OD_Character_Segmentation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "# turn off tensorflow INFO (Debugging info)\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "import cv2\n",
    "import glob\n",
    "import matplotlib.pyplot as plt\n",
    "import keras\n",
    "from keras.models import load_model\n",
    "from keras import backend as K\n",
    "import xml.etree.ElementTree as ET\n",
    "from pprint import pprint\n",
    "K.set_image_data_format('channels_first')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# turn off tensorflow INFO (Debugging info)\n",
    "import os\n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Helpers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_wspaces(img_):\n",
    "    gray_ = cv2.cvtColor(img_, cv2.COLOR_BGR2GRAY)\n",
    "    gray_ = 255*(gray_ < 128).astype(np.uint8) # To invert the text to white\n",
    "    coords_ = cv2.findNonZero(gray_) # Find all non-zero points (text)\n",
    "    x_, y_, w_, h_ = cv2.boundingRect(coords_) # Find minimum spanning bounding box\n",
    "    rect_ = img_[y_:y_+h_, x_:x_+w_] # Crop the image - note we do this on the original image\n",
    "    \n",
    "    # add a white border of 1 pixel\n",
    "    bordersize=2\n",
    "    rect_ = cv2.copyMakeBorder(\n",
    "        rect_,\n",
    "        top=bordersize,\n",
    "        bottom=bordersize,\n",
    "        left=bordersize,\n",
    "        right=bordersize,\n",
    "        borderType=cv2.BORDER_CONSTANT,\n",
    "        value=[255, 255, 255]\n",
    "    )\n",
    "    return rect_\n",
    "\n",
    "def load_image_into_numpy_array(image):\n",
    "    (im_width, im_height) = image.size\n",
    "    return np.array(image.getdata()).reshape((im_height, im_width, 3)).astype(np.uint8)\n",
    "\n",
    "\n",
    "def one_hot_encode_to_char(arr, threshold=0.5, get_max=True):\n",
    "    result = []\n",
    "    val = 0\n",
    "    for i in range(len(arr)):\n",
    "        if arr[i] >= threshold:\n",
    "            result.append((val, arr[i]))\n",
    "        val +=1\n",
    "    _max = []\n",
    "    high = 0\n",
    "    if get_max:\n",
    "        for i in result:\n",
    "            if i[1] > high:\n",
    "                _max = [i[0]]\n",
    "                high = i[1]\n",
    "        return _max\n",
    "    else:\n",
    "        return [i[0] for i in result]\n",
    "\n",
    "def one_hot_encode_to_char_list(arr, threshold=0.5, get_max=True):\n",
    "    result = []\n",
    "    for i in range(len(arr)):\n",
    "        if arr[i] >= threshold:\n",
    "            result.append((i, arr[i]))\n",
    "    _max = []\n",
    "    high = 0\n",
    "    result = sorted(result, key=lambda x: x[1], reverse=True)\n",
    "    if get_max:\n",
    "        return result[-1]\n",
    "    return result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Image paths: \n",
      "Datasets/Object_Detection/test\\exp0015.png\n",
      "Datasets/Object_Detection/test\\exp0016.png\n",
      "Datasets/Object_Detection/test\\exp0029.png\n",
      "Datasets/Object_Detection/test\\exp0037.png\n",
      "Datasets/Object_Detection/test\\exp0044.png\n",
      "Datasets/Object_Detection/test\\exp0051.png\n",
      "Datasets/Object_Detection/test\\exp9.png\n"
     ]
    }
   ],
   "source": [
    "PATH_TO_TEST_IMAGES_DIR = \"Datasets/Object_Detection/test/*.png\"\n",
    "PATH_TO_TRAIN_IMAGES_DIR = \"Datasets/Object_Detection/train/*.png\"\n",
    "\n",
    "TEST_IMAGE_PATHS = list(glob.glob(PATH_TO_TEST_IMAGES_DIR))\n",
    "TRAIN_IMAGE_PATHS = list(glob.glob(PATH_TO_TRAIN_IMAGES_DIR))\n",
    "\n",
    "print(\"Train Image paths: \")\n",
    "for i in TEST_IMAGE_PATHS:\n",
    "    print(i)\n",
    "    \n",
    "# Change TEST/TRAIN Images to test here\n",
    "image_paths = TEST_IMAGE_PATHS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load CNN/ANN Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "IMAGE_SIZE = (320, 320)\n",
    "models_path = \"trained_models/\"\n",
    "\n",
    "# CNN\n",
    "cnn = load_model(models_path+\"model3.h5\")\n",
    "\n",
    "# ANN\n",
    "#ann = load_model(models_path+\"ann1.h5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load symbols/labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latex</th>\n",
       "      <th>old_symbol</th>\n",
       "      <th>new_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>33</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D</td>\n",
       "      <td>34</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>E</td>\n",
       "      <td>35</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  latex  old_symbol  new_id\n",
       "0     A          31       0\n",
       "1     B          32       1\n",
       "2     C          33       2\n",
       "3     D          34       3\n",
       "4     E          35       4"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "symbols = pd.read_csv(\"processed_data/symbols.csv\").drop([\"Unnamed: 0\"], axis=1)\n",
    "symbols.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Image path:  Datasets/Object_Detection/test\\exp0015.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 99.62 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 81 , Latex: \\supset , Confidence Score: 47.64 %\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 23.3 %\n",
      "Symbol_id: 83 , Latex: - , Confidence Score: 9.81 %\n",
