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takotab/fastai_trouble.ipynb

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Please do not use this. Follow the steps as descried on the fastai data block docs.
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fastai_trouble.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from fastai.vision import *"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"PosixPath('/home/tako/.fastai/data/planet_tiny')"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"planet = untar_data(URLs.PLANET_TINY)\n",
"planet"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"mkdir: cannot create directory ‘/home/tako/.fastai/data/planet_tiny/test’: File exists\n"
]
}
],
"source": [
"!mkdir /home/tako/.fastai/data/planet_tiny/test\n",
"!mkdir /home/tako/.fastai/data/planet_tiny/val\n",
"!cp /home/tako/.fastai/data/planet_tiny/train/*9.jpg /home/tako/.fastai/data/planet_tiny/test\n",
"!cp /home/tako/.fastai/data/planet_tiny/train/*8.jpg /home/tako/.fastai/data/planet_tiny/test\n",
"!cp /home/tako/.fastai/data/planet_tiny/train/*7.jpg /home/tako/.fastai/data/planet_tiny/val"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"train_10098.jpg train_15839.jpg train_28128.jpg train_39758.jpg\n",
"train_10838.jpg train_16718.jpg train_28549.jpg train_4309.jpg\n",
"train_11789.jpg train_17098.jpg train_29999.jpg train_4559.jpg\n",
"train_1189.jpg\t train_19208.jpg train_30958.jpg train_4788.jpg\n",
"train_11988.jpg train_19388.jpg train_31179.jpg train_5589.jpg\n",
"train_12129.jpg train_20599.jpg train_31979.jpg train_5788.jpg\n",
"train_12498.jpg train_20768.jpg train_34359.jpg train_6098.jpg\n",
"train_12689.jpg train_21859.jpg train_34558.jpg train_7879.jpg\n",
"train_12768.jpg train_23239.jpg train_35878.jpg train_789.jpg\n",
"train_12848.jpg train_2478.jpg train_36338.jpg train_8119.jpg\n",
"train_13019.jpg train_25678.jpg train_36778.jpg train_8348.jpg\n",
"train_14418.jpg train_26139.jpg train_3918.jpg train_9638.jpg\n",
"train_15269.jpg train_26158.jpg train_39539.jpg train_9879.jpg\n"
]
}
],
"source": [
"!ls /home/tako/.fastai/data/planet_tiny/test"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(\"/home/tako/.fastai/data/planet_tiny/labels.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>image_name</th>\n",
" <th>tags</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>train_39539</td>\n",
" <td>clear primary water</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>train_12498</td>\n",
" <td>agriculture clear primary road</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>train_4788</td>\n",
" <td>cloudy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>train_9879</td>\n",
" <td>agriculture clear primary</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>train_34359</td>\n",
" <td>cloudy</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" image_name tags\n",
"2 train_39539 clear primary water\n",
"3 train_12498 agriculture clear primary road\n",
"6 train_4788 cloudy\n",
"13 train_9879 agriculture clear primary\n",
"21 train_34359 cloudy"
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def test(x):\n",
" \n",
" if str(x)[-1:] in ['8','9']:\n",
" return \"test\"\n",
" elif str(x)[-1:] in ['7']:\n",
" return 'val'\n",
" return 'train'\n",
"\n",
"mask = df.image_name.apply(test)\n",
"# print(mask)\n",
"df_test = df[mask=='test']\n",
"df_val = df[mask=='val']\n",
"df_train = df[mask == 'train']\n",
"df_test.head()"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"labels.csv test test.csv train train.csv val val.csv\n"
]
}
],
"source": [
"df_test.to_csv(\"/home/tako/.fastai/data/planet_tiny/test.csv\",index=False)\n",
"df_val.to_csv(\"/home/tako/.fastai/data/planet_tiny/val.csv\",index=False)\n",
"df_train.to_csv(\"/home/tako/.fastai/data/planet_tiny/train.csv\",index=False)\n",
"!ls /home/tako/.fastai/data/planet_tiny"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Method 1"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"\n",
"imagelist_train = ImageItemList.from_csv(planet, 'train.csv', folder='train', suffix='.jpg')\n",
"imagelist_val = ImageItemList.from_csv(planet, 'val.csv', folder='val', suffix='.jpg')\n",
"imagelist_test = ImageItemList.from_csv(planet, 'test.csv', folder='test', suffix='.jpg')\n",
"itemslists = ItemLists(planet,train = imagelist_train, valid=imagelist_test, test = imagelist_test)\n"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "process() got an unexpected keyword argument 'name'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-73-437fc214c084>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mitemslists\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlabel_from_df\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel_delim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m' '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36m_inner\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 423\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 424\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLabelLists\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 425\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 426\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 427\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0m_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36mprocess\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 470\u001b[0m \u001b[0;34m\"Process the inner datasets.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 471\u001b[0m \u001b[0mxp\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0myp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_processors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 472\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlists\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'train'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'valid'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'test'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mxp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 473\u001b[0m \u001b[0;31m#progress_bar clear the outputs so in some case warnings issued during processing disappear.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 474\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mds\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlists\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: process() got an unexpected keyword argument 'name'"
]
}
],
"source": [
"itemslists.label_from_df(label_delim=' ')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Method 2"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"LabelLists;\n",
"\n",
"Train: LabelList\n",
"y: MultiCategoryList (130 items)\n",
"[MultiCategory clear;primary, MultiCategory partly_cloudy;primary;water, MultiCategory clear;primary, MultiCategory agriculture;clear;cultivation;primary;road, MultiCategory clear;primary]...\n",
"Path: /home/tako/.fastai/data/planet_tiny\n",
"x: ImageItemList (130 items)\n",
