!conda install cv2 PIL\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "img = cv2.imread('no_0.png', cv2.IMREAD_GRAYSCALE)\n",
+    "img = cv2.resize(img, (32, 32))\n",
+    "my_img = img[np.newaxis,...,np.newaxis]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAH4AAACPCAYAAAA87W80AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAG5ElEQVR4nO2dbYhUVRiAn3d3XRfDD3RV8lvBPlBCQSXMSINQgwTbMEVCAyOoP/Uz7cPKxD9BP6Kw+qM/QgyxFAwLc93KUDI3LVIJ8wMF81tDXdfd0497dvfOeMe5szu799593weGe88959x55z6858w9w8yIcw5DHxVJB2Akg4lXiolXiolXiolXiolXSq8RLyL1ItLle1MRWS0iTkRmdz2q9JIq8f6Chx9NInJeRH4TkS9EZL6IVCYYW30n+1aKyGsickhEborIJRHZISIzyxxm/JjStIATyth3/bYSGARMAh4DqoFfgaXOuWN5fccA/ZxzR7oYQy1QC5xyzt3Ii22Pc252iecTYDPwHHAU2A4MBp4HaoA659w3XYm5UzjnUvMAXBBSZN1wfwEdcAoYlkBs9Z3ot8T3/RmoCR2fDjQB/wL9e/xaJy07rnhfXwHs9u0+yqurj+oL9AVWA8f9hf4HWOOP3yXTt3XAbF9e3hZXxGN1jNfU4NvOiajb6Ote7Olrnao5vhjOuVYCaQBL/DBaEF+/BXgHuAN8TDDULgc2xXzaRjqmnpN+v+1RX+T5+wIzgRvAjxFNvvXbJ2PGUj6SzvJSMj6Uwc2+7fh7ZTzwgm/XAFSHjg8CjhAj4/Niq4/7WnyfSb7f4QL103z9Psv4IjjnmoCLvji0SPNlfvumc+526BxXgPfLH91dDPTbqwXq244P6v5QcsmceE/bEF/slmQq0Arsjaj7qawRdY64r6PsZE68iNQQ3A4BnC/SfCBwyTl3J6LuXFkDi6YtowcWqB+Q167HyJx4YBZQBZxzzp0o0vYaMFhEqiLqhpc7sAj+BlqACQVimOi3xyLqupVMiReRCmCVL34Zo8tBgtcYtUI2q8SnbyVYUIqNfz+yF+gHPB7RZL7f/lBiLF0mM+JFZBjBLdhsggWctTG6bfTbNSJSHTrXQOCtEkO4CIwusQ/Ap6EYakIxTCdYvTtPcMvZo0QNP4kjIqv9bgUdS7azCJZs9xMs2V6IcaqNwGJgHvCHiGwD+gB1BEu/DxJkchx2AYtFZDtwgGBdoME511Ck3ybgWYIl24O+/xAC6ZXAS865azFjKB9J37tH3ceHHk3ABYIL/TmBwIoCfeuJXrmrAd4jWLFrAk4AHwAj/XN8HfM+fhjB9HKOYN6OtXLn+1YBrwOHgZvAZWAHMDOpa52qD2l6EhF5CvgOWOeceyPpeHqazMzxnUVERkQcGwKs88WtPRtROigp42sHV7pxo/t0Yzjl5/jJZm7ectzXT6iqEpqbHVevt9LSArWDKxg7KluvpxROnG7mwqWWyM8zSnpzN250H/bv7Mwb2+TYvO066zdc48+jt7l0pYWavsL0KX1ZvngAK5YOoMjnPJlmxtzTBetS+a6+nCxa0J9FC/onHUbq6PVzvBGNiVeKiVeKiVeKiVeKiVeKiVeKiVeKiVeKiVeKiVeKiVeKiVdKJj+dmztiSlnPt/NsY1nPlwUs45Vi4pWSyaE+TP4wfaO1/buRLBw1I9Y5Vp57JKe8dvihLseVdizjlWLilWLilZKZOf7pSXPa93ee3V2wXb+K6lC7xljnnjtyak556quvtO8fXPlJzAizhWW8Uky8UjIz1Ldcvtxt59555mBOecLWjtvA/FXC3rLKZxmvFBOvFBOvlMzM8T3J8YXrOwoLc+vCc37lwxNz6nbs+qoboyovlvFKMfFKsaG+RMK3c3Pv+q2N7GAZrxQTr5TMDPVpXDHLjyn8jj+N8YaxjFeKiVeKiVdKauf4B/Ysyykfe2JDQpH0TizjlWLilZLaoX78kt9zD5xNJo5SuP392FCpMakwYmEZrxQTrxQTr5TUzvFZZPekjj+FTvvyrWW8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8Uky8UlL7Far8rx1N2PJy+/7xuvWknVvPhP/6rDGpMApiGa8UE6+U1A71+Ty06q+OQl1ycdyL8L9Z7TnzWYKRFMcyXikmXikmXimZmeN3HGlo30/Lr03MGzMtpzxuX5+EIikdy3ilmHilZGaoD5P79yBTCrb7b9GjOeWLk6V933XsUnvYFWw39u1fCp5/8oHWnPKH9xdumzYs45Vi4pVi4pWSyTk+zL1v5+5VF5MVXT9FGrGMV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4qJV4o454q3amssch442X3hGGVmrHNuaFRFSeKN3oMN9Uox8Uox8Uox8Uox8Uox8Uox8Uox8Uox8Ur5HzcwDod71Qn4AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 144x144 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axes = plt.subplots(1, 1,figsize = (2,2))\n",
+    "fig.subplots_adjust(hspace=-0.7, wspace= 0.2)\n",
+    "#for i,ax in enumerate(axes.flat):\n",