      "Symbol_id: 96 , Latex: \\perp , Confidence Score: 2.74 %\n",
      "Symbol_id: 65 , Latex: \\Delta , Confidence Score: 2.57 %\n",
      "Symbol_id: 31 , Latex: 5 , Confidence Score: 2.5 %\n",
      "Symbol_id: 51 , Latex: o , Confidence Score: 2.36 %\n",
      "Symbol_id: 75 , Latex: \\cdot , Confidence Score: 1.34 %\n",
      "Symbol_id: 98 , Latex: \\exists , Confidence Score: 1.22 %\n",
      "Symbol_id: 105 , Latex: //( , Confidence Score: 1.08 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 81 , Latex: \\supset , Confidence Score: 42.18 %\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 29.61 %\n",
      "Symbol_id: 83 , Latex: - , Confidence Score: 10.21 %\n",
      "Symbol_id: 96 , Latex: \\perp , Confidence Score: 4.24 %\n",
      "Symbol_id: 65 , Latex: \\Delta , Confidence Score: 2.61 %\n",
      "Symbol_id: 31 , Latex: 5 , Confidence Score: 1.64 %\n",
      "Symbol_id: 51 , Latex: o , Confidence Score: 1.6 %\n",
      "Symbol_id: 105 , Latex: //( , Confidence Score: 1.28 %\n",
      "Symbol_id: 75 , Latex: \\cdot , Confidence Score: 1.21 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 92 , Latex: \\times , Confidence Score: 99.42 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 84 , Latex: + , Confidence Score: 98.91 %\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAD/UlEQVR4nO2cP4gcZRiHn59RKy2UO+XQnCeSQqsIiwZSiiBpooViCkkhnIUBBZtgZWmhtkKCgRSBICiYIhAk2NhI1hDUeKhBDj094l3ln0aiP4udyHnu3u3uzPvN7Mz3wHE7MzvzvffMxzsz37z3yTaZOG6pO4C2kwUHkwUHkwUHkwUHkwUHU0qwpKckfSPpmqTjVQXVJjTtfbCkPcC3wJPAGnAJOGL76+rCm31uLbHvY8A1298DSDoLHAZGCp6bm/PS0lKJJpvJ6uoqm5ubGratjOD7gB+3LK8Bj2//kqRlYBlgcXGRfr9foslm0uv1Rm4rk4OHnbH/5RvbJ2z3bPfm5+dLNDeblOnBa8DeLcv3Az+XC6c6pP+e/7rGXMr04EvAPkkPSrodeB44V01Y7WHqHmz7hqRjwAVgD3DK9tXKIivB9t5bJ2VSBLbPA+criqWVtPJJrklj3K0U3CQ6I1hSLbm5M4LrIgsOprWCbTfiYtdawU0hCw4mCw4mCw4mCw4mCw4mCw4mCw6m1HBlVxg1hjHOg0xtgusaFE/dbk4RweQUMQWTjHHkHhxMbT041UjXsJybcpQt9+BgsuBgsuBgsuBgWi+47ldHuwqWtFfSJ5JWJF2V9Eqx/m5JH0v6rvh9V3y4s8c4PfgG8Jrth4EDwMuSHgGOAxdt7wMuFsuZbewq2Pa67cvF59+AFQbF14eB08XXTgNPRwU5y0yUgyUtAY8CnwH32l6HwUkA7hmxz7KkvqT+xsZGuWhnkLEFS7oD+AB41fav4+7XxAr3lGVUYwmWdBsDuWdsf1isvi5podi+APwSE+JsM85dhID3gBXb72zZdA44Wnw+CnxUfXjVUdft2jiDPQeBF4AvJV0p1r0OvAm8L+lF4Afg2ZgQZ5tdBdv+lOH/UQTwRLXhtI/WP8ntRIqLXacFp6BzglNf6DonODVZMLG5uJOCU94Td1JwSrLgLUSkiSw4mCw4mCw4mE7XpqW4k8g9OJgsOJip502bqjFpA/gD2EzW6PTMMX6cD9ge+j4sqWAASX3bo+fBaghVxZlTRDBZcDB1CD5RQ5vTUEmcyXNw18gpIpgsOJhkgps8mfMOJbpvSPpJ0pXi59DEx06Rg5s+mXNR+rVg+7KkO4HPGVSLPgf8bvutaY+dqgf/O5mz7T+Bm5M5N4IdSnRLk0rwsMmcK/kDqmZbiS7AMUlfSDo1TRV/KsFjTeZcN0NKdN8FHgL2A+vA25MeM5XgRk/mDMNLdG1ft/2X7b+BkwxS3USkEtzoyZxHlejerH8ueAb4atJjJ3mj0eTJnAtGlegekbSfQTpbBV6a9MD5UTmY/CQXTBYcTBYcTBYcTBYcTBYcTBYczD+WpU2+0NDQ5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 63 , Latex: \\gamma , Confidence Score: 95.91 %\n",
      "Symbol_id: 24 , Latex: Y , Confidence Score: 2.83 %\n",
      "Symbol_id: 60 , Latex: y , Confidence Score: 1.16 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 6\n",
      "Image path:  Datasets/Object_Detection/test\\exp0016.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 25 , Latex: Z , Confidence Score: 88.24 %\n",
      "Symbol_id: 28 , Latex: 2 , Confidence Score: 7.87 %\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 3.87 %\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAEVElEQVR4nO2cP4gcZRjGf49RKy2UO+UwOU8khVaRXTRgKUKwiRaKKSSFcBYGFGyClaWF2gYiBlIEJBDBFAGRYGMj2Q1BjYca5NDTI95V/mkk+lrsrCzrzN78e7+Z2f1+sNzOzM587z738sz3ffvOJzMj4sdtTQcw70SBnYkCOxMFdiYK7EwU2JlKAks6IulbSTcknawrqHlCZfvBkvYB3wFPA1vAFeCYmX1TX3jd5/YK5z4O3DCzHwAkfQgcBTIFXlpasrW1NQCGw2GFpovT6/Xcrr25ucnu7q7SjlUR+AHgp4ntLeCJ6Q9JWgfWAVZXVxkMBuP9FZouzrhdD/r9fuaxKh6cptD//MbMTptZ38z6y8vLFZrrJlUyeAs4MLG9H/hl1gnD4TB45o6Z1a7nfEyVDL4CHJT0kKQ7gReBi/WENT+UzmAzuyXpBPAJsA84Y2bXa4ssIJPZXXc2V7EIzOwScKmmWOaSoCO5Xq+HmbXmFYI4VHYmCjyFpFp7OpU8eB6p2zpiBjsTBXYmCuzMQnpw1k3Mo+u2kAJP09a5iEgOFi6DPecd0ogZ7MzCZHBT89Axg51ZmAyeJGRF6dwL3JQ1jIkW4czCCRy64HzhBA7NXHpwmu829ajEXAjcVM1DHqJFONP5DA459ViGmMHOdC6D2+y3aeyZwZIOSPpM0oak65JeS/bfK+lTSd8nf+/xD7d75LGIW8AbZvYIcBh4VdKjwEngspkdBC4n227MqlcIWalTlD0FNrNtM7uavP8d2GBUfH0UOJt87CzwrFeQWf3aNgs7ptBNTtIa8BjwBXC/mW3D6J8A3JdxzrqkgaTBzs5OtWg7SG6BJd0FXABeN7Pf8p5XpsJ9bAdpttCFrJ0kl8CS7mAk7jkz+yjZfVPSSnJ8BfjVJ8Ruk6cXIeADYMPM3ps4dBE4nrw/DnxcJZCsjIXu+G0aefrBTwIvAV9JupbsexN4Gzgv6WXgR+B5nxC7zZ4Cm9nnpD9RBPBU1QC6NnAoSmMjuXkXdkyci3AmCuxMFNiZoB7c5JOeTdHK6cq00VtXiRbhTGseRJzF9NxEW155iBnsTGs8OC2L235DzBNfzGBnWpPBaeTtPbQ502MGOxMFdqb0ummlGpN2gD+B3WCNlmeJ/HE+aGapv4cFFRhA0sDMstfBagl1xRktwpkosDNNCHy6gTbLUEucwT140YgW4UwU2JlgArd5MecZJbpvSfpZ0rXk9Uzha4fw4LYv5pyUfq2Y2VVJdwNDRtWiLwB/mNk7Za8dKoP/W8zZzP4Cxos5t4IZJbqVCSVw2mLOtXyBupkq0QU4IelLSWfKVPGHEjjXYs5Nk1Kiewp4GDgEbAPvFr1mKIELL+YcmrQSXTO7aWZ/m9k/wPuMrK4QoQRu9WLOWSW64/rnhOeAr4teO8gvGh1YzDmrRPeYpEOM7GwTeKXoheNQ2Zk4knMmCuxMFNiZKLAzUWBnosDORIGd+Re9PPU+jHtkXQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 81 , Latex: \\supset , Confidence Score: 44.76 %\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 22.91 %\n",
      "Symbol_id: 83 , Latex: - , Confidence Score: 10.4 %\n",
      "Symbol_id: 65 , Latex: \\Delta , Confidence Score: 3.57 %\n",
      "Symbol_id: 51 , Latex: o , Confidence Score: 3.41 %\n",
      "Symbol_id: 31 , Latex: 5 , Confidence Score: 2.85 %\n",
      "Symbol_id: 96 , Latex: \\perp , Confidence Score: 2.23 %\n",
      "Symbol_id: 75 , Latex: \\cdot , Confidence Score: 1.7 %\n",
