{"cells":[{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"import os\nimport random\nimport pandas as pd\n\ndf = pd.read_csv('../input/prostate-cancer-grade-assessment/test.csv')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(f\"Length of test.csv: {len(df)}\\n\")\n\n\nprint(df.head())\nprint('')\n\n\nfor i in df['image_id'][:2]:\n    print(f'{i} - {os.path.exists(f\"../input/prostate-cancer-grade-assessment/train_images/{i}.tiff\")}')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for i in os.walk('/kaggle/'):\n    if 'test_images' in i:\n        print(i)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\nif os.path.exists('../input/prostate-cancer-grade-assessment/test_images'):\n    print('inference!')\n    images = os.listdir('../input/prostate-cancer-grade-assessment/test_images')\n\nelse:\n    print('not inference')\n    images = os.listdir('../input/prostate-cancer-grade-assessment/train_images')\n\nwith open('./submission.csv', 'wb') as f:\n    f.write(bytes('image_id,isup_grade\\n', encoding='utf8'))\n    for image in images:\n        f.write(bytes(f'{image.replace(\".tiff\", \"\")},{random.choice(range(6))}\\n', encoding='utf8'))\n\n\n","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":4}