{"cells":[{"metadata":{},"cell_type":"markdown","source":"# Balanced Starter | Stratified | Submission Example\n\n**This notebook shows you how to:**\n\n- Easily view the images using `OpenSlide`\n- The dataset is pretty imbalanced, using a simple method of balancing the data prior to training\n- Create a seperate train/test to check how the model is doing prior to submitting as the actual `test` set is hidden\n- Create a stratified `DataLoader` and use `half-precision` to improve training time\n- Test on the created `test` set and view the results via Confusion Matrix and calculate the Quadratic Weighted Kappa\n- How to submit example\n\nChange the current distribution of `isup_grade` from this:\n\n\n![isup.PNG](attachment:isup.PNG)\n\nTo this:\n![isup2.PNG](attachment:isup2.PNG)","attachments":{"isup.PNG":{"image/png":"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"}},"execution_count":null},{"metadata":{},"cell_type":"markdown","source":"**How to submit**\n\n- This competition requires the internet to be `off` before you can submit to the competition.  For this you will have to create an internet free version of loading fastai to your kernel.  \n\nTo make it easier I have provided a convenient `kaggle dataset` with all the files you need to make a successful submission.\n\n- **1** Go to [fastai017_whl](https://www.kaggle.com/avirdee/fastai017-whl) to view the dataset. This dataset provides the 3 files you need to load `fastai2` version 0.0.17, `fastcore` version 0.1.18 and `fastprogress` version 0.2.3 (please upvote if you find this helpful)\n\n- **2** In your kernel click on the `Add data` tab on the right top of the notebook and under the `Search Datasets` bar, enter `fastai017.whl`\n\n- **3** Once the dataset has loaded you will find `fastai017.whl` under the `input` section.\n\n- **5** You can now load all `fastai2` dependencies with the internet off.","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"# Load the dependancies","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"## Internet ON","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"With the internet `on` during the testing phase you would use the standard `pip` methods of loading the `fastai2` dependancies","execution_count":null},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"!pip install fastai2 --q","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Internet OFF","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"However with internet `off` as per the competition requirements we need to load the dependancies with the internet `off`.  In this case you will have to load the dependancies like this (by adding [fast017-whl](https://www.kaggle.com/avirdee/fastai017-whl) to your kernel):","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"!pip install ../input/fastai017-whl/fastprogress-0.2.3-py3-none-any.whl\n!pip install ../input/fastai017-whl/fastcore-0.1.18-py3-none-any.whl\n!pip install ../input/fastai017-whl/fastai2-0.0.17-py3-none-any.whl","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"This will load all the required dependacies","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"#Load the dependancies\nfrom fastai2.basics import *\nfrom fastai2.callback.all import *\nfrom fastai2.vision.all import *\n\nimport seaborn as sns\nimport numpy as np\nimport pandas as pd\nimport os\nimport cv2\nimport openslide\n\nfrom sklearn.model_selection import StratifiedShuffleSplit\n\nsns.set(style=\"whitegrid\")\nsns.set_context(\"paper\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"With internet off you will also have to load your trained model, for this example I am using `resnet18`.  Once you have add the model to your kernel you have to make a `checkpoints` directory and copy the model to that directory","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"Path('/root/.cache/torch/checkpoints/').mkdir(exist_ok=True, parents=True)\n!cp '../input/resnet18/resnet18.pth' '/root/.cache/torch/checkpoints/resnet18-5c106cde.pth'","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"source = Path(\"../input/prostate-cancer-grade-assessment\")\nfiles = os.listdir(source)\nprint(files)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train = source/'train_images'\nmask = source/'train_label_masks'\ntrain_labels = pd.read_csv(source/'train.csv')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Balance the Data","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"The competition requirement is that you have to predict the `isup_grade` for each image in the test set","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"train_labels.