{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import os\nimport pandas as pd\n\n# folder names for 2 classes\nBASE_DIR = './'\ntrain_folder1 = BASE_DIR+'ants/'\ntrain_folder2 = BASE_DIR+'bees/'\n\n# sorting\nfiles_in_train1 = sorted(os.listdir(train_folder1))\nfiles_in_train2 = sorted(os.listdir(train_folder2))\n\n# get imagenames list\nimages=[i for i in files_in_train1]\n\n# write to csv for 1st class\ndf = pd.DataFrame()\ndf['images']=[train_folder1+str(x) for x in images]\ndf['labels']='0'\ndf.to_csv('train.csv', header=None)\n\nimages2=[i for i in files_in_train2]\n\n# write to csv for 2nd class\ndf = pd.DataFrame()\ndf['images']=[train_folder1+str(x) for x in images2]\ndf['labels']='1'\ndf.to_csv('train.csv', header=None)\n\n","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}