{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import os\nimport numpy as np\nimport pandas as pd\n\nDATA_PATH = '/kaggle/input/prostate-cancer-grade-assessment/test_images'\nTEST_CSV = '/kaggle/input/prostate-cancer-grade-assessment/test.csv'\nSAMPLE_CSV = '/kaggle/input/prostate-cancer-grade-assessment/sample_submission.csv'\n\nif os.path.exists(DATA_PATH):\n    subject_ids = list(pd.read_csv(TEST_CSV).image_id)\n    \n    print(f\"length subject_ids: {len(subject_ids)}\")\n    \n    preds = []\n    for subject_id in subject_ids:\n        score = 0\n        preds.append(score)\n\n    sub_df = pd.DataFrame({'image_id': subject_ids, 'isup_grade': preds})\n    sub_df.to_csv('submission.csv', index=False)\n    print(sub_df.head())\nelse:\n    print(\"test images not available (v3)\")\n    sub_df = pd.read_csv(SAMPLE_CSV)\n    sub_df.to_csv('submission.csv', index=False)","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","collapsed":true,"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":false},"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":4}