{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":1686636,"sourceType":"datasetVersion","datasetId":999462}],"dockerImageVersionId":31193,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"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},"outputs":[],"execution_count":null},{"cell_type":"code","source":"pip install torch torchvision timm scikit-learn pandas numpy opencv-python torchmetrics tqdm\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-11-24T17:29:16.397990Z","iopub.execute_input":"2025-11-24T17:29:16.398243Z","iopub.status.idle":"2025-11-24T17:30:51.476711Z","shell.execute_reply.started":"2025-11-24T17:29:16.398219Z","shell.execute_reply":"2025-11-24T17:30:51.475981Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-11-24T17:30:56.285772Z","iopub.execute_input":"2025-11-24T17:30:56.285993Z","iopub.status.idle":"2025-11-24T17:30:56.301402Z","shell.execute_reply.started":"2025-11-24T17:30:56.285979Z","shell.execute_reply":"2025-11-24T17:30:56.300897Z"}},"outputs":[],"execution_count":null}]}