      "Symbol_id: 105 , Latex: //( , Confidence Score: 1.45 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 81 , Latex: \\supset , Confidence Score: 61.21 %\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 20.3 %\n",
      "Symbol_id: 83 , Latex: - , Confidence Score: 3.4 %\n",
      "Symbol_id: 65 , Latex: \\Delta , Confidence Score: 2.51 %\n",
      "Symbol_id: 51 , Latex: o , Confidence Score: 2.18 %\n",
      "Symbol_id: 75 , Latex: \\cdot , Confidence Score: 2.16 %\n",
      "Symbol_id: 31 , Latex: 5 , Confidence Score: 1.47 %\n",
      "Symbol_id: 95 , Latex: \\cap , Confidence Score: 1.27 %\n",
      "Symbol_id: 105 , Latex: //( , Confidence Score: 1.23 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 92 , Latex: \\times , Confidence Score: 99.99 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 84 , Latex: + , Confidence Score: 83.46 %\n",
      "Symbol_id: 96 , Latex: \\perp , Confidence Score: 11.68 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 60 , Latex: y , Confidence Score: 53.52 %\n",
      "Symbol_id: 63 , Latex: \\gamma , Confidence Score: 26.85 %\n",
      "Symbol_id: 24 , Latex: Y , Confidence Score: 14.39 %\n",
      "Symbol_id: 59 , Latex: x , Confidence Score: 2.03 %\n",
      "Symbol_id: 33 , Latex: 7 , Confidence Score: 1.07 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 6\n",
      "Image path:  Datasets/Object_Detection/test\\exp0029.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 93.76 %\n",
      "Symbol_id: 25 , Latex: Z , Confidence Score: 5.91 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 37.76 %\n",
      "Symbol_id: 96 , Latex: \\perp , Confidence Score: 17.76 %\n",
      "Symbol_id: 76 , Latex: \\leq , Confidence Score: 16.29 %\n",
      "Symbol_id: 77 , Latex: \\geq , Confidence Score: 13.37 %\n",
      "Symbol_id: 81 , Latex: \\supset , Confidence Score: 6.55 %\n",
      "Symbol_id: 82 , Latex: \\subseteq , Confidence Score: 5.1 %\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 1.2 %\n",
      "Symbol_id: 94 , Latex: \\div , Confidence Score: 1.04 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 92 , Latex: \\times , Confidence Score: 99.6 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 94 , Latex: \\div , Confidence Score: 99.94 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 97 , Latex: \\forall , Confidence Score: 64.37 %\n",
      "Symbol_id: 60 , Latex: y , Confidence Score: 32.37 %\n",
      "Symbol_id: 98 , Latex: \\exists , Confidence Score: 1.93 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 5\n",
      "Image path:  Datasets/Object_Detection/test\\exp0037.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 95.74 %\n",
      "Symbol_id: 25 , Latex: Z , Confidence Score: 4.04 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 37.76 %\n",
      "Symbol_id: 96 , Latex: \\perp , Confidence Score: 17.76 %\n",
      "Symbol_id: 76 , Latex: \\leq , Confidence Score: 16.29 %\n",
      "Symbol_id: 77 , Latex: \\geq , Confidence Score: 13.37 %\n",
      "Symbol_id: 81 , Latex: \\supset , Confidence Score: 6.55 %\n",
      "Symbol_id: 82 , Latex: \\subseteq , Confidence Score: 5.1 %\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 1.2 %\n",
      "Symbol_id: 94 , Latex: \\div , Confidence Score: 1.04 %\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAADxUlEQVR4nO2cP4gcdRTHP1+jVlood8qhOU8khVYRDhVSiiA20UIxhaQQzsKAgk2wsrRQWyHBQAohCAqmCIgEGxvJGoIaDzXIoadHvKv800j0a7Fzcpy7udmdebMz4/vAsTszO/N7+9nfvZ1h3zzZJonjhlkH0HdScDApOJgUHEwKDiYFB1NJsKTHJX0j6Yqk43UF1Sc07XmwpH3At8BjwDpwAThi++v6wus+N1bY9yHgiu3vASSdAQ4DYwXPzc15aWmpwpDtZG1tja2tLY3aVkXwXcCPO5bXgYd3v0jSCrACsLi4yGAwqDBkO1leXh67rUoOHvWJ/Sff2D5he9n28vz8fIXhukkVwevA/h3LdwM/Vwunf1QRfAE4IOleSTcDzwJn6wmrP0ydg21fk3QM+AjYB5yyfbm2yHpClS85bJ8DztUUSy+pJDgCaeTZTispcw2Rl8rBtGYGd2nmTkJrZrDtUv9yXaM1gvtKa1LENn2bxTmDg0nBwaTgYFJwMCk4mBQcTAoOJgUHk4KDScHBpOBgUnAwKTiYFBxMCg4mBQeTgoNJwcGk4GD2FCxpv6RPJK1KuizppWL97ZI+lvRd8XhbfLjdo8wMvga8Yvt+4BHgRUkPAMeB87YPAOeL5WQXewq2vWH7YvH8N2CVYfH1YeB08bLTwJNRQXaZiXKwpCXgQeAz4E7bGzD8EIA7xuyzImkgabC5uVkt2g5SWrCkW4D3gZdt/1p2v6xwL4GkmxjKfdf2B8Xqq5IWiu0LwC8xIXabMmcRAt4BVm2/tWPTWeBo8fwo8GH94XWfMqVTh4DngC8lXSrWvQq8Drwn6XngB+DpmBC7zZ6CbX/K6DuKAB6tN5z+kVdywaTgYGZWvtqHiva8R6MFpOBgUnAwKTiYmX3J9e1ejHHkDA4mBQeTgoNJwcGk4GBScDBT902bajBpE/gD2Gps0OmZo3yc99ge+XtYo4IBJA1sj++D1RLqijNTRDApOJhZCD4xgzGnoZY4G8/B/zcyRQSTgoNpTHCbmzlfp0T3NUk/SbpU/D0x8bGbyMFtb+ZclH4t2L4o6Vbgc4bVos8Av9t+Y9pjNzWD/23mbPtPYLuZcyu4ToluZZoSPKqZcy1voG52legCHJP0haRT01TxNyW4VDPnWTOiRPdt4D7gILABvDnpMZsS3PpmzqNKdG1ftf2X7b+BkwxT3UQ0JbjVzZzHlehu1z8XPAV8NemxG/lVuQPNnMeV6B6RdJBhOlsDXpj0wHmpHExeyQWTgoNJwcGk4GBScDApOJgUHMw/vjsvtlyWb2UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 97 , Latex: \\forall , Confidence Score: 64.37 %\n",
      "Symbol_id: 60 , Latex: y , Confidence Score: 32.37 %\n",
