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"}}},{"cell_type":"markdown","source":"This notebooks hold all the steps to prepare the appropriate dataset from scratch and will be used for future notebooks i.e. on training, inferencing.","metadata":{}},{"cell_type":"markdown","source":"# Import Libraries:","metadata":{}},{"cell_type":"code","source":"# Libraries\nimport os\nimport torch\nimport numpy as np\nimport pandas as pd\nimport torch.nn as nn\nfrom glob import glob\nfrom PIL import Image\nimport matplotlib.pyplot as plt\nfrom torchvision.utils import make_grid\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision.transforms import ToTensor, Resize","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:11.665081Z","iopub.execute_input":"2022-08-07T06:26:11.665686Z","iopub.status.idle":"2022-08-07T06:26:13.460974Z","shell.execute_reply.started":"2022-08-07T06:26:11.665594Z","shell.execute_reply":"2022-08-07T06:26:13.459797Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# CONSTANTS\nSEED  = 42\nBATCH_SIZE = 64\nimport warnings\nwarnings.filterwarnings(\"ignore\")","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:13.463157Z","iopub.execute_input":"2022-08-07T06:26:13.464580Z","iopub.status.idle":"2022-08-07T06:26:13.469552Z","shell.execute_reply.started":"2022-08-07T06:26:13.464540Z","shell.execute_reply":"2022-08-07T06:26:13.468752Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Defining paths :\nAs only the training dataset has to be made in this notebook, so only defining the training paths.","metadata":{}},{"cell_type":"code","source":"train_dir = \"../input/uw-madison-gi-tract-image-segmentation/train\"\ntraining_metadata_path = \"../input/uw-madison-gi-tract-image-segmentation/train.csv\"","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:13.470713Z","iopub.execute_input":"2022-08-07T06:26:13.471311Z","iopub.status.idle":"2022-08-07T06:26:13.485038Z","shell.execute_reply.started":"2022-08-07T06:26:13.471277Z","shell.execute_reply":"2022-08-07T06:26:13.483944Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Loading Metadata and Preprocessing :\nNow, we have to load the metadata and process the primary findings.","metadata":{}},{"cell_type":"markdown","source":"### Loading metadata :","metadata":{}},{"cell_type":"code","source":"# loading metadata\ntrain_df = pd.read_csv(training_metadata_path)\ntrain_df.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:13.487545Z","iopub.execute_input":"2022-08-07T06:26:13.487882Z","iopub.status.idle":"2022-08-07T06:26:14.155034Z","shell.execute_reply.started":"2022-08-07T06:26:13.487838Z","shell.execute_reply":"2022-08-07T06:26:14.154386Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# viewing primary information \ntrain_df.info()","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:14.156476Z","iopub.execute_input":"2022-08-07T06:26:14.156949Z","iopub.status.idle":"2022-08-07T06:26:14.210387Z","shell.execute_reply.started":"2022-08-07T06:26:14.156906Z","shell.execute_reply":"2022-08-07T06:26:14.209377Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"We can see most of the record doesen't have any segmentation, so we can say that there's no segmentation.","metadata":{}},{"cell_type":"markdown","source":"### Preprocessing :","metadata":{}},{"cell_type":"markdown","source":"First step is to extract the primary case ids. Also we have to make the segmentation masks into string format as the nan values will be difficult to etract in other ways.","metadata":{}},{"cell_type":"code","source":"train_df[\"segmentation\"] = train_df[\"segmentation\"].astype(\"str\")\ntrain_df[\"case_id\"] = train_df[\"id\"].apply(lambda x: x.split(\"_\")[0][4:])\ntrain_df[\"day_id\"] = train_df[\"id\"].apply(lambda x: x.split(\"_\")[1][3:])\ntrain_df[\"slice_id\"] = train_df[\"id\"].apply(lambda x: x.split(\"_\")[-1])","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:14.211874Z","iopub.execute_input":"2022-08-07T06:26:14.212344Z","iopub.status.idle":"2022-08-07T06:26:14.505327Z","shell.execute_reply.started":"2022-08-07T06:26:14.212300Z","shell.execute_reply":"2022-08-07T06:26:14.504335Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Let's visualize the dataset again.","metadata":{}},{"cell_type":"code","source":"train_df.