+    " #   ax.imshow(np.squeeze(my_img))\n",
+    "  #  ax.text(6., -1.0, f'Digit {0}',fontsize = 20)\n",
+    "  #  ax.get_xaxis().set_visible(False)\n",
+    "   # ax.get_yaxis().set_visible(False)\n",
+    "axes.imshow(np.squeeze(my_img))\n",
+    "axes.text(6., -1.0, f'Digit {0}',fontsize = 20)\n",
+    "axes.get_xaxis().set_visible(False)\n",
+    "axes.get_yaxis().set_visible(False)\n",
+    "    \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "'AxesSubplot' object is not subscriptable",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-37-87f60303bb68>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubplots_adjust\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhspace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.4\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwspace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m0.2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0maxes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmy_img\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      7\u001b[0m \u001b[0maxes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_xaxis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_visible\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[0maxes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_yaxis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_visible\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mTypeError\u001b[0m: 'AxesSubplot' object is not subscriptable"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "predict = model.predict(my_img)\n",
+    "\n",
+    "fig, axes = plt.subplots(1, 1, figsize=(16, 12))\n",
+    "fig.subplots_adjust(hspace=0.4, wspace=-0.2)\n",
+    "\n",
+    "axes[0, 0].imshow(np.squeeze(my_img))\n",
+    "axes[0, 0].get_xaxis().set_visible(False)\n",
+    "axes[0, 0].get_yaxis().set_visible(False)\n",
+    "axes[0, 0].text(10., -1.5, f'Digit {0}')\n",
+    "for pred in predict:\n",
+    "  axes[0, 1].bar(np.arange(len(pred)), pred)\n",
+    "  axes[0, 1].set_xticks(np.arange(len(pred)))\n",
+    "  axes[0, 1].set_title(f\"Categorical distribution. Model prediction: {np.argmax(pred)}\")"
+   ]
   }
  ],
  "metadata": {
@@ -1022,13 +3684,9 @@
    "provenance": []
   },
   "kernelspec": {
-   "name": "python3",
-   "display_name": "Python 3.9.0 64-bit",
-   "metadata": {
-    "interpreter": {
-     "hash": "63fd5069d213b44bf678585dea6b12cceca9941eaf7f819626cde1f2670de90d"
-    }
-   }
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1040,9 +3698,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.0-final"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
-}
\ No newline at end of file
+ "nbformat_minor": 4
+}
diff --git a/workspace.code-workspace b/workspace.code-workspace
new file mode 100644
index 0000000..362d7c2
--- /dev/null
+++ b/workspace.code-workspace
@@ -0,0 +1,7 @@
+{
+	"folders": [
+		{
+			"path": "."
+		}
+	]
+}
\ No newline at end of file