      "Symbol_id: 98 , Latex: \\exists , Confidence Score: 1.93 %\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAEN0lEQVR4nO2cP4gcZRjGf49RKy2UO+XQnCeSQqsIiwqWIohNtFBMISmEszCgYBOsLC3UVogYSCGIoGCKgEiwsZGsIajxUIMcenrEu8o/jUQfi52TZZ3d252Zd3a+zfeD43Zmdr7vvWeffef7Zt77ZJtMHNfNO4BFJwscTBY4mCxwMFngYLLAwdQSWNJjkr6VdFnSiaaCWiRUdRws6QDwHfAosAWcB47a/qa58NLn+hrnPgBctv0DgKT3gCPAWIGXlpa8trZWo8tusrm5ye7ursqO1RH4DuCnoe0t4MHRN0laB9YBVldX6ff7NbrsJr1eb+yxOjm47BP7X76xfdJ2z3ZveXm5RndpUsfBW8DBoe07gV/qhTNAKv22AdDWvZOmYqjj4PPAIUl3S7oReAY4U6O9haSyg21flXQc+Bg4AJyyfamxyBaEOikC22eBsw3FspDkmVwwWeBgssDB1MrBUewNg8qGSqP7mh62NT1EzA4OptMC225tYhFFpwVeBLLAwSQhcMppIgmBUyZ5gScNq7pA8gJ3nU5ONNom8v5zdnAwyTh41EnDrouePtchGYFnoewrPy/Rc4oIJlkHlzly0sVqXsO57OBgknVwGZPuI1dtqy4LJfAew+LMKnbTF8OcIoLJAg8RMZTLAgezkDl4WtqYfOzrYEkHJX0qaUPSJUkvFvtvlfSJpO+L37eER5sg06SIq8DLtu8FHgJekHQfcAI4Z/sQcK7Yzoywr8C2t21fKF7/DmwwKL4+Apwu3nYaeCIqyJSZ6SInaQ24H/gcuN32Ngw+BOC2MeesS+pL6u/s7NSLNkGmFljSTcAHwEu2f5v2vGu9wn0qgSXdwEDcd21/WOy+ImmlOL4C/BoTYtpMM4oQ8A6wYfvNoUNngGPF62PAR82HVx1JY6fJbVYMTTMOfhh4FvhK0sVi3yvAa8D7kp4DfgSeigkxbfYV2PZnlP9HEcAjzYYTx7yeaCzUTK6LNRL5XkQwyTt40oWsC2QHB5Ocg7uYZyeRhMDzfuxTh5wigumkg1N27CjZwcHM3cFVL1pddu0w2cHBzN3BqTixKtnBwWSBg6m8blqlzqQd4E9gt7VOq7PE9HHeZbv0eVirAgNI6tsevw5WR2gqzpwigskCBzMPgU/Ooc8qNBJn6zn4WiOniGCywMG0JnCXF3OeUKL7qqSfJV0sfh6fue02cnDXF3MuSr9WbF+QdDPwBYNq0aeBP2y/XrXtthz832LOtv8C9hZz7gQTSnRr05bAZYs5N/IHNM1IiS7AcUlfSjpVpYq/LYGnWsx53pSU6L4F3AMcBraBN2Ztsy2BwxZzboqyEl3bV2z/bfsf4G0GqW4m2hK404s5jyvR3at/LngS+HrWtlt5opHAYs7jSnSPSjrMIJ1tAs/P2nCeKgeTZ3LBZIGDyQIHkwUOJgscTBY4mCxwMP8CetFuxq6+e1wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 90 , Latex: \\% , Confidence Score: 99.98 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 92 , Latex: \\times , Confidence Score: 99.95 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 5\n",
      "Image path:  Datasets/Object_Detection/test\\exp0044.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 47 , Latex: k , Confidence Score: 98.55 %\n",
      "Symbol_id: 10 , Latex: K , Confidence Score: 1.4 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 62 , Latex: \\Sigma , Confidence Score: 52.19 %\n",
      "Symbol_id: 90 , Latex: \\% , Confidence Score: 43.08 %\n",
      "Symbol_id: 94 , Latex: \\div , Confidence Score: 3.41 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 37 , Latex: a , Confidence Score: 38.84 %\n",
      "Symbol_id: 6 , Latex: G , Confidence Score: 28.27 %\n",
      "Symbol_id: 16 , Latex: Q , Confidence Score: 13.26 %\n",
      "Symbol_id: 88 , Latex: \\& , Confidence Score: 12.66 %\n",
      "Symbol_id: 85 , Latex: \\$ , Confidence Score: 6.05 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 84 , Latex: + , Confidence Score: 99.58 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 85 , Latex: \\$ , Confidence Score: 99.99 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 81 , Latex: \\supset , Confidence Score: 53.35 %\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 26.88 %\n",
      "Symbol_id: 31 , Latex: 5 , Confidence Score: 7.75 %\n",
      "Symbol_id: 51 , Latex: o , Confidence Score: 2.8 %\n",
      "Symbol_id: 65 , Latex: \\Delta , Confidence Score: 2.18 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 85 , Latex: \\$ , Confidence Score: 43.98 %\n",
      "Symbol_id: 63 , Latex: \\gamma , Confidence Score: 14.16 %\n",
      "Symbol_id: 90 , Latex: \\% , Confidence Score: 10.77 %\n",
      "Symbol_id: 6 , Latex: G , Confidence Score: 10.5 %\n",
      "Symbol_id: 29 , Latex: 3 , Confidence Score: 9.98 %\n",
      "Symbol_id: 76 , Latex: \\leq , Confidence Score: 2.5 %\n",
      "Symbol_id: 45 , Latex: i , Confidence Score: 1.88 %\n",
      "Symbol_id: 94 , Latex: \\div , Confidence Score: 1.14 %\n",
      "Symbol_id: 55 , Latex: s , Confidence Score: 1.12 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 90 , Latex: \\% , Confidence Score: 87.67 %\n",
      "Symbol_id: 89 , Latex: \\# , Confidence Score: 12.26 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 49 , Latex: m , Confidence Score: 72.47 %\n",
      "Symbol_id: 50 , Latex: n , Confidence Score: 26.25 %\n",
      "Symbol_id: 12 , Latex: M , Confidence Score: 1.02 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 9\n",
      "Image path:  Datasets/Object_Detection/test\\exp0051.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 30 , Latex: 4 , Confidence Score: 72.19 %\n",
      "Symbol_id: 0 , Latex: A , Confidence Score: 13.38 %\n",
      "Symbol_id: 89 , Latex: \\# , Confidence Score: 11.92 %\n",
      "Symbol_id: 90 , Latex: \\% , Confidence Score: 1.5 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 62 , Latex: \\Sigma , Confidence Score: 44.21 %\n",
      "Symbol_id: 76 , Latex: \\leq , Confidence Score: 21.53 %\n",
      "Symbol_id: 94 , Latex: \\div , Confidence Score: 14.0 %\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 7.56 %\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 5.0 %\n",
      "Symbol_id: 25 , Latex: Z , Confidence Score: 3.18 %\n",
      "Symbol_id: 90 , Latex: \\% , Confidence Score: 1.41 %\n",
      "Symbol_id: 98 , Latex: \\exists , Confidence Score: 1.01 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 28 , Latex: 2 , Confidence Score: 99.93 %\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAEaklEQVR4nO2cP4hcVRTGf59RKy2UjbJo1hVJoVVkFhUsRRCbaKGYQlIIa2FAwSZYWVqobSBiIIUggoIpAiLBxkYyE4IaFzXIoqtL3K3800j0WMxbGcY3M+/fue/N7PnBsDPz5t175tuP8+6798yVmRH4cUPbASw6IbAzIbAzIbAzIbAzIbAztQSW9ISkbyVdlXSyqaAWCVUdB0s6AHwHPA5sAReBY2b2TXPhzT831jj3IeCqmf0AIOl94CgwUeClpSVbXV0t3dFgMCh9Tq/XK31OVTY3N9nd3VXesToC3wX8NPJ6C3h4/EOS1oF1gJWVFfr9fumOpNzYp1Kln6qsra1NPFYnB+d96//lGzM7bWZrZrZ28ODBGt3NJ3UcvAUcGnl9N/BLvXCGVHHsrDbamnOp4+CLwGFJ90q6GXgOONdMWItDZQeb2XVJJ4BPgAPAGTO7UrW9Wa4t68Dx9vLaT+HqOikCMzsPnG8oloWklsBN4OWs8Tby+knh6rhVdqY1B0/KuV55cbTdafm+6dFH6ylij5TDqGl95V0c68QWKcKZpA4eDAaN3ER4sufW0TjrpI1wsDOdycFdo+hFcRbhYGdCYGeSCtzr9TCz3MeiEg52JgSeQd1hZQjsTAzTJtDUTFsIPEbTU5iRIpwJgUfwmIAPgZ2JHIzv0tG+FjjW5BaAfenglOuB4WBn9o2Dp80peM7mzXSwpEOSPpO0IemKpJez92+X9Kmk77O/t7lFOccUSRHXgVfN7H7gEeAlSQ8AJ4ELZnYYuJC97hySchctU81FzxTYzLbN7FL2/Hdgg2Hx9VHgbPaxs8BTXkFWIU9YSF/GWuoiJ2kVeBD4ArjTzLZh+E8A7phwzrqkvqT+zs5OvWjnkMICS7oF+BB4xcx+K3peGxXuk5zbxtJUIYEl3cRQ3PfM7KPs7WuSlrPjy8CvPiHON0VGEQLeBTbM7O2RQ+eA49nz48DHzYdXjL18O+2C1hZFxsGPAs8DX0m6nL33GvAG8IGkF4AfgWd8QpxvZgpsZp+T/4sigMeaDac8XRgpTGPu7uTauiOrSsxFODM3Dk5dEd8U4WBnOu3gecu3eXRO4K5XwJclUoQzrTt40Rw7TjjYmc79EDHV+U1Q5EIbDnYmBHYmBHYmBHam8r5plTqTdoA/gd1knVZnieJx3mNmuethSQUGkNQ3s8n7YHWEpuKMFOFMCOxMGwKfbqHPKjQSZ/IcvN+IFOFMCOxMMoG7vJnzlBLd1yX9LOly9niydNspcnDXN3POSr+WzeySpFuBAcNq0WeBP8zszaptp3Lwf5s5m9lfwN5mzp1gSolubVIJnLeZcyNfoGnGSnQBTkj6UtKZKlX8qQQutJlz2+SU6J4C7gOOANvAW2XbTCWw22bOTZFXomtm18zsbzP7B3iHYaorRSqBO72Z86QS3b3654ynga/Ltp1kTa7pzZwdmFSie0zSEYbpbBN4sWzDcavsTNzJORMCOxMCOxMCOxMCOxMCOxMCO/Mv8dKkQMfK0BgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 