{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"9da06010-30af-35db-9038-fe4372e923fa"},"outputs":[],"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 \nimport os\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\n# from subprocess import check_output\n# print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n# https://keras.io/preprocessing/image/\nfrom keras.preprocessing.image import ImageDataGenerator\n\nTRAIN_DIR = '../input/train'\nTEST_DIR = '../input/test'\n\n# (256, 256) is keras ImageDataGenerator default\nTARGET_IMG_DIM = (256, 256)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"a16cb1ea-0e29-a66e-9a89-07cd6e368394"},"outputs":[],"source":"# os.listdir(TRAIN_DIR)\nif not os.path.exists(TRAIN_DOG):\n    os.makedirs(TRAIN_DOG)\nif not os.path.exists(TRAIN_CAT):\n    os.makedirs(TRAIN_CAT)\n"}],"metadata":{"_change_revision":0,"_is_fork":false,"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":0}