{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# transform the image using the homography H \n",
    "# the size of the final image is decided using the bounds -> (left, top, right, bottom) \n",
    "# the left, top of the input image is translated to (0,0)\n",
    "def warp_image_with_bounds(im, H, bounds):\n",
    "    t      = [-bounds[0],-bounds[1]] # translation of left, top to (0,0)\n",
    "    Ht     = np.array([[1,0,t[0]],[0,1,t[1]],[0,0,1]]) # translation transform\n",
    "    result = cv2.warpPerspective(im, Ht.dot(H), (bounds[2]-bounds[0], bounds[3]-bounds[1]))\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reversable handler: allows images to be reversed and still work with the code\n",
    "def reverse_image(xmin, xmax, ymin, ymax, bounds):\n",
    "    for x in bounds:\n",
    "        if x[0][0] > xmax:\n",
    "            xmax = x[0][0].astype(np.int32)\n",
    "        if x[0][0] < xmin:\n",
    "            xmin = x[0][0].astype(np.int32)\n",
    "        if x[0][1] > ymax:\n",
    "            ymax = x[0][1].astype(np.int32)\n",
    "        if x[0][1] < ymin:\n",
    "            ymin = x[0][1].astype(np.int32)\n",
    "    return xmin, xmax, ymin, ymax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# find the homography between the source and destination images using the specified points\n",
    "def find_homography(im_src, im_dst):\n",
    "    # four corresponding points on source and destination image\n",
    "    pts_src = np.array([[1649.15, 298], [2293.79, 236.60], [2243.19, 2168.90], [1770.98, 2133.52]])\n",
    "    pts_dst = np.array([[495, 100], [1135, 131], [1021, 1986], [555,1995]])\n",
    "    \n",
    "    # display images and points\n",
    "    fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(20,10))\n",
    "    ax[0].imshow(im_src); ax[0].plot(pts_src[:,0], pts_src[:,1], 'ro', markersize=10); ax[0].axis('off')\n",
    "    ax[1].imshow(im_dst); ax[1].plot(pts_dst[:,0], pts_dst[:,1], 'ro', markersize=10); ax[1].axis('off')\n",
    "    plt.show()\n",
    "    \n",
    "    # compute homography between src and dst\n",
    "    # YOUR CODE HERE\n",
    "    print('Homography: ', H)\n",
    "    return H"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stitch_images(im_src, im_dst):\n",
    "    # estimate homography\n",
    "    H = find_homography(im_src, im_dst)\n",
    "    \n",
    "    # load images\n",
    "    h1, w1, d1  = im_src.shape\n",
    "    h2, w2, d2  = im_dst.shape   \n",
    "    src_corners = np.float32([[0,0],[0,h1],[w1,h1],[w1,0]]).reshape(-1,1,2) \n",
    "    dst_corners = np.float32([[0,0],[0,h2],[w2,h2],[w2,0]]).reshape(-1,1,2)\n",
    "    \n",
    "    # FIND BOUNDS OF THE STITCHED IMAGE\n",
    "    # YOUR CODE HERE\n",
    "    # [xmin, xmax, ymin, ymax] = ...\n",
    "\n",
    "    # warp the image with bounds\n",
    "    result = warp_image_with_bounds(im_src, H, [xmin, ymin, xmax, ymax])\n",
    "    \n",
    "    # place the destination image into the result\n",
    "    # YOUR CODE HERE\n",
    "    \n",
    "    # visualize the result\n",
    "    fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(20,10))\n",
    "    ax.imshow(result)\n",
    "    ax.axis('off')\n",
    "    \n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rectify(im_src):    \n",
    "    # four corresponding points on source and destination image\n",
    "    pts_src = np.array([[464.48358, 727.9149], [2370.2458, 796.1351], [2310.8284, 2484.0332], [277.4284, 2525.8455]]).astype(np.float32)\n",
    "    pts_dst = np.array([[0, 0], [2000, 0], [2000, 2000], [0, 2000]]).astype(np.float32)\n",
    "    \n",
    "    # compute homography between src and dst\n",
    "    # YOUR CODE HERE\n",
    "    \n",
    "    # compute the bounds of the output rectified image (hint: cv2.perspectiveTransform)\n",
    "    # YOUR CODE HERE\n",
    "    # [xmin, xmax, ymin, ymax] = ...\n",
    "    \n",
    "    # warp the image using the bounds\n",
    "    result = warp_image_with_bounds(im_src, H, [xmin, ymin, xmax, ymax])\n",
    "\n",
    "    # display\n",
    "    fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(20,10))\n",
    "    ax.imshow(result)\n",
    "    ax.axis('off')\n",
    "    \n",
    "    return result  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# image stitching and rectification\n",
    "\n",
    "im_src = plt.imread( 'a5-src.png' )\n",
    "im_dst = plt.imread( 'a5-dst.png' )\n",
    "stch   = stitch_images( im_src, im_dst )\n",
    "rect   = rectify(stitch)"
   ]
  }
 ],
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