25 , Latex: Z , Confidence Score: 96.7 %\n",
      "Symbol_id: 90 , Latex: \\% , Confidence Score: 1.16 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 4\n",
      "Image path:  Datasets/Object_Detection/test\\exp9.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 92 , Latex: \\times , Confidence Score: 96.34 %\n",
      "Symbol_id: 93 , Latex: \\ast , Confidence Score: 2.54 %\n",
      "Symbol_id: 59 , Latex: x , Confidence Score: 1.11 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 84 , Latex: + , Confidence Score: 99.94 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 77 , Latex: \\geq , Confidence Score: 64.55 %\n",
      "Symbol_id: 62 , Latex: \\Sigma , Confidence Score: 32.26 %\n",
      "Symbol_id: 85 , Latex: \\$ , Confidence Score: 2.32 %\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAEYElEQVR4nO2cP4gcVRzHP1+jVlood8qhOU8khVYRFg1YiiA20UIxhaQQzsKAgk2wsrRQWyHBQIqACAmYIiASbGwkawhqPNQgh54e8a7yTyPRn8XOyrKZ2ZuZN7/ZN7PvA8vtzOy897vvfe/33sz89snMSPhxy7wD6DtJYGeSwM4kgZ1JAjuTBHYmSGBJT0v6TtI1ScebCqpPqO48WNI+4HvgKWALuAQcMbNvmwuv+9wacO5jwDUz+xFA0ofAYaBQ4KWlJVtbWwvoMk42NzfZ3d1V3rEQge8Dfp7Y3gIen/6QpHVgHWB1dZXhcBjQZZwMBoPCYyE5OO8vdlO+MbMTZjYws8Hy8nJAd90kxMFbwP6J7fuBX+s2JuX+h92E570TjxhCHHwJOCDpQUm3Ay8C5wPa6yW1HWxmNyQdAz4B9gGnzOxqY5EVMHaZl5NntVvW4ZOEpAjM7AJwIaSNvhPNlZyZVXKlpFqOaptoBO4r0QlcNbfG7uKgHOxFnsizhPQe+EKIzsF9o1cCxzjw9UrgGIkyB+cxnV9jc2oRnRG4CpPiz3vgSynCmc46eOzMvVJF3vE2XZ0c7ExnHTxm0o1lB742B8jkYGc67+BJ6rjZm14JPEks8+aUIpzprYOnqXqHrimSg51ZGAfn0UaeXmiByxIifEoRziQHTzHLrXXuYSQHO7OQDq6aU0Puvu3pYEn7JX0maUPSVUmvZfvvlvSppB+yn3fVjqLHlEkRN4A3zOxh4BDwqqRHgOPARTM7AFzMtqNn+mnH9Gua0HvHewpsZttmdjl7/wewwaj4+jBwOvvYaeDZoEhapEyZVtVSriIqDXKS1oBHgS+Ae81sOwtmG7in4Jx1SUNJw52dnbBoO0hpgSXdAZwFXjez38uet+gV7qUElnQbI3HPmNm5bPd1SSvZ8RXgN58Qu02ZWYSAD4ANM3tv4tB54Gj2/ijwcfPhdZ8y8+AngJeAryVdyfa9CbwNfCTpZeAn4HmfELvNngKb2efkf6MI4Mlmw2mevIuKNp9uLOSVXBEe9RLpXoQzSWBnksDO9CoH1x28PGvVOidwkzOANooAU4pwphMObnremspXe0SUDm7CsfP+6sCY5GBnonRwLO5rguRgZ5LAztReN61WZ9IO8Bew21qn9VmifJwPmFnu87BWBQaQNDSz4nWwIqGpOFOKcCYJ7Mw8BD4xhz7r0EicrefgRSOlCGeSwM60JnDMiznPKNF9S9Ivkq5kr2cqt91GDo59Mees9GvFzC5LuhP4klG16AvAn2b2Tt2223Lw/4s5m9nfwHgx5yiYUaIbTFsC5y3m3Mgv0DRTJboAxyR9JelUnSr+tgQutZjzvMkp0X0feAg4CGwD71Ztsy2BG13M2YO8El0zu25m/5jZv8BJRqmuEm0JHPVizkUluuP654zngG+qtt3KE415LeZcgaIS3SOSDjJKZ5vAK1UbTpfKzqQrOWeSwM4kgZ1JAjuTBHYmCexMEtiZ/wCaH4nMFabBFwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 77 , Latex: \\geq , Confidence Score: 88.44 %\n",
      "Symbol_id: 104 , Latex: = , Confidence Score: 8.22 %\n",
      "Symbol_id: 62 , Latex: \\Sigma , Confidence Score: 3.24 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN/ANN Predictions:\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 93.76 %\n",
      "Symbol_id: 25 , Latex: Z , Confidence Score: 5.91 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 5\n"
     ]
    }
   ],
   "source": [
    "for i in image_paths:\n",
    "    image = cv2.imread(i)\n",
    "    print('Image path: ', i)\n",
    "    plt.figure(figsize=(5,5))\n",
    "    plt.imshow(image)\n",
    "    plt.show()\n",
    "    \n",
    "    # Image Preprocessing\n",
    "    # Remove Noise\n",
    "    image = cv2.fastNlMeansDenoisingColored(image,None,10,10,7,21)\n",
    "    \n",
    "    # Change color channel to Grayscale\n",
    "    gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    # Convert not so faint pixels to black and others to white \n",
    "    res,thresh = cv2.threshold(gray,200,255,cv2.THRESH_BINARY_INV) #threshold \n",
    "    \n",
    "    # Structuring Element\n",
    "    kernel = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3)) \n",
    "    \n",
    "    # Lower the thickness of features\n",
    "    dilated = cv2.dilate(thresh,kernel,iterations = 5) \n",
    "    \n",
    "    # Find countours/features and draw bounding box around them\n",
    "    val,contours, hierarchy = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) \n",
    "    coord = []\n",
    "    for contour in contours:  \n",
    "        [x,y,w,h] = cv2.boundingRect(contour)   \n",
    "        if h>300 and w>300:   \n",
    "            continue   \n",
    "        if h<7 or w<7:   \n",
    "            continue  \n",
    "        coord.append((x,y,w,h)) \n",
    "    \n",
    "    # if the image has only one sentence sort in one axis\n",
    "    coord.sort(key=lambda tup:tup[0]) \n",
    "    \n",
    "    # crop the bounding boxes and detect labels for them\n",
    "    count = 0\n",
    "    for cor in coord:\n",
    "        [x,y,w,h] = cor\n",
    "        \n",
    "        # crop image\n",
    "        t = image[y:y+h,x:x+w,:]\n",
