{"cells":[
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport sklearn\nimport glob, os\n"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "from subprocess import check_output\nprint(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\nsmjpegs = [f for f in glob.glob(\"../input/train_sm/*.jpeg\")]\nprint(smjpegs[:9])"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "set160 = [smj for smj in smjpegs if \"set160\" in smj]\nprint(set160)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "first = plt.imread(\"../input/train_sm/set160_1.jpeg\")\ndims = np.shape(first)\nprint(dims)\nplt.imshow(first)"
 }
],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}}, "nbformat": 4, "nbformat_minor": 0}