{
 "cells": [
  {
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   "source": [
    "# <center>CS568:Deep Learning</center>  <center>Spring 2020</center> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Total Marks: 10**\n",
    "\n",
    "**Submission deadline: Sunday 05 April, 2020.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convolution(input_image, mask):\n",
    "    \n",
    "     # add code here\n",
    "\n",
    "    return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_image = cv2.imread('book_gray.png')\n",
    "\n",
    "averaging_filter = 1/9*np.ones((3,3))\n",
    "vertical_edge_detection = np.array([[1, 0, -1], [1, 0, -1], [1, 0, -1]])\n",
    "horizontal_edge_detection = np.array([[1, 1, 1], [0, 0, 0], [-1, -1, -1]])\n",
    "\n",
    "result_avg_filter = convolution(input_image, averaging_filter)\n",
    "result_ver_edge_detection = convolution(input_image, vertical_edge_detection)\n",
    "result_hor_edge_detection = convolution(input_image, horizontal_edge_detection)\n",
    "\n",
    "## add code here to display output images\n",
    "## add code here to save images"
   ]
  }
 ],
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