{"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"gpu","dataSources":[{"sourceType":"competition","sourceId":14774,"databundleVersionId":875431},{"sourceType":"datasetVersion","sourceId":418427,"datasetId":187021,"databundleVersionId":433708},{"sourceType":"datasetVersion","sourceId":1399787,"datasetId":252150,"databundleVersionId":1432488},{"sourceType":"datasetVersion","sourceId":848739,"datasetId":251095,"databundleVersionId":875102},{"sourceType":"datasetVersion","sourceId":527603,"datasetId":250877,"databundleVersionId":543908}],"dockerImageVersionId":29188,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import cv2\nimport matplotlib.pyplot as plt\nfrom os.path import isfile\nimport torch.nn.init as init\nimport torch\nimport torch.nn as nn\nimport numpy as np\nimport pandas as pd \nimport os\nfrom PIL import Image, ImageFilter\nprint(os.listdir(\"../input\"))\nfrom sklearn.model_selection import train_test_split, StratifiedKFold\nfrom torch.utils.data import Dataset\nfrom torchvision import transforms\nfrom torch.optim import Adam, SGD, RMSprop\nimport time\nfrom torch.autograd import Variable\nimport torch.functional as F\nfrom tqdm import tqdm\nfrom sklearn import metrics\nimport urllib\nimport pickle\nimport cv2\nimport torch.nn.functional as F\nfrom torchvision import models\nimport seaborn as sns\nimport random\n\nimport sys","metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true,"scrolled":true,"execution":{"iopub.status.busy":"2026-03-10T12:48:25.983722Z","iopub.execute_input":"2026-03-10T12:48:25.983985Z","iopub.status.idle":"2026-03-10T12:48:30.114472Z","shell.execute_reply.started":"2026-03-10T12:48:25.983949Z","shell.execute_reply":"2026-03-10T12:48:30.113738Z"}},"outputs":[{"name":"stdout","text":"['retinopathy-train-2015', 'efficientnet-pytorch', 'aptos2019-blindness-detection', 'efficientnet']\n","output_type":"stream"}],"execution_count":8},{"cell_type":"code","source":"package_path = '/kaggle/input/efficientnet/EfficientNet-PyTorch-master/'\nsys.path.append(package_path)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-10T13:00:59.582484Z","iopub.execute_input":"2026-03-10T13:00:59.58282Z","iopub.status.idle":"2026-03-10T13:00:59.586192Z","shell.execute_reply.started":"2026-03-10T13:00:59.582757Z","shell.execute_reply":"2026-03-10T13:00:59.585551Z"}},"outputs":[],"execution_count":16},{"cell_type":"code","source":"from efficientnet_pytorch import EfficientNet","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-10T13:01:01.971336Z","iopub.execute_input":"2026-03-10T13:01:01.97178Z","iopub.status.idle":"2026-03-10T13:01:02.003354Z","shell.execute_reply.started":"2026-03-10T13:01:01.971715Z","shell.execute_reply":"2026-03-10T13:01:02.002838Z"}},"outputs":[],"execution_count":17},{"cell_type":"code","source":"def seed_everything(seed):\n random.seed(seed)\n os.environ['PYTHONHASHSEED'] = str(seed)\n np.random.seed(seed)\n torch.manual_seed(seed)\n torch.cuda.manual_seed(seed)\n torch.backends.cudnn.deterministic = True","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-10T13:01:07.010188Z","iopub.execute_input":"2026-03-10T13:01:07.010476Z","iopub.status.idle":"2026-03-10T13:01:07.014959Z","shell.execute_reply.started":"2026-03-10T13:01:07.01044Z","shell.execute_reply":"2026-03-10T13:01:07.013912Z"}},"outputs":[],"execution_count":18},{"cell_type":"code","source":"num_classes = 1\nseed_everything(1234)\nlr = 1e-3\nIMG_SIZE = 256","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-03-10T13:01:10.621437Z","iopub.execute_input":"2026-03-10T13:01:10.621727Z","iopub.status.idle":"2026-03-10T13:01:10.636983Z","shell.execute_reply.started":"2026-03-10T13:01:10.621679Z","shell.execute_reply":"2026-03-10T13:01:10.636278Z"}},"outputs":[],"execution_count":19},{"cell_type":"code","source":"train = '../input/aptos2019-blindness-detection/train_images/'\ntest = '../input/aptos2019-blindness-detection/test_images/'\ntrain_csv = pd.read_csv('../input/aptos2019-blindness-detection/train.csv')\n\ntrain_df, val_df = train_test_split(train_csv, test_size=0.1, random_state=2018, stratify=train_csv.diagnosis)\ntrain_df.reset_index(drop=True, inplace=True)\nval_df.reset_index(drop=True, inplace=True)\ntrain_df.head()","metadata":{"trusted":true,"_uuid":"766f44c87272f67d632e519dce11cf54a3382696","execution":{"iopub.status.busy":"2026-03-10T13:01:48.335793Z","iopub.execute_input":"2026-03-10T13:01:48.336068Z","iopub.status.idle":"2026-03-10T13:01:48.396644Z","shell.execute_reply.started":"2026-03-10T13:01:48.336029Z","shell.execute_reply":"2026-03-10T13:01:48.395912Z"}},"outputs":[{"execution_count":20,"output_type":"execute_result","data":{"text/plain":" id_code diagnosis\n0 1f5496352859 0\n1 82e5bc01f8a4 0\n2 fbdc796290d4 0\n3 7adfb8fc0621 0\n4 e26d8718ca58 1","text/html":"\n\n
\n \n \n | \n id_code | \n diagnosis | \n
\n \n \n \n | 0 | \n 1f5496352859 | \n 0 | \n
\n \n | 1 | \n 82e5bc01f8a4 | \n 0 | \n
\n \n | 2 | \n fbdc796290d4 | \n 0 | \n
\n \n | 3 | \n 7adfb8fc0621 | \n 0 | \n
\n \n | 4 | \n e26d8718ca58 | \n 1 | \n
\n \n
\n