sc.ipynb
1.75 KB
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/home/jaehun/super_resolution/dataset/IMAGENET/images/train\n"
]
}
],
"source": [
"train=os.path.join(os.getcwd(),'train')\n",
"test=os.path.join(os.getcwd(),'test')\n",
"print(train)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/home/jaehun/super_resolution/dataset/IMAGENET/images'"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"os.getcwd()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"f=open(\"iids_train.txt\", 'w')\n",
"os.chdir(train)\n",
"for i in os.listdir(os.getcwd()):\n",
" f.write(os.path.basename(i)[:-5]+'\\n')\n",
" #print(os.path.basename(i)[:-5])\n",
"\n",
"f.close()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}