{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.12.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":113558,"databundleVersionId":14878066,"sourceType":"competition"}],"dockerImageVersionId":31234,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"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":{"iopub.status.busy":"2025-12-22T06:25:55.246739Z","iopub.execute_input":"2025-12-22T06:25:55.246927Z","iopub.status.idle":"2025-12-22T06:26:02.742763Z","shell.execute_reply.started":"2025-12-22T06:25:55.246906Z","shell.execute_reply":"2025-12-22T06:26:02.741472Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import os\nimport pandas as pd\n\nTEST_DIR = \"/kaggle/input/recodai-luc-scientific-image-forgery-detection/test_images\"\n\ncase_ids = sorted(\n    int(f.replace(\".png\", \"\"))\n    for f in os.listdir(TEST_DIR)\n    if f.endswith(\".png\")\n)\n\nsubmission = pd.DataFrame({\n    \"case_id\": case_ids,\n    \"annotation\": [\"authentic\"] * len(case_ids)\n})\n\nsubmission.to_csv(\"submission.csv\", index=False)\n\nprint(\"Rows:\", len(submission))\nprint(submission.head())\nprint(submission.dtypes)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-12-22T06:26:10.224922Z","iopub.execute_input":"2025-12-22T06:26:10.225499Z","iopub.status.idle":"2025-12-22T06:26:10.268399Z","shell.execute_reply.started":"2025-12-22T06:26:10.225467Z","shell.execute_reply":"2025-12-22T06:26:10.267579Z"}},"outputs":[],"execution_count":null}]}