{"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_minor":4,"nbformat":4,"cells":[{"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\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 read-only \"../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[:5]:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2021-10-15T19:01:25.255444Z","iopub.execute_input":"2021-10-15T19:01:25.255760Z","iopub.status.idle":"2021-10-15T19:01:25.267614Z","shell.execute_reply.started":"2021-10-15T19:01:25.255724Z","shell.execute_reply":"2021-10-15T19:01:25.266633Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"npz_test = np.load(\"../input/sartorius-segmentation-train-mask-dataset-npz/0030fd0e6378.npz\")[\"arr_0\"]\n\nplt.figure(figsize=(12,7))\nplt.imshow(npz_test)\nplt.axis(False)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2021-10-15T19:02:37.957639Z","iopub.execute_input":"2021-10-15T19:02:37.958487Z","iopub.status.idle":"2021-10-15T19:02:38.177501Z","shell.execute_reply.started":"2021-10-15T19:02:37.958438Z","shell.execute_reply":"2021-10-15T19:02:38.176790Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"RANDOM_CELL=2\n\nplt.figure(figsize=(12,7))\nplt.imshow(np.where(npz_test==RANDOM_CELL, 1, 0))\nplt.axis(False)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2021-10-15T19:03:35.258141Z","iopub.execute_input":"2021-10-15T19:03:35.258958Z","iopub.status.idle":"2021-10-15T19:03:35.390686Z","shell.execute_reply.started":"2021-10-15T19:03:35.258915Z","shell.execute_reply":"2021-10-15T19:03:35.389731Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"RANDOM_CELL=31\n\nplt.figure(figsize=(12,7))\nplt.imshow(np.where(npz_test==RANDOM_CELL, 1, 0))\nplt.axis(False)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2021-10-15T19:03:36.372784Z","iopub.execute_input":"2021-10-15T19:03:36.373755Z","iopub.status.idle":"2021-10-15T19:03:36.497049Z","shell.execute_reply.started":"2021-10-15T19:03:36.373712Z","shell.execute_reply":"2021-10-15T19:03:36.496427Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"RANDOM_CELL=101\n\nplt.figure(figsize=(12,7))\nplt.imshow(np.where(npz_test==RANDOM_CELL, 1, 0))\nplt.axis(False)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2021-10-15T19:03:25.516748Z","iopub.execute_input":"2021-10-15T19:03:25.517063Z","iopub.status.idle":"2021-10-15T19:03:25.650817Z","shell.execute_reply.started":"2021-10-15T19:03:25.517020Z","shell.execute_reply":"2021-10-15T19:03:25.650135Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}