{"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_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"!pip install efficientnet","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:42.038327Z","iopub.execute_input":"2023-03-08T19:43:42.038694Z","iopub.status.idle":"2023-03-08T19:43:51.027828Z","shell.execute_reply.started":"2023-03-08T19:43:42.038662Z","shell.execute_reply":"2023-03-08T19:43:51.026452Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras import layers\nimport tensorflow_datasets as tfds\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport tifffile as tiff \nimport cv2\nfrom skimage.transform import resize\nimport seaborn as sns\nfrom skimage.color import rgb2gray\n\nimport albumentations as A\n\nfrom tensorflow.keras.applications import EfficientNetB4\nimport efficientnet.keras as efn\n\nfrom PIL import Image, ImageOps\nfrom skimage import color\n\ntf.config.experimental_run_functions_eagerly(True)\nBASE_PATH = \"../input/hubmap-organ-segmentation/\"","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-03-08T19:43:51.030588Z","iopub.execute_input":"2023-03-08T19:43:51.031011Z","iopub.status.idle":"2023-03-08T19:43:51.039283Z","shell.execute_reply.started":"2023-03-08T19:43:51.030967Z","shell.execute_reply":"2023-03-08T19:43:51.038117Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"![image.png](attachment:2667768a-3253-4c1f-858e-f075aaa7f01c.png) ![image.png](attachment:a1b045a7-852d-419c-a107-783b1027a440.png)\n\n**For EDA and Loss Function - https://www.kaggle.com/code/muki2003/hubmap-tensorflow-eda-loss-function**","metadata":{},"attachments":{"2667768a-3253-4c1f-858e-f075aaa7f01c.png":{"image/png":"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"},"a1b045a7-852d-419c-a107-783b1027a440.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"# **Meta and Image Data**","metadata":{}},{"cell_type":"code","source":"train = pd.read_csv('../input/hubmap-organ-segmentation/train.csv')\ntest = pd.read_csv('../input/hubmap-organ-segmentation/test.csv')","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:51.040820Z","iopub.execute_input":"2023-03-08T19:43:51.041210Z","iopub.status.idle":"2023-03-08T19:43:51.396587Z","shell.execute_reply.started":"2023-03-08T19:43:51.041176Z","shell.execute_reply":"2023-03-08T19:43:51.395560Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:51.399011Z","iopub.execute_input":"2023-03-08T19:43:51.399292Z","iopub.status.idle":"2023-03-08T19:43:51.436939Z","shell.execute_reply.started":"2023-03-08T19:43:51.399265Z","shell.execute_reply":"2023-03-08T19:43:51.436052Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Train Pie Chart\ndef pie_target(feat,df):\n    fig, ax = plt.subplots(4,2,figsize=(22,22))\n    for i in enumerate(feat):\n            fig.suptitle('Pie chart and Count Plot', size = 29)\n            ax[i[0],0].title.set_text(f'Pie of {i[1]}')\n            labels = list(df[i[1]].value_counts().index)\n            values = df[i[1]].value_counts()\n            \n            ax[i[0],0].pie(values,startangle=60, labels=labels,autopct='%1.0f%%', pctdistance=0.6)\n            ax[i[0],1].title.set_text(f'Count Plot for {i[1]}')\n            sns.countplot(x=i[1],data=df ,ax=ax[i[0],1])\n            ax[i[0],0].add_artist(plt.Circle((0,0),0.4,fc='white'))\n    fig.tight_layout()        \n    plt.show()\n    \ncat_features=['tissue_thickness','age','organ','sex']\npie_target(cat_features,train)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:51.438235Z","iopub.execute_input":"2023-03-08T19:43:51.438681Z","iopub.status.idle":"2023-03-08T19:43:53.083563Z","shell.execute_reply.started":"2023-03-08T19:43:51.438644Z","shell.execute_reply":"2023-03-08T19:43:53.082530Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## **Masking and Unmaksing Function**","metadata":{}},{"cell_type":"code","source":"def rle2mask(rle, width, target_size=None):\n    if target_size == None:\n        target_size = width\n\n    rle = np.array(list(map(int, rle.split())))\n    label = np.zeros((width*width))\n    \n    for start, end in zip(rle[::2], rle[1::2]):\n        label[start:start+end] = 1\n        \n    #Convert label to image\n    label = Image.fromarray(label.reshape(width, width))\n    #Resize label\n    label = label.resize((target_size, target_size))\n    label = np.array(label).astype(float)\n    #rescale label\n    label = np.round((label - label.min())/(label.max() - label.min()))\n    \n    return label.T\n\ndef mask2rle(mask, orig_dim=160):\n    #Rescale image to original size\n    size = int(len(mask.flatten())**.5)\n    n = Image.fromarray(mask.reshape((size, size))*255.0)\n    n = n.resize((orig_dim, orig_dim))\n    n = np.array(n).astype(np.float32)\n    #Get pixels to flatten\n    pixels = n.T.flatten()\n    #Round the pixels using the half of the range of pixel value\n    pixels = (pixels-min(pixels) > ((max(pixels)-min(pixels))/2)).astype(int)\n    pixels = np.nan_to_num(pixels) #incase of zero-div-error\n    \n    pixels = np.concatenate([[0], pixels, [0]])\n    runs = np.where(pixels[1:] != pixels[:-1])[0]\n    runs[1::2] -= runs[::2]\n    \n    return ' '.join(str(x) for x in runs)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:53.084602Z","iopub.execute_input":"2023-03-08T19:43:53.084960Z","iopub.status.idle":"2023-03-08T19:43:53.096974Z","shell.execute_reply.started":"2023-03-08T19:43:53.084921Z","shell.execute_reply":"2023-03-08T19:43:53.095863Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# **Organ Data Generator**","metadata":{}},{"cell_type":"code","source":"class ImageDataGenerator(tf.keras.utils.Sequence):\n    def __init__(self, df, batch_size=32, train=False, size=256):\n        self.df = df.reset_index(drop=True)\n        self.dim = size\n        self.train = train\n        if self.train: self.batch_size = batch_size // 4\n        else: self.batch_size = batch_size\n        self.pref = 'train' if train else 'test'\n    \n    def __len__(self):\n        return np.ceil(len(self.df) / self.batch_size).astype(int)\n    \n    def on_epoch_end(self):\n        if self.train: #Reshuffle train on end of epoch\n            self.df = self.df.sample(frac=1.0).reset_index(drop=True)\n            \n    def __getitem__(self, idx):\n        batch_x = self.df.iloc[idx*self.batch_size:(idx+1)*self.batch_size].id.values\n        \n        if not self.train:\n            X = np.zeros((batch_x.shape[0], self.dim, self.dim, 3))\n            \n            for i in range(batch_x.shape[0]):\n                image = Image.open(f\"../input/hubmap-organ-segmentation/{self.pref}_images/{batch_x[i]}.tiff\")\n                image = image.resize((self.dim, self.dim))\n                image = np.array(image) / 255.\n                X[i,] = image\n                \n            return X\n                \n        else:\n            batch_y = self.df.iloc[idx*self.batch_size:(idx+1)*self.batch_size].rle.values\n            batch_w = self.df.iloc[idx*self.batch_size:(idx+1)*self.batch_size].img_width.values\n            #print(batch_y, batch_w)\n            X = np.zeros((batch_x.shape[0]*4, self.dim, self.dim, 3))\n            Y = np.zeros((batch_x.shape[0]*4, self.dim, self.dim, 1))\n            \n            for i in range(batch_x.shape[0]):\n                image = Image.open(f\"../input/hubmap-organ-segmentation/{self.pref}_images/{batch_x[i]}.tiff\")\n                image = image.resize((self.dim, self.dim))\n                image = np.array(image)\n                #image = np.array(image) / 255\n                rle = rle2mask(batch_y[i], batch_w[i], self.dim)\n                rle = rle.reshape((self.dim, self.dim, 1))\n\n                for n, (h, v) in enumerate([(0, 0), (0, 1), (1, 0), (1, 1)]):\n                    X[i*4 + n, :, :, :], Y[i*4 + n, :, :, :] = self.augumention(image,rle)\n                    \n            return X, Y#.reshape(Y.shape[:-1])\n                \n    def getAuguments(self):\n        auguments = [\n                A.Blur(blur_limit=7, always_apply=False, p=0.5),\n                A.CLAHE(clip_limit=5.0, tile_grid_size=(8, 8), always_apply=False, p=0.66),\n                A.RandomBrightnessContrast(brightness_limit=0.3, contrast_limit=0.3, p=0.5),\n                A.Posterize (num_bits=6, p=0.3),\n                A.RandomGamma (gamma_limit=(50, 300), p=0.3),    \n                A.Sharpen (alpha=(0.2, 0.7), lightness=(0.7, 1.0), p=0.4),\n                A.Flip(p=0.5),\n                A.ElasticTransform (alpha_affine=60, p=0.5),\n                A.RandomResizedCrop(self.dim,self.dim, p=0.33),\n                A.Rotate (limit=180, p=0.5)\n        ]\n        return A.Compose(auguments)\n    \n    def augumention(self, image,mask):\n        transform = self.getAuguments()\n        transformed = transform(image=image.astype('uint8'), mask=mask.astype('int'))\n        return transformed['image'] / 255, transformed['mask']","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:53.098976Z","iopub.execute_input":"2023-03-08T19:43:53.099881Z","iopub.status.idle":"2023-03-08T19:43:53.119571Z","shell.execute_reply.started":"2023-03-08T19:43:53.099844Z","shell.execute_reply":"2023-03-08T19:43:53.118624Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_loader = ImageDataGenerator(train, 8, True, 256)\ndataget_check = train_loader.