{"cells":[{"cell_type":"markdown","metadata":{"_cell_guid":"7fd7a95a-8970-75c0-8be2-89ad1bbf0448"},"source":"My first script"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"3291eaea-06ab-d2b7-ac71-a078ea417e8b"},"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":"e68a5877-0c95-f667-f67a-6e8d095fb9ab"},"outputs":[],"source":"from collections import defaultdict\nimport csv\nimport sys\n\nimport cv2\nfrom shapely.geometry import MultiPolygon, Polygon\nimport shapely.wkt\nimport shapely.affinity\nimport numpy as np\nimport tifffile as tiff\n\ncsv.field_size_limit(sys.maxsize);"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"2c9b9dbc-c95d-2c72-9909-b58d1cd76401"},"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}