    "        \n",
    "        # remove extra whitespace layer around feature\n",
    "        t = remove_wspaces(t)\n",
    "        \n",
    "        # resize image to 32 x 32\n",
    "        t = cv2.resize(t, (32,32))\n",
    "        \n",
    "        # convert to a binary array (contains either 0 or 1)\n",
    "        _, t = cv2.threshold(t,200,255,cv2.THRESH_BINARY)\n",
    "        \n",
    "        # edge detection to remove noise\n",
    "        t = cv2.Laplacian(t,cv2.CV_64F, ksize=3)\n",
    "        \n",
    "        # fill any gaps inside feature lost during edge detection\n",
    "        kernel = np.ones((3,3),np.uint8)\n",
    "        t = cv2.morphologyEx(t, cv2.MORPH_CLOSE, kernel)\n",
    "        #\n",
    "        \n",
    "        # Erosion area (output is too thin (around 1 px)) \n",
    "        # Both CNN/ANN were not able to detect features because of this method\n",
    "        # kernel = np.ones((2,2),np.uint8)\n",
    "        #t = cv2.erode(t,kernel,iterations = 1)\n",
    "        #\n",
    "        \n",
    "        # invert inverted image to white background and black features\n",
    "        t = 255 - t\n",
    "        \n",
    "        # this line is used to reset all values to 0 or 255\n",
    "        _, t = cv2.threshold(t,50,255,cv2.THRESH_BINARY)\n",
    "                \n",
    "        # Convert image to numpy array (uint8 since fatures are 255/0)\n",
    "        # If image contains values as 0 to 255, they should be in integers \n",
    "        # (uint8 takes values between 0 and 255)\n",
    "        # If image contains values as 0 or 1, they should be in float\n",
    "        t_im = np.asarray(t).astype('uint8')\n",
    "        \n",
    "        # Change Color channels to grayscale\n",
    "        #t_im = cv2.cvtColor(t_im, cv2.COLOR_BGRA2RGBA)\n",
    "        #t_im = cv2.cvtColor(t_im, cv2.COLOR_RGBA2RGB)\n",
    "        #t_im = cv2.cvtColor(t_im, cv2.COLOR_BGR2RGB)\n",
    "        t_im = cv2.cvtColor(t_im, cv2.COLOR_RGB2GRAY)\n",
    "        \n",
    "        # resize image to 32 x 32 (not required but just to ensure image is 32 x 32)\n",
    "        t_im = cv2.resize(t_im, (32,32))\n",
    "        \n",
    "        # change features to 0/1\n",
    "        t_im = t_im / 255.0\n",
    "        \n",
    "        # Label Prediction\n",
    "        # CNN\n",
    "        t_im = np.resize(t_im, (1, 1, 32, 32))\n",
    "        t_im = t_im.astype('float32')\n",
    "        res = cnn.predict(t_im)\n",
    "        #\n",
    "        # ANN\n",
    "        #t_im = t_im.flatten().reshape((1, 32*32))\n",
    "        #print(t_im.shape)\n",
    "        #res = ann.predict(t_im)\n",
    "        #\n",
    "        \n",
    "        # flatten result and convert one hot encoded result to a label (0 to 106)\n",
    "        res = res.flatten()\n",
    "        # lbl = one_hot_encode_to_char(res, threshold=0.1)\n",
    "        # if type(lbl) == list: lbl = lbl[0]\n",
    "        # print(\"Symbol is :\", symbols.loc[symbols['new_id']==lbl])\n",
    "        lbls = one_hot_encode_to_char_list(res, threshold=0.01, get_max = False)\n",
    "        \n",
    "        # Print Predictions\n",
    "        print(\"CNN/ANN Predictions:\")\n",
    "        for j in lbls:\n",
    "            symbols_row = symbols[symbols['new_id'] == j[0]][['latex', 'old_symbol', 'new_id']]\n",
    "            latex, old_symbol, new_id = symbols_row.iloc[0].to_list()\n",
    "            print('Symbol_id:', new_id, ', Latex:', latex, ', Confidence Score:', round(j[1]*100, 2), '%')\n",
    "\n",
    "        # Display figure\n",
    "        plt.figure(figsize=(1,1))\n",
    "        # plt.subplot(len(coord),1, count+1)\n",
    "        plt.imshow(t.astype('uint8'))\n",
    "        plt.show()\n",
    "        count += 1\n",
    "    print(\"number of char in image:\", count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example showing the output after each image processing technique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Image path:  Datasets/Object_Detection/test\\exp0015.png\n",
      "Original Image\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after denoising\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after changing color channel\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after changing color\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Structuring element\n",
      "array([[0, 1, 0],\n",
      "       [1, 1, 1],\n",
      "       [0, 1, 0]], dtype=uint8)\n",
      "after dilation\n"
     ]
    },
    {
     "data": {
      "image/png": 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UAlubLiBpQx1tqAFcx0Tzso7W7BMws2a0qSdgZg1oPAQkXSPpSBqnYEvNyz4q6RVJ+yXtS22LJe1J4ynskXReBcvdJumkpINdbT2Xq8K9af0ckLSq4jrukPR2Wif7Ja3ruu32VMcRSWtLrGO5pKclHU5jW9yS2mtdJ1PUUes6qX2sj4ho7A9YQPHLxZcCZwAvA5fVuPyjwPkT2v4O2JKmtwBfq2C5nwFWAQenWy6wDvgXih9wXQM8V3EddwB/0WPey9LrMwSsSK/bgpLqWAKsStPnAD9Iy6t1nUxRR63rJD2vs9P0QuC59Dx3AhtS+9eBP0vTfw58PU1vAB6eyfKa7gmsBsYi4vWI+Bmwg2LcgiZ1j5vQPZ5CaSLiGT7646uTLXc98EAUnqX4gdclFdYxmfXAjog4FRFvAGP0+GWpWdZxPCJeStPvU/yG5VJqXidT1DGZStZJel61jfXRdAj8YoyCpHv8gjoE8B1JL0oaTW0XRcRxKN4UwIU11TLZcptYRzenbva2rs2hWupIXdnLKb79GlsnE+qAmtdJnWN9NB0CfY1RUKErI2IVcC2wWdJnalx2v+peR/cBn6AYcu44cFdddUg6G3gUuDUi3ptq1ipr6VFH7eskKhjrYzJNh8AvxihIuscvqFxEHEuXJ4HHKVb2iU7XMl2erKmcyZZb6zqKiBPpDfhz4Bv8sntbaR2SFlJ88B6MiMdSc+3rpFcdTa2TtOzSxvqYTNMh8AIwnPZ6nkGxU2NXHQuWdJakczrTwOeAg/zquAnd4ylUbbLl7gJuSnvE1wDvdrrIVZiwbX09xTrp1LEh7YleAQwDz5e0TFH8VP3hiLi766Za18lkddS9TlT3WB9l7FUdcE/oOoq9sD8Evlzjci+l2LP7MnCos2yKbam9wGvpcnEFy36Iolv5AUWKb5psuRRdvX9I6+cVYKTiOr6VlnMgvbmWdM3/5VTHEeDaEuv4fYru6wFgf/pbV/c6maKOWtcJ8HsUY3kcoAicv+x6zz5PsQPyn4Gh1L4oXR9Lt186k+X5jEGzzDW9OWBmDXMImGXOIWCWOYeAWeYcAmaZcwiYZc4hYJY5h4BZ5v4fD1qm8lQianAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After contour search\n",
