{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"d9219e89-5a9a-5a2a-6b13-a5d8fb7955f8"},"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":"7834aa75-0ba5-7466-5a49-e00536f93d1d"},"outputs":[],"source":"import keras\nimport numpy as np\nfrom keras.preprocessing.image import  load_img\nimport os\nimport cv2"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"ebc7f0f9-54b1-0aa8-0ad2-0bd8bbdc118d"},"outputs":[],"source":"def loadImages(folder):\n    # return array of images\n    images = []\n    for filename in os.listdir(folder):\n        img = cv2.imread(os.path.join(folder,filename))\n        if img is not None:\n            images.append(img)\n    return np.array(images)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"a55e147f-90ce-6000-a8df-2d1f66fe344f"},"outputs":[],"source":"training_data=loadImages('../input/train')\n\nvalidation_data=loadImages('../input/test')"}],"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":"3.6.0"}},"nbformat":4,"nbformat_minor":0}