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Plotting the distribution of `isup_grade`","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"def plot_count(df, feature, title='', size=2):\n    f, ax = plt.subplots(1,1, figsize=(3*size,2*size))\n    total = float(len(df))\n    sns.countplot(df[feature],order = df[feature].value_counts().index, palette='Set1')\n    plt.title(title)\n    for p in ax.patches:\n        height = p.get_height()\n        ax.text(p.get_x()+p.get_width()/2.,\n                height + 3,\n                '{:1.2f}%'.format(100*height/total),\n                ha=\"center\") \n    plt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"plot_count(train_labels, 'isup_grade','ISUP grade - data count and percent', size=3)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"This shows us that the distribution of images based on `isup_grade` is unbalanced with the highest number of images being grade `0` and the lowest number of images being grade `5`","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"Checking to see how many images are within each `isup_grade`","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"isup_0 = train_labels[train_labels.isup_grade == 0]\nisup_1 = train_labels[train_labels.isup_grade == 1]\nisup_2 = train_labels[train_labels.isup_grade == 2]\nisup_3 = train_labels[train_labels.isup_grade == 3]\nisup_4 = train_labels[train_labels.isup_grade == 4]\nisup_5 = train_labels[train_labels.isup_grade == 5]\n\nprint(f'isup_0: {len(isup_0)}, isup_1: {len(isup_1)}, isup_2: {len(isup_2)}, isup_3: {len(isup_3)}, isup_4: {len(isup_4)}, isup_5: {len(isup_5)}')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"You can quickly balance the data using `sample` so that each class has `1224` images each and then create a balanced dataset","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"isup_sam0 = isup_0.sample(n=1224)\nisup_sam1 = isup_1.sample(n=1224)\nisup_sam2 = isup_2.sample(n=1224)\nisup_sam3 = isup_3.sample(n=1224)\nisup_sam4 = isup_4.sample(n=1224)\n\nframes = [isup_sam0, isup_sam1, isup_sam2, isup_sam3, isup_sam4, isup_5]\nbalanced_df = pd. concat(frames)\nbalanced_df","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Looking at the distribution of the balanced dataset we can see that each class is equally represented","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"plot_count(balanced_df, 'isup_grade','ISUP grade - data count and percent', size=3)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Create Train/Test set","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"In this competition the `test` set is hidden but to get a better idea of how you are doing I am creating another seperate `test` set that we can test on prior to submitting to the competition\n\nCreate a copy of the `balanced_df` that we created and split it into a `80/20` split","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"df_copy = balanced_df.copy()\n\n# 80/20 split or whatever you choose\ntrain_set = df_copy.sample(frac=0.80, random_state=7)\ntest_set = df_copy.drop(train_set.index)\nprint(len(train_set), len(test_set))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"So we will have `5875` images in the train set and `1469` images in the test set.","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"Save `train_set` to `csv` so that we can strattify the training set","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"#Save train_set to csv for strattification\ntrain_set.to_csv('split.csv', index=False)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Stratify the Train Set","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"For this we use `StratifiedShuffleSplit` from `sklearn` so that we can split the train set into 6 distinct splits and then train on each split","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"Load the `split.csv` file","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"df = pd.read_csv('split.csv')\ndf.shape[0]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Create a stratified dataframe `strat_df` with `6` splits.  `test_size` here is the % of `strat_df` that will be used for validation.","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"sss = StratifiedShuffleSplit(n_splits=6, test_size=0.2, random_state=7)\nstrat_df = pd.DataFrame()\ncols=['isup_grade']\n\nfor i, (train_index, test_index) in enumerate(sss.split(df, df.isup_grade)):\n    df_split = df.copy()\n    df_split['fold'] = i\n    df_split.loc[train_index, 'which'] = 'train'\n    df_split.loc[test_index, 'which'] = 'valid'\n    X_train = df_split.loc[train_index]\n    X_valid = df_split.loc[test_index]\n    X_train.loc[:, 'which'] = 'train'\n    X_valid.loc[:, 'which'] = 'valid'\n    \n    mult_dis = X_train.loc[X_train.image_id=='isup_grade']\n    for _ in range(3): X_train = X_train.append(mult_dis)\n    \n    strat_df = strat_df.append(X_train).append(X_valid)\n    print(i, strat_df.shape, [(X_train[c].sum()/len(X_train), X_train[c].sum()) for c in cols])\nstrat_df = strat_df.reset_index()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Looking at the created `strat_df`, the `dataframe` now includes the `fold` number and whether it is being used for training or validation","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"strat_df.