{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, \nimport cv2\n# Input data files are available in the \"../input/\" directory\nimport os\nimport matplotlib.pyplot as plt\nimport itertools\n# import segmentation_models as sm\nimport keras\nimport random\n# from iteration_utilities import unique_everseen\n# for dirname, _, filenames in os.walk('/kaggle/input'):\n#     for filename in filenames:\n#         print(os.path.join(dirname, filename))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_dir = '/kaggle/input/recursion-cellular-image-classification/'\nos.listdir('/kaggle/input/recursion-cellular-image-classification/')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df1 = pd.read_csv(train_dir + 'pixel_stats.csv')\ndf1.head(10)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df2 = pd.read_csv(train_dir + 'test.csv')\ndf2.head(10)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df3 = pd.read_csv(train_dir + 'test_controls.csv')\ndf3.head(10)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df4 = pd.read_csv(train_dir + 'train_controls.csv')\ndf4.head(10)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df4.info()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df5 = pd.read_csv(train_dir + 'train.csv')\ndf5.tail(10)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df5.info()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"os.listdir(train_dir + 'train/')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"im = cv2.imread(train_dir + 'train/' + 'HUVEC-15/Plate3/C16_s2_w4.png')\nplt.imshow(im)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","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":1}