{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"11f1b592-dcf5-d7f9-a323-81be17810fd0"},"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 \n\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\nfrom subprocess import check_output\nprint(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n\n# Any results you write to the current directory are saved as output."},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"aec99f16-0c53-eee3-06f2-1b82373d5fba"},"outputs":[],"source":"import os\n#print(os.listdir(\"/kaggle/input/train\"))\n#pd.read_csv(\"/kaggle/input/train/)\n\nfrom PIL import Image\nImage.open('/kaggle/input/train/cat.11181.jpg')"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"80b39595-8e83-7d73-f7e0-8ca698eff8b0"},"outputs":[],"source":""}],"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}