      "contours:  6\n",
      "hierarchy:  [[[ 1 -1 -1 -1]\n",
      "  [ 2  0 -1 -1]\n",
      "  [ 3  1 -1 -1]\n",
      "  [ 4  2 -1 -1]\n",
      "  [ 5  3 -1 -1]\n",
      "  [-1  4 -1 -1]]]\n",
      "predicted bboxes [(84, 164, 40, 12), (78, 151, 36, 12), (126, 138, 56, 42), (11, 138, 51, 44), (191, 136, 43, 41), (252, 133, 36, 40)]\n",
      "orted bboxes [(11, 138, 51, 44), (78, 151, 36, 12), (84, 164, 40, 12), (126, 138, 56, 42), (191, 136, 43, 41), (252, 133, 36, 40)]\n",
      "cropped images\n"
     ]
    },
    {
     "data": {
      "image/png": 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xDF29z3a355f+Pg/zfvLMaknNeWa1pOYMIknNGUSSmjOIJDVnEElqziCS1JxBJKk5g0hSc/8L2e2nAe6fvDcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after removing whitespaces\n"
     ]
    },
    {
     "data": {
      "image/png": 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j3e9zafoJ/Abwra6PJ4C/7Np/BfgG8ATwT8ArF13rlPr7ZuCeFvro5SCSmuAnsCU1wTCS1ATDSFITDCNJTTCMJDXBMJLUBMNIUhP+H/VoIPIGK3H8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after resizing to 32 x 32\n"
     ]
    },
    {
     "data": {
      "image/png": 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vkyImeW1F2GtdDaJVpwROc/cZwLnAL81M08rAMmAK1WsE9AP3lrViMzsSeBZY4O5fl7XeOvoofZt4jkleU1oR9h3A5CH3k5NVFs3dd2a/dwPP0dqZd3aZWQdA9nt3K5pw913ZH9og8AglbRMzO4RqwFa5+5psuPRtUquPVm2TbN2jnuQ1pRVhfxs4MTuyOA6YC6wtuwkzO8LMjtp7G/g5sHX4RxVqLdWJO6GFE3juDVfmYkrYJla99tejwHZ3v29IqdRtkuqj7G1S2CSvZR1h3O9o43lUj3T+HljSoh5+TPVMwHvAB2X2ATxJ9eXg/1J9pXMNMAHYAHyc/R7foj7+HXgf2EI1bB0l9PG3VF+SbgE2Zz/nlb1Nhumj1G0C/A3VSVy3UP3H8k9D/mZ/B3wC/Adw6GieV5+gEwlCn6ATCUJhFwlCYRcJQmEXCUJhFwlCYRcJQmEXCUJhFwni/wACVNpiqlRMEgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after getting theshold \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"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after edge detection\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"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after filling gaps\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"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after inverting and getting threshold\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before character classification\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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "array([[1., 1., 0., ..., 1., 1., 1.],\n",
      "       [1., 1., 0., ..., 1., 1., 1.],\n",
      "       [0., 0., 0., ..., 1., 1., 1.],\n",
      "       ...,\n",
      "       [1., 1., 1., ..., 1., 1., 1.],\n",
      "       [1., 1., 1., ..., 1., 1., 1.],\n",
      "       [1., 1., 1., ..., 1., 1., 1.]])\n",
      "CNN/ANN Predictions:\n",
      "Symbol_id: 61 , Latex: z , Confidence Score: 99.62 %\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 72x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of char in image: 1\n"
     ]
    }
   ],
   "source": [
    "for i in image_paths:\n",
    "    image = cv2.imread(i)\n",
    "    print('Image path: ', i)\n",
    "    print(\"Original Image\")\n",
    "    plt.figure()\n",
    "    plt.imshow(image)\n",
    "    plt.show()\n",
    "    \n",
    "    # Image Preprocessing\n",
    "    # Remove Noise\n",
    "    image = cv2.fastNlMeansDenoisingColored(image,None,10,10,7,21)\n",
    "    print('after denoising')\n",
    "    plt.imshow(image)\n",
    "    plt.show()\n",
    "    \n",
    "    # Change color channel to Grayscale\n",
    "    gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)\n",
    "    print('after changing color channel')\n",
    "    plt.imshow(gray)\n",
    "    plt.show()\n",
    "    \n",
    "    # Convert not so faint pixels to black and others to white \n",
    "    res,thresh = cv2.threshold(gray,200,255,cv2.THRESH_BINARY_INV) #threshold \n",
    "    print('after changing color')\n",
    "    plt.imshow(thresh)\n",
    "    plt.show()\n",
    "    \n",
    "    # Structuring Element\n",
    "    kernel = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3)) \n",
    "    print('Structuring element')\n",
    "    pprint(kernel)\n",
    "    \n",
    "    # Lower the thickness of features\n",
    "    dilated = cv2.dilate(thresh,kernel,iterations = 5) \n",
    "    print('after dilation')\n",
    "    plt.imshow(dilated)\n",
    "    plt.show()\n",
    "    \n",
    "    # Find countours/features and draw bounding box around them\n",
    "    val,contours, hierarchy = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) \n",
    "    coord = []\n",
    "    for contour in contours:  \n",
    "        [x,y,w,h] = cv2.boundingRect(contour)   \n",
    "        if h>300 and w>300:   \n",
    "            continue   \n",
    "        if h<7 or w<7:   \n",
    "            continue  \n",
    "        coord.append((x,y,w,h))\n",
    "    \n",
    "    print('After contour search')\n",
    "    # print('val: ', val.shape)\n",
    "    print('contours: ', len(contours))\n",
    "    print('hierarchy: ', hierarchy)\n",
