{"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 the files in the input directory\n\nimport os\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"import cv2\n\n# normalize an image for training purposes\ndef normalize(x):\n    return (x.astype(float) - 128)/128\n\n# open, resize and normalize an image\ndef preprocess(img_name, size):\n    img = cv2.imread(img_name)\n    img = cv2.resize(img, size)\n    img = normalize(img)\n    \n    return img\n    ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"ac29a74650d81126b093011e4b116c41894b3af3"},"cell_type":"code","source":"images_folder = '../input/stage_1_test_images/'\nimage_names = os.listdir(images_folder)\n\nimage_name = images_folder+image_names[0]\n\nprint (image_name)\n                         ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"d56e7553f36db186e0ccc43bcd77f3db94fbcf03"},"cell_type":"code","source":"from matplotlib import pyplot\n\n# read and show the original image\noriginal_image = cv2.imread(image_name)\n\npyplot.imshow(original_image)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"2baa4545141ad112ddd97f84a237ba2582ffda35"},"cell_type":"code","source":"# preprocess an image and show it\nprocessed_image = preprocess(image_name, (150,150))\n\npyplot.imshow(processed_image)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"56064884c8a6265b1c893b8cd45c9102c5959463"},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}