{"cells":[{"metadata":{},"cell_type":"markdown","source":"## Imports"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport os, sys\nfrom fastai import *\nfrom fastai.vision import *","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import fastai\nfastai.__version__","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"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\nseed_everything(42)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data"},{"metadata":{"trusted":true},"cell_type":"code","source":"PATH = Path('../input/aptos2019-blindness-detection')\ndf_train = pd.read_csv(PATH/\"train.csv\") \\\n           .assign(filename = lambda df: \"train_images/\" + df.id_code + \".png\")\ndf_test = pd.read_csv(PATH/\"test.csv\") \\\n          .assign(filename = lambda df: \"test_images/\" + df.id_code + \".png\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"_ = df_train.hist()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"transforms = get_transforms(\n    do_flip = True,\n    flip_vert = True,\n    max_zoom = 1,\n    max_rotate = 180, #default 10\n    max_lighting = 0.2, #default 0.2\n    max_warp = 0.1 #default 0.1\n)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data = ImageDataBunch.from_df(path = \"../input/aptos2019-blindness-detection\",\n                              df = df_train,\n                              fn_col = \"filename\",\n                              label_col = \"diagnosis\",\n                              ds_tfms = transforms,\n                             size=224)\\\n        .normalize(imagenet_stats)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data.show_batch(rows=3, figsize=(7,6))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Model"},{"metadata":{"trusted":true},"cell_type":"code","source":"# copy pretrained weights for resnet50 to the folder fastai will search by default\nPath('/tmp/.cache/torch/checkpoints/').mkdir(exist_ok=True, parents=True)\n!cp '../input/resnet50/resnet50.pth' '/tmp/.cache/torch/checkpoints/resnet50-19c8e357.pth'","execution_count":null,"outputs":[]},{"metadata":{"_kg_hide-output":false,"trusted":true},"cell_type":"code","source":"kappa = KappaScore()\nkappa.weights = \"quadratic\"\nlearn = cnn_learner(data, models.resnet50,\n                    metrics=[error_rate, kappa],\n                    model_dir=\"/tmp/model/\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.lr_find(end_lr=0.5)\nlearn.recorder.plot(suggestion=True)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"lr = 7e-3\nlearn.fit_one_cycle(10, lr)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.recorder.plot_losses()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.unfreeze()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"lrs = slice(lr/400,lr/4)\nlearn.fit_one_cycle(10,lrs)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.recorder.plot_losses()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"interp = ClassificationInterpretation.from_learner(learn)\ninterp.plot_top_losses(9, figsize=(15,11))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"interp.plot_confusion_matrix(figsize=(8,8), dpi=60)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Submission"},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_df = pd.read_csv('../input/aptos2019-blindness-detection/sample_submission.csv')\nsample_df.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.data.add_test(ImageList.from_df(\n    sample_df, PATH,\n    folder='test_images',\n    suffix='.png'\n))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"preds,y = learn.get_preds(DatasetType.Test)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_df.diagnosis = preds.argmax(1)\nsample_df.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_df.to_csv('submission.csv',index=False)\n_ = sample_df.hist()","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}