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amiralushamiralush
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Merge pull request #167 from dnth/dnth/update-example
Rerun broken notebooks
2 parents 9697e66 + b4da1cc commit d761e59

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‎examples/analysing-image-classification-dataset.ipynb‎

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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "SwSYWR4vzk_e",
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"metadata": {
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "8aba34e1",
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"metadata": {},
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"</div>"
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],
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"text/plain": [
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" path noisy_labels_0 noisy_labels_1 \\\n",
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"0 train/n02979186/n02979186_9036.JPEG n02979186 n02979186 \n",
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" path noisy_labels_0 noisy_labels_1 \n",
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"0 train/n02979186/n02979186_9036.JPEG n02979186 n02979186 \\\n",
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"1 train/n02979186/n02979186_11957.JPEG n02979186 n02979186 \n",
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"2 train/n02979186/n02979186_9715.JPEG n02979186 n02979186 \n",
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"\n",
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "dfc957bf",
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"metadata": {},
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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>img_filename</th>\n",
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" <th>filename</th>\n",
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" <th>label</th>\n",
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" <th>split</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>train/n02979186/n02979186_9036.JPEG</td>\n",
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" <td>imagenette2-160/train/n02979186/n02979186_9036...</td>\n",
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" <td>cassette_player</td>\n",
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" <td>train</td>\n",
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" <td>imagenette2-160</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>train/n02979186/n02979186_11957.JPEG</td>\n",
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" <td>imagenette2-160/train/n02979186/n02979186_1195...</td>\n",
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" <td>cassette_player</td>\n",
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" <td>train</td>\n",
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" <td>imagenette2-160</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>train/n02979186/n02979186_9715.JPEG</td>\n",
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" <td>imagenette2-160/train/n02979186/n02979186_9715...</td>\n",
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" <td>cassette_player</td>\n",
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" <td>train</td>\n",
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" <td>imagenette2-160</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>train/n02979186/n02979186_21736.JPEG</td>\n",
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" <td>imagenette2-160/train/n02979186/n02979186_2173...</td>\n",
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" <td>cassette_player</td>\n",
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" <td>train</td>\n",
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" <td>imagenette2-160</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>train/n02979186/ILSVRC2012_val_00046953.JPEG</td>\n",
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" <td>imagenette2-160/train/n02979186/ILSVRC2012_val...</td>\n",
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" <td>cassette_player</td>\n",
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" <td>train</td>\n",
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" <td>imagenette2-160</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>13389</th>\n",
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" <td>val/n03425413/n03425413_17521.JPEG</td>\n",
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" <td>imagenette2-160/val/n03425413/n03425413_17521....</td>\n",
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" <td>gas_pump</td>\n",
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" <td>val</td>\n",
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" <td>imagenette2-160</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>13390</th>\n",
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" <td>val/n03425413/n03425413_20711.JPEG</td>\n",
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" <td>imagenette2-160/val/n03425413/n03425413_20711....</td>\n",
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" <td>gas_pump</td>\n",
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" <td>val</td>\n",
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" <td>imagenette2-160</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>13391</th>\n",
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" <td>val/n03425413/n03425413_19050.JPEG</td>\n",
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" <td>imagenette2-160/val/n03425413/n03425413_19050....</td>\n",
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" <td>gas_pump</td>\n",
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" <td>val</td>\n",
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" <td>imagenette2-160</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>13392</th>\n",
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" <td>val/n03425413/n03425413_13831.JPEG</td>\n",
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" <td>imagenette2-160/val/n03425413/n03425413_13831....</td>\n",
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" <td>gas_pump</td>\n",
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" <td>val</td>\n",
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" <td>imagenette2-160</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>13393</th>\n",
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" <td>val/n03425413/n03425413_1242.JPEG</td>\n",
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" <td>imagenette2-160/val/n03425413/n03425413_1242.JPEG</td>\n",
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" <td>gas_pump</td>\n",
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" <td>val</td>\n",
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" <td>imagenette2-160</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>13394 rows × 3 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" img_filename label split\n",
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"0 train/n02979186/n02979186_9036.JPEG cassette_player train\n",
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"1 train/n02979186/n02979186_11957.JPEG cassette_player train\n",
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"2 train/n02979186/n02979186_9715.JPEG cassette_player train\n",
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"3 train/n02979186/n02979186_21736.JPEG cassette_player train\n",
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"4 train/n02979186/ILSVRC2012_val_00046953.JPEG cassette_player train\n",
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"... ... ... ...\n",
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"13389 val/n03425413/n03425413_17521.JPEG gas_pump val\n",
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"13390 val/n03425413/n03425413_20711.JPEG gas_pump val\n",
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"13391 val/n03425413/n03425413_19050.JPEG gas_pump val\n",
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"13392 val/n03425413/n03425413_13831.JPEG gas_pump val\n",
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"13393 val/n03425413/n03425413_1242.JPEG gas_pump val\n",
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" filename label \n",
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"0 imagenette2-160/train/n02979186/n02979186_9036... cassette_player \\\n",
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"1 imagenette2-160/train/n02979186/n02979186_1195... cassette_player \n",
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"2 imagenette2-160/train/n02979186/n02979186_9715... cassette_player \n",
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"3 imagenette2-160/train/n02979186/n02979186_2173... cassette_player \n",
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"4 imagenette2-160/train/n02979186/ILSVRC2012_val... cassette_player \n",
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"... ... ... \n",
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"13389 imagenette2-160/val/n03425413/n03425413_17521.... gas_pump \n",
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"13390 imagenette2-160/val/n03425413/n03425413_20711.... gas_pump \n",
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"13391 imagenette2-160/val/n03425413/n03425413_19050.... gas_pump \n",
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"13392 imagenette2-160/val/n03425413/n03425413_13831.... gas_pump \n",
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"13393 imagenette2-160/val/n03425413/n03425413_1242.JPEG gas_pump \n",
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"\n",
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" split \n",
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"0 imagenette2-160 \n",
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"1 imagenette2-160 \n",
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"2 imagenette2-160 \n",
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"3 imagenette2-160 \n",
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"4 imagenette2-160 \n",
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"... ... \n",
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"13389 imagenette2-160 \n",
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"13390 imagenette2-160 \n",
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"13391 imagenette2-160 \n",
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"13392 imagenette2-160 \n",
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"13393 imagenette2-160 \n",
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"\n",
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"[13394 rows x 3 columns]"
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]
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"# rename columns to fastdup's column names\n",
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"df_annot = df_annot.rename({'noisy_labels_0': 'label', 'path': 'filename'}, axis='columns')\n",
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"\n",
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"# append datadir\n",
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"df_annot['filename'] = df_annot['filename'].apply(lambda x: data_dir + x)\n",
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"\n",
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"# create split column\n",
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"df_annot['split'] = df_annot['filename'].apply(lambda x: x.split(\"/\")[0])\n",
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"\n",
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "0c648ed1-5016-4230-9873-546eb510b764",
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"metadata": {
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 6,
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"id": "7f69d8b2",
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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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"'0.918'"
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"'0.922'"
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]
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},
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"execution_count": 1,
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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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},
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"attachments": {},
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"cell_type": "markdown",
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"id": "62e35a12-fadd-4b3f-bcab-69e6e67862a4",
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"metadata": {},
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]
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]
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},
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"cell_type": "markdown",
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"id": "c2c393be-2b42-4814-8688-03d2be9e8998",
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]
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"cell_type": "markdown",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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"version": "3.10.11"
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}
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},
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"nbformat": 4,

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