{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","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 all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"import cv2\nimport numpy as np\nimport pandas as pd\n\n\nimport matplotlib.pyplot as plt\n%matplotlib inline\n\nimport os\nimport random\nimport gc","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"import pandas as pd\nsample_submission = pd.read_csv(\"../input/dogs-vs-cats-redux-kernels-edition/sample_submission.csv\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_dir = '../input/dogs-vs-cats-redux-kernels-edition/train'\ntest_dir ='../input/dogs-vs-cats-redux-kernels-edition/test'\n\ntrain_dogs=['../input/train/{}'.format(i) for i in os.listdir(train_dir)if 'dog' in 1]\ntrain_cats=['../input/train/{}'.format(i) for i in os.listdir(train_dir)if 'cat' in 1]\n\ntrain_dogs=['../input/test/{}'.format(i) for i in os.listdir(test_dir)]\n\ntrain_imgs = train_dogs[:2000] + train_cats[:2000]\nrandom.shuffle(train_imgs)\n\ndel train_dogs\ndel train_cats\n\ngc.collect()","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}