{"cells":[{"metadata":{},"cell_type":"markdown","source":"https://www.kaggle.com/slm37102/ranzcr-clip-fastai-starter/"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"from fastai.vision.all import *","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"path = Path('../input/ranzcr-clip-catheter-line-classification')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df = pd.read_csv(path/'train.csv')\ntrain_df","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"columns = list(train_df.columns[1:12])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_x(r):\n    return path/'train'/(r['StudyInstanceUID']+'.jpg')\n\ndef get_y(r):\n    return r[columns].values.tolist()\n\ndef get_data(size=224, bs=128, data_df=train_df):\n    dblock = DataBlock(blocks=(ImageBlock, MultiCategoryBlock(encoded=True, vocab=columns)),\n                       splitter=RandomSplitter(seed=42),\n                       get_x = get_x,\n                       get_y = get_y,\n                       item_tfms = RandomResizedCrop(460, min_scale=0.75, ratio=(1.,1.)),\n                       batch_tfms = [*aug_transforms(size=size, flip_vert=True, max_warp=0),\n                                     Normalize.from_stats(*imagenet_stats)])\n    return dblock.dataloaders(data_df, bs=bs)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dls = get_data()\ndls.show_batch()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn = cnn_learner(dls, resnet50, metrics=accuracy_multi, cbs=MixUp).to_native_fp16()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.fine_tune(5)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn = learn.to_native_fp32()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission_df = pd.read_csv(path/'sample_submission.csv')\nsubmission_df.iloc[:,1:] = submission_df.iloc[:,1:].astype(float)\nsubmission_df","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_data_path = submission_df['StudyInstanceUID'].apply(lambda x: path/'test'/(x + '.jpg'))\ntst_dl = learn.dls.test_dl(test_data_path)1\npreds, targs = lean.tta(dl= tst_dl)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission_df[columns] =pd.DataFrame(preds, columns= columns)\nsubmission_df","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission_df.to_csv('submission.csv', index=False)","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}