{"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_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input/aptos2019-blindness-detection'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-02-23T14:51:04.706704Z","iopub.execute_input":"2023-02-23T14:51:04.707436Z","iopub.status.idle":"2023-02-23T14:51:10.344610Z","shell.execute_reply.started":"2023-02-23T14:51:04.707399Z","shell.execute_reply":"2023-02-23T14:51:10.343211Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"path = '/kaggle/input/aptos2019-blindness-detection/'","metadata":{"execution":{"iopub.status.busy":"2023-02-23T14:51:10.346824Z","iopub.execute_input":"2023-02-23T14:51:10.347303Z","iopub.status.idle":"2023-02-23T14:51:10.353601Z","shell.execute_reply.started":"2023-02-23T14:51:10.347256Z","shell.execute_reply":"2023-02-23T14:51:10.352398Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df = pd.read_csv(path + 'train.csv', sep = ',')","metadata":{"execution":{"iopub.status.busy":"2023-02-23T14:51:10.355735Z","iopub.execute_input":"2023-02-23T14:51:10.356170Z","iopub.status.idle":"2023-02-23T14:51:10.389122Z","shell.execute_reply.started":"2023-02-23T14:51:10.356126Z","shell.execute_reply":"2023-02-23T14:51:10.387788Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2023-02-23T14:51:10.391680Z","iopub.execute_input":"2023-02-23T14:51:10.392720Z","iopub.status.idle":"2023-02-23T14:51:10.414973Z","shell.execute_reply.started":"2023-02-23T14:51:10.392672Z","shell.execute_reply":"2023-02-23T14:51:10.413550Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import cv2\nimport os\n\nfiles = os.listdir(\"/kaggle/input/aptos2019-blindness-detection/train_images\")\n\n\nimg_list = []\n\nfor i in files:\n    \n    image = cv2.imread('f\"/kaggle/input/aptos2019-blindness-detection/train_images/{}.png\"')\n    img_list.append(image)\n    \nprint(img_list)","metadata":{"execution":{"iopub.status.busy":"2023-02-23T15:20:55.042410Z","iopub.execute_input":"2023-02-23T15:20:55.042855Z","iopub.status.idle":"2023-02-23T15:20:55.064917Z","shell.execute_reply.started":"2023-02-23T15:20:55.042816Z","shell.execute_reply":"2023-02-23T15:20:55.063682Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"len(img_list)","metadata":{"execution":{"iopub.status.busy":"2023-02-23T14:53:11.085700Z","iopub.execute_input":"2023-02-23T14:53:11.086114Z","iopub.status.idle":"2023-02-23T14:53:11.093519Z","shell.execute_reply.started":"2023-02-23T14:53:11.086079Z","shell.execute_reply":"2023-02-23T14:53:11.092396Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}