    "    print('predicted bboxes', coord)\n",
    "    \n",
    "    # if the image has only one sentence sort in one axis\n",
    "    coord.sort(key=lambda tup:tup[0]) \n",
    "    \n",
    "    print('orted bboxes', coord)\n",
    "    \n",
    "    # crop the bounding boxes and detect labels for them\n",
    "    count = 0\n",
    "    for cor in coord:\n",
    "        [x,y,w,h] = cor\n",
    "        \n",
    "        # crop image\n",
    "        t = image[y:y+h,x:x+w,:]\n",
    "        print('cropped images')\n",
    "        plt.imshow(t)\n",
    "        plt.show()\n",
    "    \n",
    "        # remove extra whitespace layer around feature\n",
    "        t = remove_wspaces(t)\n",
    "        print('after removing whitespaces')\n",
    "        plt.imshow(t)\n",
    "        plt.show()\n",
    "    \n",
    "        # resize image to 32 x 32\n",
    "        t = cv2.resize(t, (32,32))\n",
    "        print('after resizing to 32 x 32')\n",
    "        plt.imshow(t)\n",
    "        plt.show()\n",
    "    \n",
    "        # convert to a binary array (contains either 0 or 1)\n",
    "        _, t = cv2.threshold(t,200,255,cv2.THRESH_BINARY)\n",
    "        print('after getting theshold ')\n",
    "        plt.imshow(t)\n",
    "        plt.show()\n",
    "    \n",
    "        # edge detection to remove noise\n",
    "        t = cv2.Laplacian(t,cv2.CV_64F, ksize=3)\n",
    "        print('after edge detection')\n",
    "        plt.imshow(t)\n",
    "        plt.show()\n",
    "    \n",
    "        \n",
    "        # fill any gaps inside feature lost during edge detection\n",
    "        kernel = np.ones((3,3),np.uint8)\n",
    "        t = cv2.morphologyEx(t, cv2.MORPH_CLOSE, kernel)\n",
    "        #\n",
    "        print('after filling gaps')\n",
    "        plt.imshow(t)\n",
    "        plt.show()\n",
    "    \n",
    "        \n",
    "        # Erosion area (output is too thin (around 1 px)) \n",
    "        # Both CNN/ANN were not able to detect features because of this method\n",
    "        # kernel = np.ones((2,2),np.uint8)\n",
    "        #t = cv2.erode(t,kernel,iterations = 1)\n",
    "        #\n",
    "        \n",
    "        # invert inverted image to white background and black features\n",
    "        t = 255 - t\n",
    "        \n",
    "        # this line is used to reset all values to 0 or 255\n",
    "        _, t = cv2.threshold(t,50,255,cv2.THRESH_BINARY)\n",
    "        print('after inverting and getting threshold')\n",
    "        plt.imshow(t)\n",
    "        plt.show()\n",
    "    \n",
    "        # Convert image to numpy array (uint8 since fatures are 255/0)\n",
    "        # If image contains values as 0 to 255, they should be in integers \n",
    "        # (uint8 takes values between 0 and 255)\n",
    "        # If image contains values as 0 or 1, they should be in float\n",
    "        t_im = np.asarray(t).astype('uint8')\n",
    "        \n",
    "        # Change Color channels to grayscale\n",
    "        #t_im = cv2.cvtColor(t_im, cv2.COLOR_BGRA2RGBA)\n",
    "        #t_im = cv2.cvtColor(t_im, cv2.COLOR_RGBA2RGB)\n",
    "        #t_im = cv2.cvtColor(t_im, cv2.COLOR_BGR2RGB)\n",
    "        t_im = cv2.cvtColor(t_im, cv2.COLOR_RGB2GRAY)\n",
    "        \n",
    "        # resize image to 32 x 32 (not required but just to ensure image is 32 x 32)\n",
    "        t_im = cv2.resize(t_im, (32,32))\n",
    "        \n",
    "        # change features to 0/1\n",
    "        t_im = t_im / 255.0\n",
    "        print('before character classification')\n",
    "        plt.imshow(t_im)\n",
    "        plt.show()\n",
    "        pprint(t_im)\n",
    "    \n",
    "        # Label Prediction\n",
    "        # CNN\n",
    "        t_im = np.resize(t_im, (1, 1, 32, 32))\n",
    "        t_im = t_im.astype('float32')\n",
    "        res = cnn.predict(t_im)\n",
    "        #\n",
    "        # ANN\n",
    "        #t_im = t_im.flatten().reshape((1, 32*32))\n",
    "        #print(t_im.shape)\n",
    "        #res = ann.predict(t_im)\n",
    "        #\n",
    "        \n",
    "        # flatten result and convert one hot encoded result to a label (0 to 106)\n",
    "        res = res.flatten()\n",
    "        # lbl = one_hot_encode_to_char(res, threshold=0.1)\n",
    "        # if type(lbl) == list: lbl = lbl[0]\n",
    "        # print(\"Symbol is :\", symbols.loc[symbols['new_id']==lbl])\n",
    "        lbls = one_hot_encode_to_char_list(res, threshold=0.01, get_max = False)\n",
    "        \n",
    "        # Print Predictions\n",
    "        print(\"CNN/ANN Predictions:\")\n",
    "        for j in lbls:\n",
    "            symbols_row = symbols[symbols['new_id'] == j[0]][['latex', 'old_symbol', 'new_id']]\n",
    "            latex, old_symbol, new_id = symbols_row.iloc[0].to_list()\n",
    "            print('Symbol_id:', new_id, ', Latex:', latex, ', Confidence Score:', round(j[1]*100, 2), '%')\n",
    "\n",
    "        # Display figure\n",
    "        plt.figure(figsize=(1,1))\n",
    "        # plt.subplot(len(coord),1, count+1)\n",
    "        plt.imshow(t.astype('uint8'))\n",
    "        plt.show()\n",
    "        count += 1\n",
    "        break\n",
    "    print(\"number of char in image:\", count)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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