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:14.509029Z","iopub.execute_input":"2022-08-07T06:26:14.509305Z","iopub.status.idle":"2022-08-07T06:26:14.524323Z","shell.execute_reply.started":"2022-08-07T06:26:14.509272Z","shell.execute_reply":"2022-08-07T06:26:14.523156Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Now, we have to extract the paths from the image ids.","metadata":{}},{"cell_type":"code","source":"def fetch_file_from_id(root_dir, case_id):\n    case_folder = case_id.split(\"_\")[0]\n    day_folder = \"_\".join(case_id.split(\"_\")[:2])\n    file_starter = \"_\".join(case_id.split(\"_\")[2:])\n    # fetching folder paths\n    folder = os.path.join(root_dir, case_folder, day_folder, \"scans\")\n    # fetching filenames with similar pattern\n    file = glob(f\"{folder}/{file_starter}*\")\n    # returning the first file, though it will always hold one file.\n    return file[0]\ntrain_df[\"path\"] = train_df[\"id\"].apply(lambda x: fetch_file_from_id(train_dir, x))\ntrain_df.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:26:14.525842Z","iopub.execute_input":"2022-08-07T06:26:14.526150Z","iopub.status.idle":"2022-08-07T06:27:44.486893Z","shell.execute_reply.started":"2022-08-07T06:26:14.526108Z","shell.execute_reply":"2022-08-07T06:27:44.486022Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Now, from the file paths we have to extract the heght and width of the image as well as the mask. Also there are some other attributes, leaving them just for simplicity.","metadata":{}},{"cell_type":"code","source":"train_df[\"height\"] = train_df[\"path\"].apply(lambda x: os.path.split(x)[-1].split(\"_\")[2]).astype(\"int\")\ntrain_df[\"width\"] = train_df[\"path\"].apply(lambda x: os.path.split(x)[-1].split(\"_\")[3]).astype(\"int\")\ntrain_df.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:44.488203Z","iopub.execute_input":"2022-08-07T06:27:44.488703Z","iopub.status.idle":"2022-08-07T06:27:44.980538Z","shell.execute_reply.started":"2022-08-07T06:27:44.488660Z","shell.execute_reply":"2022-08-07T06:27:44.979494Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Now, let's see how many classes are present here.","metadata":{}},{"cell_type":"code","source":"train_df[\"class\"].unique()","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:44.984471Z","iopub.execute_input":"2022-08-07T06:27:44.984733Z","iopub.status.idle":"2022-08-07T06:27:45.000479Z","shell.execute_reply.started":"2022-08-07T06:27:44.984703Z","shell.execute_reply":"2022-08-07T06:27:44.999522Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"We have to use the class as the channel in the mask, so performing label encoding.","metadata":{}},{"cell_type":"code","source":"class_names = train_df[\"class\"].unique()\nfor index, label in enumerate(class_names):\n    # replacing class names with indexes\n    train_df[\"class\"].replace(label, index, inplace = True)\ntrain_df.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.002435Z","iopub.execute_input":"2022-08-07T06:27:45.002832Z","iopub.status.idle":"2022-08-07T06:27:45.068805Z","shell.execute_reply.started":"2022-08-07T06:27:45.002784Z","shell.execute_reply":"2022-08-07T06:27:45.067973Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Mask Generation Methodology : \n\nThe Segmentation mask given in this place are in **RLE (RUN LENGTH ENCODING)** format.\n\n#### At first we have to understand how the format is :\n\n1. We can consider the given data has a particular shape , let's say height is **H** and width is **W**.\n2. Now we can consider the data in a flattened manner i.e. shape of the data is **(batch_size, H*W)**.\n3. The mask values are seperated by a space where every pair of value holds the valid infomation.\n4. The first value of the pair holds the sarting index of the mask in the flattened grid.\n5. The second value of the pair holds the length of mask from that starter pixel.\n6. So basically we can say , every element in the odd position holds the starter index and rest holds the length of the presence of the mask.\n\n#### Now , to process the mask what we can do :\n\n1. Split the odd elements and he even ones into different array which correspond length of present mask pixels and starter indexes.\n2. Add all the indexes that must be masked.