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Viewing the Images","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"Create a function so that you can easily view the image.  `Fastai2` does not have an in-built method of viewing `.tiff` files.  For viewing the images we use `OpenSlide`","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"def view_image(folder, fn):\n    filename = f'{folder}/{fn}.tiff'\n    file = openslide.OpenSlide(str(filename))\n    t = tensor(file.get_thumbnail(size=(255, 255)))\n    pil = PILImage.create(t) \n    return pil","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Lets view an image with `gleason_score` 3+5 to check it works","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"glee_35 = train_labels[train_labels.gleason_score == '3+5']\nglee_35[:5]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"view_image(train, '05819281002c55258bb3086cc55e3b48')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Creating the DataBlock","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"We have to create a function that can get the images from the folder, open it and change it into a `tensor` as `Fastai2` needs batches to be in the form of tensors or arrays","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_i(fn):\n    filename = f'{train}/{fn.image_id}.tiff'\n    example2 = openslide.OpenSlide(str(filename))\n    ee = example2.get_thumbnail(size=(255, 255))\n    return tensor(ee)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"specify the `blocks`, the `getters` and the `DataBlock`","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"blocks = (\n          ImageBlock,\n          CategoryBlock\n          )    \ngetters = [\n           get_i,\n           ColReader('isup_grade')\n          ]\ntrends = DataBlock(blocks=blocks,\n              splitter=RandomSplitter(),\n              getters=getters,\n              item_tfms=Resize(256),\n              batch_tfms=aug_transforms()\n              )","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"For training with folds we need to specify funtions for training with folds, the dataloader and the learner","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"def train_on_folds(bs, size, base_lr, folds):\n    learners = []\n    all_val_preds = []\n    all_val_labels = []\n    all_test_preds = []\n    \n    for fold in range(folds):\n        print(f'Processing fold: {fold}....')\n        dls = get_dls(bs=bs, size=size, fold=fold, df=strat_df)\n        \n        learn = get_learner(dls, arch, loss_func, cbs)\n        learn = train_learner(learn, base_lr)\n        learn.save(f'model_fold_{fold}')\n        learners.append(learn)\n        learn.recorder.plot_loss()\n        \n        test_dl = dls.test_dl(train_df)\n        test_preds, _, _ = learn.get_preds(dl=test_dl, with_decoded=True)\n        val_preds, val_labels = learn.get_preds()\n    \n        all_val_preds.append(val_preds)\n        all_val_labels.append(val_labels)\n        all_test_preds.append(test_preds)\n    \n    plt.show()\n    return learners, all_val_preds, all_val_labels, all_test_preds","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"set_seed(7)\ndef get_dls(bs, size, fold, df):\n    df_fold = df.copy()\n    df_fold = df_fold.loc[df_fold.fold==fold].reset_index()\n    \n    trends = DataBlock(blocks=blocks,\n                       splitter=IndexSplitter(df_fold.loc[df_fold.which=='valid'].index),\n                       getters=getters,\n                       item_tfms=Resize(256),\n                       batch_tfms=aug_transforms(size=size)\n                       )\n    dls = trends.dataloaders(df_fold, bs=bs)\n    assert (len(dls.train_ds) + len(dls.valid_ds)) == len(df_fold)\n    return dls","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Specify a function for the `learner` and we will use `half precision` hence the `.to_fp16()` to reduce memory and increase training time ","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_learner(dls,arch,loss_func, cbs):\n    return Learner(dls,arch,loss_func=loss_func,metrics=metrics, cbs=cbs).to_fp16()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"The `train_learner` function is fully customiable so you can experiement with any number of `learner` parameters","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"def train_learner(learn, base_lr):\n    learn.unfreeze()\n    learn.fit_one_cycle(2, base_lr)\n    \n    learn.freeze_to(-2)\n    learn.fit_one_cycle(2, base_lr)\n    return learn","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dls = get_dls(bs=32, size=128, fold=2, df=strat_df)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Check that `dls.show_batch` works","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"dls.show_batch()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dls.c","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"We have 6 different classes in the dataset","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"#### Specify the training parameters\n\nSubmissions are scored based on the `quadratic weighted kappa`, which measures the agreement between two outcomes.  