{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import zipfile\nfrom PIL import Image\nfrom pathlib import Path\nimport io","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"img_list = Path('/kaggle/input/siim-isic-melanoma-classification/jpeg').glob('**/*.jpg')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"with zipfile.ZipFile('train.zip', 'w') as trainzip:\n    for i, img_fn in enumerate(img_list):\n        small_img = Image.open(img_fn).resize((224, 224))\n        image_file = io.BytesIO()\n        small_img.save(image_file, 'PNG')\n        zipped_filename = img_fn.parts[-2] + '/' + img_fn.stem + '.png'\n        trainzip.writestr(zipped_filename, image_file.getvalue())","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}