{"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)\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:\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","trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import datetime\nimport re\nimport gc\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom pathlib import Path\nimport json\nimport os\nimport PIL\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras import layers\nimport pathlib","metadata":{"execution":{"iopub.status.busy":"2022-02-17T01:15:36.746103Z","iopub.execute_input":"2022-02-17T01:15:36.746819Z","iopub.status.idle":"2022-02-17T01:15:36.75287Z","shell.execute_reply.started":"2022-02-17T01:15:36.746765Z","shell.execute_reply":"2022-02-17T01:15:36.751927Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_dir = '../input/herbarium-2022-fgvc9/train_images/'\ntrain_dir = pathlib.Path(train_dir)\nplant_000_00 = list(train_dir.glob('000/00/*'))\nPIL.Image.open(str(plant_000_00[9]))","metadata":{"execution":{"iopub.status.busy":"2022-02-17T01:15:39.290559Z","iopub.execute_input":"2022-02-17T01:15:39.29112Z","iopub.status.idle":"2022-02-17T01:15:39.452993Z","shell.execute_reply.started":"2022-02-17T01:15:39.291073Z","shell.execute_reply":"2022-02-17T01:15:39.45232Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"PIL.Image.open(str(plant_000_00[46]))","metadata":{"execution":{"iopub.status.busy":"2022-02-17T01:15:46.562516Z","iopub.execute_input":"2022-02-17T01:15:46.562816Z","iopub.status.idle":"2022-02-17T01:15:46.924437Z","shell.execute_reply.started":"2022-02-17T01:15:46.562785Z","shell.execute_reply":"2022-02-17T01:15:46.923594Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"PIL.Image.open(str(plant_000_00[23]))","metadata":{"execution":{"iopub.status.busy":"2022-02-17T01:15:53.664223Z","iopub.execute_input":"2022-02-17T01:15:53.664518Z","iopub.status.idle":"2022-02-17T01:15:54.054044Z","shell.execute_reply.started":"2022-02-17T01:15:53.664485Z","shell.execute_reply":"2022-02-17T01:15:54.052957Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"PIL.Image.open(str(plant_000_00[31]))","metadata":{"execution":{"iopub.status.busy":"2022-02-17T01:15:59.87939Z","iopub.execute_input":"2022-02-17T01:15:59.87989Z","iopub.status.idle":"2022-02-17T01:15:59.997339Z","shell.execute_reply.started":"2022-02-17T01:15:59.879835Z","shell.execute_reply":"2022-02-17T01:15:59.996444Z"},"trusted":true},"execution_count":null,"outputs":[]}]}