"[Image (3, 128, 128), Image (3, 128, 128), Image (3, 128, 128), Image (3, 128, 128), Image (3, 128, 128)]...\n",
"Path: /home/tako/.fastai/data/planet_tiny;\n",
"\n",
"Valid: LabelList\n",
"y: MultiCategoryList (52 items)\n",
"[MultiCategory clear;primary;water, MultiCategory agriculture;clear;primary;road, MultiCategory cloudy, MultiCategory agriculture;clear;primary, MultiCategory cloudy]...\n",
"Path: /home/tako/.fastai/data/planet_tiny\n",
"x: ImageItemList (52 items)\n",
"[Image (3, 128, 128), Image (3, 128, 128), Image (3, 128, 128), Image (3, 128, 128), Image (3, 128, 128)]...\n",
"Path: /home/tako/.fastai/data/planet_tiny;\n",
"\n",
"Test: None"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"imagelist_train = ImageItemList.from_csv(planet, 'train.csv', folder='train', suffix='.jpg')\n",
"imagelist_val = ImageItemList.from_csv(planet, 'val.csv', folder='val', suffix='.jpg')\n",
"imagelist_test = ImageItemList.from_csv(planet, 'test.csv', folder='test', suffix='.jpg')\n",
"itemslists = ItemLists(planet,train = imagelist_train, valid=imagelist_test)\n",
"itemslists.label_from_df(label_delim=' ')"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'int' object is not iterable",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-76-38fb9f524304>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mitemslists\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_test\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimagelist_train\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlabel_from_df\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel_delim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m' '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36m_inner\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 423\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 424\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLabelLists\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 425\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 426\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 427\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0m_inner\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36mprocess\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 470\u001b[0m \u001b[0;34m\"Process the inner datasets.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 471\u001b[0m \u001b[0mxp\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0myp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_processors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 472\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlists\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'train'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'valid'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'test'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mxp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 473\u001b[0m \u001b[0;31m#progress_bar clear the outputs so in some case warnings issued during processing disappear.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 474\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mds\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlists\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36mprocess\u001b[0;34m(self, ds)\u001b[0m\n\u001b[1;32m 292\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclasses\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclasses\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 293\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mc2i\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mc2i\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 294\u001b[0;31m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 295\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 296\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__getstate__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'classes'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclasses\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36mprocess\u001b[0;34m(self, ds)\u001b[0m\n\u001b[1;32m 36\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mCollection\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mref_ds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 37\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mprocess_one\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 38\u001b[0;31m \u001b[0;32mdef\u001b[0m \u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mCollection\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess_one\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mitem\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 39\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[0;32mclass\u001b[0m \u001b[0mItemList\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 36\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mCollection\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mref_ds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 37\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mprocess_one\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 38\u001b[0;31m \u001b[0;32mdef\u001b[0m \u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mCollection\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess_one\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mitem\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 39\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[0;32mclass\u001b[0m \u001b[0mItemList\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/devtools/test_env/env-ai-37/lib/python3.7/site-packages/fastai/data_block.py\u001b[0m in \u001b[0;36mprocess_one\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 340\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mprocess_one\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 341\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mone_hot\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mEmptyLabel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 342\u001b[0;31m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mMultiCategoryProcessor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess_one\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mo\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mo\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 343\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mr\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mr\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mr\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 344\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: 'int' object is not iterable"
]
}
],
"source": [
"itemslists.add_test(imagelist_train ).label_from_df(label_delim=' ')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "env-ai-37",
"language": "python",
"name": "env-ai-37"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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