\n3. Reshape the flattened array to image grid.","metadata":{}},{"cell_type":"markdown","source":"Adding utility functions to process mask and images","metadata":{}},{"cell_type":"code","source":"def prepare_mask_data(string):\n    # fetching all the values from the string\n    all_values = map(int, string.split(\" \"))\n    # preparing the usable arrays\n    starterIndex, pixelCount = [], []\n    for index, value in enumerate(all_values):\n        if index % 2:\n            # storing even indexed values in pixelCount\n            pixelCount.append(value)\n        else:\n            # storing odd indexed values in starterIndex\n            starterIndex.append(value)\n    return starterIndex, pixelCount\n    \ndef fetch_pos_pixel_indexes(indexes, counts):\n    final_arr = []\n    for index, counts in zip(indexes, counts):\n        # adding all the values from starterIndex to range of positive pixel counts\n        final_arr += [index + i for i in range(counts)]\n    return final_arr\n\ndef prepare_mask(string, height, width):\n    # preparing the respective arrays\n    indexes, counts = prepare_mask_data(string)\n    # preparing all the pixel indexes those have mask values\n    pos_pixel_indexes = fetch_pos_pixel_indexes(indexes, counts)\n    # forming the flattened array\n    mask_array = np.zeros(height * width)\n    # updating values in the array\n    mask_array[pos_pixel_indexes] = 1\n    # reshaping the masks\n    return mask_array.reshape(width, height)\n\ndef load_image(path):\n    # loading the image in RGB format\n    image = Image.open(path).convert('RGB')\n    return image","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.070166Z","iopub.execute_input":"2022-08-07T06:27:45.070434Z","iopub.status.idle":"2022-08-07T06:27:45.080341Z","shell.execute_reply.started":"2022-08-07T06:27:45.070398Z","shell.execute_reply":"2022-08-07T06:27:45.079256Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Dataset preparation : \n\nNow, we have to prepare the custom dataset  inherited from pytorch's Datatset class.","metadata":{}},{"cell_type":"code","source":"class UWDataset(Dataset):\n    \n    def __init__(self, meta_df, h=256, w=256):\n        super().__init__()\n        self.meta_df = meta_df\n        self.h = h\n        self.w = w\n        self.resize = Resize((h, w))\n        \n    def __len__(self):\n        return len(self.meta_df)\n    \n    def __getitem__(self, index):\n        # fetching image path\n        path = self.meta_df.loc[index, \"path\"]\n        # loading image\n        image = load_image(path)\n        # loading mask's original height, width\n        mask_h, mask_w = self.meta_df.loc[index, \"height\"], self.meta_df.loc[index, \"width\"]\n        # loading the segmentation encoding for maks preparation\n        mask_string = self.meta_df.loc[index, \"segmentation\"]\n        # laoding the mask\n        main_mask_channel = self.load_mask(string=mask_string, h=mask_h, w=mask_w)\n        # updating those in tensor format\n        image = ToTensor()(self.resize(image))\n        main_mask_channel = ToTensor()(self.resize(main_mask_channel))\n        # loading the original mask\n        mask = torch.zeros((3, self.h, self.w))\n        # loading the class label\n        class_label = self.meta_df.loc[index, \"class\"]\n        mask[class_label, ...] = main_mask_channel\n        \n        return image, mask\n    \n    def load_mask(self, string, h, w):\n        # cheking if the segmentation encoding is a valid mask or null values\n        if string != \"nan\":\n            return Image.fromarray(prepare_mask(string, h, w))\n        return Image.fromarray(np.zeros((h, w)))","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.081572Z","iopub.execute_input":"2022-08-07T06:27:45.081819Z","iopub.status.idle":"2022-08-07T06:27:45.093439Z","shell.execute_reply.started":"2022-08-07T06:27:45.081791Z","shell.execute_reply":"2022-08-07T06:27:45.092531Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Let's load the dataset","metadata":{}},{"cell_type":"code","source":"ds = UWDataset(train_df)\nprint(f\"Length of the dataset : {len(ds)}\")","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.095271Z","iopub.execute_input":"2022-08-07T06:27:45.095740Z","iopub.status.idle":"2022-08-07T06:27:45.110237Z","shell.execute_reply.started":"2022-08-07T06:27:45.095694Z","shell.execute_reply":"2022-08-07T06:27:45.108659Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Let's check if the mask and the image are generating in a right way","metadata":{}},{"cell_type":"code","source":"image, mask = ds[194]\nimage.shape, mask.shape","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.111387Z","iopub.execute_input":"2022-08-07T06:27:45.111676Z","iopub.status.idle":"2022-08-07T06:27:45.294820Z","shell.execute_reply.started":"2022-08-07T06:27:45.111643Z","shell.execute_reply":"2022-08-07T06:27:45.293904Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"combined_im_mask = torch.cat([image, mask], dim=2)","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.296820Z","iopub.execute_input":"2022-08-07T06:27:45.297062Z","iopub.status.idle":"2022-08-07T06:27:45.312739Z","shell.execute_reply.started":"2022-08-07T06:27:45.297034Z","shell.execute_reply":"2022-08-07T06:27:45.311556Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def