Laplacian-energy.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import cv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "laplacian = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "laplacian.append(np.zeros((5,5),dtype=np.uint8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0]], dtype=uint8)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "laplacian[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "laplacian[0][2,2] = 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0],\n",
       "       [  0,   0, 255,   0,   0],\n",
       "       [  0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0]], dtype=uint8)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "laplacian[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#A = cv2.imread('lena.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.ndarray'>\n"
     ]
    }
   ],
   "source": [
    "print(type(laplacian[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for i in range(5):\n",
    "    interpolation = cv2.pyrUp(laplacian[i])\n",
    "    laplacian.append(interpolation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0],\n",
       "       [  0,   0, 255,   0,   0],\n",
       "       [  0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0]], dtype=uint8)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "laplacian[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   4,  16,  24,  16,   4,   0,   0,   0],\n",
       "       [  0,   0,  16,  64,  96,  64,  16,   0,   0,   0],\n",
       "       [  0,   0,  24,  96, 143,  96,  24,   0,   0,   0],\n",
       "       [  0,   0,  16,  64,  96,  64,  16,   0,   0,   0],\n",
       "       [  0,   0,   4,  16,  24,  16,   4,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0]], dtype=uint8)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "laplacian[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   1,   1,   2,   3,   3,   3,   2,   1,   1,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   1,   3,   5,   8,  10,  11,  10,   8,   5,   3,\n",
       "          1,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   1,   3,   6,  13,  19,  25,  28,  25,  19,  13,   6,\n",
       "          3,   1,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   1,   5,  13,  25,  39,  50,  55,  50,  39,  25,  13,\n",
       "          5,   1,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   2,   8,  19,  39,  60,  77,  85,  77,  60,  39,  19,\n",
       "          8,   2,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   3,  10,  25,  50,  77, 100, 110, 100,  77,  50,  25,\n",
       "         10,   3,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   3,  11,  28,  55,  85, 110, 120, 110,  85,  55,  28,\n",
       "         11,   3,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   3,  10,  25,  50,  77, 100, 110, 100,  77,  50,  25,\n",
       "         10,   3,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   2,   8,  19,  39,  60,  77,  85,  77,  60,  39,  19,\n",
       "          8,   2,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   1,   5,  13,  25,  39,  50,  55,  50,  39,  25,  13,\n",
       "          5,   1,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   1,   3,   6,  13,  19,  25,  28,  25,  19,  13,   6,\n",
       "          3,   1,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   1,   3,   5,   8,  10,  11,  10,   8,   5,   3,\n",
       "          1,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   1,   1,   2,   3,   3,   3,   2,   1,   1,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
       "          0,   0,   0,   0,   0,   0,   0],\n",
       "       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
       "          0,   0,   0,   0,   0,   0,   0]], dtype=uint8)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "laplacian[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "255"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "laplacian[0].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1023"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "laplacian[1].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
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