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Use builtin jupyter notebook to show table
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‎tutorials/Tutorial1-Introduction.ipynb

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@@ -90,7 +90,7 @@
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{
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"data": {
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"text/plain": [
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"<matplotlib.image.AxesImage at 0x206c10fec88>"
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"<matplotlib.image.AxesImage at 0x1c8c6201dc8>"
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]
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},
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"execution_count": 3,
@@ -133,7 +133,7 @@
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{
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"data": {
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"text/plain": [
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"<matplotlib.image.AxesImage at 0x206c11c8b88>"
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"<matplotlib.image.AxesImage at 0x1c8c62d0708>"
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]
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},
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"execution_count": 4,
@@ -199,32 +199,178 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Found 18 hits\n",
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" TemplateName BBox Score\n",
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"0 small [80, 37, 41, 38] 1.000000\n",
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"1 small [133, 108, 41, 38] 0.860808\n",
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"2 small [134, 178, 41, 38] 0.816142\n",
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"3 small [82, 106, 41, 38] 0.800473\n",
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"4 small [316, 105, 41, 38] 0.747887\n",
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"5 small [23, 178, 41, 38] 0.742242\n",
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"6 small [185, 103, 41, 38] 0.685315\n",
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"7 small [257, 34, 41, 38] 0.657858\n",
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"8 small [26, 103, 41, 38] 0.617951\n",
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"9 small [22, 37, 41, 38] 0.606692\n",
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"10 small [335, 247, 41, 38] 0.585767\n",
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"11 small [227, 239, 41, 38] 0.578679\n",
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"12 small [95, 244, 41, 38] 0.576981\n",
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"13 small [286, 237, 41, 38] 0.543841\n",
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"14 small [251, 106, 41, 38] 0.525461\n",
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"15 small [157, 234, 41, 38] 0.524984\n",
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"16 small [134, 37, 41, 38] 0.511434\n",
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"17 small [196, 27, 41, 38] 0.506831\n"
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"Found 18 hits\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>TemplateName</th>\n",
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" <th>BBox</th>\n",
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" <th>Score</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>small</td>\n",
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" <td>[80, 37, 41, 38]</td>\n",
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" <td>1.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>small</td>\n",
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" <td>[133, 108, 41, 38]</td>\n",
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" <td>0.860808</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>small</td>\n",
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" <td>[134, 178, 41, 38]</td>\n",
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" <td>0.816142</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>small</td>\n",
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" <td>[82, 106, 41, 38]</td>\n",
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" <td>0.800473</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>small</td>\n",
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" <td>[316, 105, 41, 38]</td>\n",
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" <td>0.747887</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td>small</td>\n",
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" <td>[23, 178, 41, 38]</td>\n",
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" <td>0.742242</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>small</td>\n",
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" <td>[185, 103, 41, 38]</td>\n",
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" <td>0.685315</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>7</th>\n",
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" <td>small</td>\n",
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" <td>[257, 34, 41, 38]</td>\n",
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" <td>0.657858</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>8</th>\n",
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" <td>small</td>\n",
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" <td>[26, 103, 41, 38]</td>\n",
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" <td>0.617951</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>9</th>\n",
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" <td>small</td>\n",
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" <td>[22, 37, 41, 38]</td>\n",
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" <td>0.606692</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10</th>\n",
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" <td>small</td>\n",
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" <td>[335, 247, 41, 38]</td>\n",
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" <td>0.585767</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>11</th>\n",
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" <td>small</td>\n",
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" <td>[227, 239, 41, 38]</td>\n",
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" <td>0.578679</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>12</th>\n",
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" <td>small</td>\n",
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" <td>[95, 244, 41, 38]</td>\n",
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" <td>0.576981</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>13</th>\n",
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" <td>small</td>\n",
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" <td>[286, 237, 41, 38]</td>\n",
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" <td>0.543841</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>14</th>\n",
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" <td>small</td>\n",
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" <td>[251, 106, 41, 38]</td>\n",
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" <td>0.525461</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>15</th>\n",
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" <td>small</td>\n",
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" <td>[157, 234, 41, 38]</td>\n",
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" <td>0.524984</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16</th>\n",
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" <td>small</td>\n",
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" <td>[134, 37, 41, 38]</td>\n",
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" <td>0.511434</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>17</th>\n",
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" <td>small</td>\n",
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" <td>[196, 27, 41, 38]</td>\n",
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" <td>0.506831</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" TemplateName BBox Score\n",
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"0 small [80, 37, 41, 38] 1.000000\n",
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"1 small [133, 108, 41, 38] 0.860808\n",
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"2 small [134, 178, 41, 38] 0.816142\n",
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"3 small [82, 106, 41, 38] 0.800473\n",
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"4 small [316, 105, 41, 38] 0.747887\n",
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"5 small [23, 178, 41, 38] 0.742242\n",
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"6 small [185, 103, 41, 38] 0.685315\n",
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"7 small [257, 34, 41, 38] 0.657858\n",
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"8 small [26, 103, 41, 38] 0.617951\n",
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"9 small [22, 37, 41, 38] 0.606692\n",
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"10 small [335, 247, 41, 38] 0.585767\n",
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"11 small [227, 239, 41, 38] 0.578679\n",
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"12 small [95, 244, 41, 38] 0.576981\n",
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"13 small [286, 237, 41, 38] 0.543841\n",
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"14 small [251, 106, 41, 38] 0.525461\n",
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"15 small [157, 234, 41, 38] 0.524984\n",
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"16 small [134, 37, 41, 38] 0.511434\n",
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"17 small [196, 27, 41, 38] 0.506831"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"print(\"Found {} hits\".format( len(Hits.index) ) )\n",
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"print(Hits)"
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"Hits"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<matplotlib.image.AxesImage at 0x206c12717c8>"
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"<matplotlib.image.AxesImage at 0x1d438c62608>"
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]
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},
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"execution_count": 7,
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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},

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