show_image(tensor_image, name):\n    plt.figure(figsize=(20, 20))\n    plt.imshow(tensor_image.permute(1,2,0))\n    plt.title(name, size=30)\n    plt.show()\nshow_image(combined_im_mask, \"Real & Mask\")","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.314551Z","iopub.execute_input":"2022-08-07T06:27:45.314802Z","iopub.status.idle":"2022-08-07T06:27:45.789585Z","shell.execute_reply.started":"2022-08-07T06:27:45.314773Z","shell.execute_reply":"2022-08-07T06:27:45.788881Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Train Validation Split :\nAfter creating the dataset it is time to split the data into training and validation.\nWe'll be using a **80-20 train-validation** split.","metadata":{}},{"cell_type":"code","source":"train_size = int(len(ds)*0.8)\nval_size = len(ds) - train_size\ntrain_ds, val_ds = torch.utils.data.random_split(ds, [train_size, val_size], generator=torch.Generator().manual_seed(42))\nprint(f\"Length of the training dataset : {len(train_ds)}\")\nprint(f\"Length of the validation dataset : {len(val_ds)}\")","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.790533Z","iopub.execute_input":"2022-08-07T06:27:45.790972Z","iopub.status.idle":"2022-08-07T06:27:45.818813Z","shell.execute_reply.started":"2022-08-07T06:27:45.790927Z","shell.execute_reply":"2022-08-07T06:27:45.817830Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Now as we have prepared all the data , it is time to prepared batched data that'll be feeded to the model for training purposes.","metadata":{}},{"cell_type":"code","source":"train_dl = DataLoader(train_ds, batch_size=BATCH_SIZE, shuffle = True, drop_last = True)\nval_dl = DataLoader(val_ds, batch_size=BATCH_SIZE, shuffle=True, drop_last = True)","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.820110Z","iopub.execute_input":"2022-08-07T06:27:45.820602Z","iopub.status.idle":"2022-08-07T06:27:45.825478Z","shell.execute_reply.started":"2022-08-07T06:27:45.820566Z","shell.execute_reply":"2022-08-07T06:27:45.824565Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Let's visualize the first patch of training and validation patch","metadata":{}},{"cell_type":"code","source":"for train_image_batch, train_mask_batch in train_dl:\n    break\nfor val_image_batch, val_mask_batch in val_dl:\n    break","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:45.826661Z","iopub.execute_input":"2022-08-07T06:27:45.827522Z","iopub.status.idle":"2022-08-07T06:27:48.098112Z","shell.execute_reply.started":"2022-08-07T06:27:45.827480Z","shell.execute_reply":"2022-08-07T06:27:48.097023Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_batch = torch.cat([make_grid(train_image_batch, nrow=8), make_grid(train_mask_batch, nrow=8)], dim=2)\nval_batch = torch.cat([make_grid(val_image_batch, nrow=8), make_grid(val_mask_batch, nrow=8)], dim=2)","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:48.099384Z","iopub.execute_input":"2022-08-07T06:27:48.099762Z","iopub.status.idle":"2022-08-07T06:27:48.312790Z","shell.execute_reply.started":"2022-08-07T06:27:48.099726Z","shell.execute_reply":"2022-08-07T06:27:48.311917Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"show_image(train_batch, \"Training Batch\")","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:48.313973Z","iopub.execute_input":"2022-08-07T06:27:48.314410Z","iopub.status.idle":"2022-08-07T06:27:50.589569Z","shell.execute_reply.started":"2022-08-07T06:27:48.314368Z","shell.execute_reply":"2022-08-07T06:27:50.588715Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"show_image(val_batch, \"Validation Batch\")","metadata":{"execution":{"iopub.status.busy":"2022-08-07T06:27:50.590626Z","iopub.execute_input":"2022-08-07T06:27:50.590841Z","iopub.status.idle":"2022-08-07T06:27:52.827192Z","shell.execute_reply.started":"2022-08-07T06:27:50.590814Z","shell.execute_reply":"2022-08-07T06:27:52.826434Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Thus we conclude the data preparation step. \nSummary :\nIn this notebook we learnt :\n1. how to process the data shapes form the image ids.\n2. Process mask from RLE format.\n3. Create custom dataset and dataloader for training purpose.\n\n\n# If you liked the work, please UPVOTE :)\n\nDo follow me on [**LinkedIn**](https://linkedin.com/in/sagnik1511) , [**GitHub**](https://github.com/sagnik1511) and on [**Kaggle**](https://kaggle.com/sagnik1511)\n\n# Thanks for visiting :D\n","metadata":{}}]}