{"cells":[{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nimport pandas as pd\nfrom PIL import Image","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"work_dir = '../input/cassava-leaf-disease-classification/'\nos.listdir(work_dir) \ntrain_path = '/kaggle/input/cassava-leaf-disease-classification/train_images'","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data = pd.read_csv(work_dir + 'train.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['label'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"TEST_DIR = '../input/cassava-leaf-disease-classification/test_images/'\ntest_images = os.listdir(TEST_DIR)\npredictions = []\n\nfor image in test_images:\n    predictions.append(3)\n\nsub = pd.DataFrame({'image_id': test_images, 'label': predictions})\nsub.to_csv('submission.csv', index = False)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sub","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}