{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"efed14fe-b472-2b66-19b1-c437e3f97f02"},"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)\nimport matplotlib.pyplot as plt\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/train\"]).decode(\"utf8\"))\n\n# Any results you write to the current directory are saved as output."},{"cell_type":"markdown","metadata":{"_cell_guid":"76c59ef7-419d-edee-11b3-b4485d5ef247"},"source":"First thing first, let's import some useful libraries."},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"3b2082b5-4120-4984-a316-b8216307b5de"},"outputs":[],"source":"from IPython.display import Image\nfrom IPython.display import display\n\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\n\nimage = mpimg.imread(\"../input/train/dog.10126.jpg\")\nplt.imshow(image)\nplt.show()"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"02174a37-d94c-0c85-6982-54fe00c6bcdc"},"outputs":[],"source":""},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"2502f4d6-7fc9-b0cb-6854-de648d827f4c"},"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}