{"metadata": {"kernelspec": {"display_name": "Python 3", "name": "python3", "language": "python"}, "language_info": {"version": "3.6.3", "nbconvert_exporter": "python", "file_extension": ".py", "pygments_lexer": "ipython3", "mimetype": "text/x-python", "name": "python", "codemirror_mode": {"version": 3, "name": "ipython"}}}, "nbformat_minor": 1, "cells": [{"cell_type": "code", "metadata": {"_uuid": "c467ef82c86e7bc0458ab7dc23f8d2951770a90b", "_cell_guid": "bda811fa-312f-4df5-9630-6336d92275a4"}, "execution_count": null, "source": ["# This Python 3 environment comes with many helpful analytics libraries installed\n", "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", "# For example, here's several helpful packages to load in \n", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "from subprocess import check_output\n", "import keras \n", "import tensorflow as tf\n", "import zipfile\n", "import pdb\n", "import matplotlib.pyplot as plt\n", "import matplotlib.image as mpimg\n", "print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n", "list_camera_folder=check_output([\"ls\", \"../input/train/\"]).decode(\"utf8\")\n", "#print(list_camera_folder)\n", "DEBUG=1;\n", "\n", "data= dict();\n", "list_camera_folder = list(list_camera_folder.split('\\n')[:-1]);\n", "for camera_model in list_camera_folder:\n", "    #pdb.set_trace()\n", "    if camera_model not in data.keys():\n", "        name_of_image_files = check_output([\"ls\", \"../input/train/\"+camera_model]).decode(\"utf8\").split('\\n')[:-1]\n", "        data[camera_model]=[];\n", "        for files in name_of_image_files:\n", "            file_path = \"../input/train/\"+camera_model+'/'+files;\n", "            data[camera_model].append(file_path);\n", "    else:\n", "        name_of_image_files = check_output([\"ls\", \"../input/train/\"+camera_model]).decode(\"utf8\").split('\\n')[:-1]\n", "        for files in name_of_image_files:\n", "            file_path = \"../input/train/\"+camera_model+'/'+files;\n", "            data[camera_model].append(file_path);\n", "            \n", "#print length of data\n", "if DEBUG:\n", "    for mykey in data.keys():\n", "        print(mykey,len(data[mykey]))\n", "if DEBUG:\n", "   for index,key in enumerate(data.keys()):\n", "        datalength = len(data[key]);\n", "        index= np.random.randint(datalength, size=1);\n", "        #pdb.set_trace()\n", "        img_name= data[key][index[0]];\n", "        image= mpimg.imread(img_name);\n", "        plt.figure(index+1);plt.imshow(image)\n", "plt.show()\n", "        \n", "        \n"], "outputs": []}], "nbformat": 4}