To get a good understanding of this metric see this excellent [notebook](https://www.kaggle.com/reighns/understanding-the-quadratic-weighted-kappa) as well as this excellent [notebook](https://www.kaggle.com/aroraaman/quadratic-kappa-metric-explained-in-5-simple-steps)\n\nCohen's kappa measures the agreement between two raters who each classify N items into C mutually exclusive categories.  A perfect score of 1.0 is granted when both the predictions and actuals are the same.\n\n![kappa.PNG](attachment:kappa.PNG)","attachments":{"kappa.PNG":{"image/png":"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"}},"execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"arch = resnet18(pretrained=True)\nloss_func = LabelSmoothingCrossEntropy(eps=0.3, reduction='mean')\ncbs = [ShowGraphCallback()]\nmetrics=[accuracy,CohenKappa(weights='quadratic')]\ntrain_df = pd.read_csv('split.csv')\nbs = 32\nsize = 196","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dls = get_dls(bs=bs, size=size, fold=1, df=strat_df)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn = Learner(dls,\n                model=arch,\n                loss_func=loss_func,\n                metrics=metrics,\n                cbs=cbs)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Find the best `learning rate`","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.lr_find()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"base_lr = 1e-2\nlearners, all_val_preds, all_val_labels, all_test_preds = train_on_folds(bs, size, base_lr, folds=1)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Inference on the Test set","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"We will use the `test_set` that was created","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"test_set","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Let's look at some of the images in our created `test` set","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.load('model_fold_0')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"tst_dl = dls.test_dl(test_set)\ntst_dl.show_batch(max_n=9)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Get the predicted classes","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"_, _, pred_classes = learn.get_preds(dl=tst_dl, with_decoded=True)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"pred_classes","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Let's check out the test results.  For this we create a dataframe of actual and predicted classes","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"test_df = test_set.copy()\ntest_df['isup_grade_pred'] = pred_classes\ntest_df","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Create a `confusion matrix` of the results","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"confusion_matrix = pd.crosstab(test_df['isup_grade'], test_df['isup_grade_pred'], rownames=['Actual'], colnames=['Predicted'])\nsns.heatmap(confusion_matrix, annot=True)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import classification_report \nprint(classification_report(test_df['isup_grade'], test_df['isup_grade_pred']))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"This can further help us tweak the model to get better results","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"# Submission","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"In this competition the test set if hidden but we do know that there is a `test_images` folder","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"submission_test_path = \"../input/prostate-cancer-grade-assessment/test_images/\"\nsample = '../input/prostate-cancer-grade-assessment/sample_submission.csv'","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sub_df = pd.read_csv(sample)\ntest_df = pd.read_csv(source/f'test.csv')\nif os.path.exists(submission_test_path):\n    learn.load('prostate')\n    def get_inf(df=test_df):\n        filename = f'{submission_test_path}/{df.image_id}.tiff' \n        example2 = openslide.OpenSlide(str(filename))\n        ee = example2.get_thumbnail(size=(255, 255))\n        return tensor(ee)\n    \n    blocks = (\n          ImageBlock,\n          CategoryBlock\n          )\n    getters = [\n           get_inf,\n           ColReader('isup_grade')\n          ]\n\n    trends = DataBlock(blocks=blocks,\n              getters=getters,\n              item_tfms=Resize(128)\n              )\n    \n    dls = trends.dataloaders(test_df, bs=32)\n    learn = cnn_learner(dls, resnet18)\n    \n    test_dl = dls.test_dl(test_df)\n    _,_,pred_classes = learn.get_preds(dl=test_dl, with_decoded=True)\n    \n    test_df[\"isup_grade\"] = pred_classes\n    sub = test_df[[\"image_id\",\"isup_grade\"]]\n    sub.to_csv('submission.csv', index=False)\n","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}