__getitem__(1)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:53.121087Z","iopub.execute_input":"2023-03-08T19:43:53.121513Z","iopub.status.idle":"2023-03-08T19:43:55.112552Z","shell.execute_reply.started":"2023-03-08T19:43:53.121472Z","shell.execute_reply":"2023-03-08T19:43:55.111574Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(20, 20))\nfor i in range(7):\n    plt.figure(figsize=(20, 20))\n    plt.axis('off')\n    plt.subplot(1, 2, 1)\n    plt.imshow(dataget_check[0][i])\n    plt.imshow(dataget_check[1][i], cmap='coolwarm', alpha=0.5)\n    \n    plt.axis('off')\n    plt.subplot(1, 2, 2)\n    plt.imshow(dataget_check[0][i+1])\n    plt.imshow(dataget_check[1][i+1], cmap='coolwarm', alpha=0.5)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:43:55.114170Z","iopub.execute_input":"2023-03-08T19:43:55.114560Z","iopub.status.idle":"2023-03-08T19:44:00.161452Z","shell.execute_reply.started":"2023-03-08T19:43:55.114515Z","shell.execute_reply":"2023-03-08T19:44:00.160615Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## **Graph Plot Visualize**","metadata":{}},{"cell_type":"code","source":"from IPython.display import clear_output\nfrom tensorflow.keras import backend as K\n\nclass PlotLearning(tf.keras.callbacks.Callback):\n    \"\"\"\n    Callback to plot the learning curves of the model during training.\n    \"\"\"\n    def on_train_begin(self, logs={}):\n        self.metrics = {}\n        for metric in logs:\n            self.metrics[metric] = []\n        \n    def on_epoch_end(self, epoch, logs={}):\n        # Storing metrics\n        for metric in logs:\n            if metric in self.metrics:\n                self.metrics[metric].append(logs.get(metric))\n            else:\n                self.metrics[metric] = [logs.get(metric)]\n        \n        # Plotting\n        metrics = [x for x in logs if 'val' not in x]\n        \n        f, axs = plt.subplots(1, len(metrics), figsize=(15,5))\n        clear_output(wait=True)\n\n        for i, metric in enumerate(metrics):\n            axs[i].plot(range(1, epoch + 2), \n                        self.metrics[metric], \n                        label=metric)\n            if logs['val_' + metric]:\n                axs[i].plot(range(1, epoch + 2), \n                            self.metrics['val_' + metric], \n                            label='val_' + metric)\n                \n            axs[i].legend()\n            axs[i].grid()\n\n        plt.tight_layout()\n        plt.show()","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:44:00.165669Z","iopub.execute_input":"2023-03-08T19:44:00.166724Z","iopub.status.idle":"2023-03-08T19:44:00.181046Z","shell.execute_reply.started":"2023-03-08T19:44:00.166687Z","shell.execute_reply":"2023-03-08T19:44:00.179865Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# **PreTrained Segmentation Model**","metadata":{}},{"cell_type":"code","source":"! pip install segmentation-models","metadata":{"scrolled":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:44:00.183170Z","iopub.execute_input":"2023-03-08T19:44:00.183527Z","iopub.status.idle":"2023-03-08T19:44:10.087099Z","shell.execute_reply.started":"2023-03-08T19:44:00.183491Z","shell.execute_reply":"2023-03-08T19:44:10.085857Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"! pip install git+https://github.com/qubvel/segmentation_models","metadata":{"scrolled":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:44:10.089224Z","iopub.execute_input":"2023-03-08T19:44:10.089618Z","iopub.status.idle":"2023-03-08T19:44:21.148038Z","shell.execute_reply.started":"2023-03-08T19:44:10.089578Z","shell.execute_reply":"2023-03-08T19:44:21.146743Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import segmentation_models as sm\nsm.set_framework('tf.keras')\nsm.framework()\n\nfrom segmentation_models import Unet, FPN\nfrom segmentation_models.utils import set_trainable\n\nmodel = Unet('efficientnetb4',input_shape=(512, 512, 3), classes=1, activation='sigmoid', encoder_weights=None)\n\nmodel.summary()","metadata":{"scrolled":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:44:21.149979Z","iopub.execute_input":"2023-03-08T19:44:21.151086Z","iopub.status.idle":"2023-03-08T19:44:26.216526Z","shell.execute_reply.started":"2023-03-08T19:44:21.151039Z","shell.execute_reply":"2023-03-08T19:44:26.215543Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# **Metric's and Loss Function**","metadata":{}},{"cell_type":"code","source":"from keras import backend as K\nfrom keras.losses import binary_crossentropy\nimport tensorflow as tf\n\ndef dice_coef(y_true, y_pred, smooth=1):\n    y_true_f = K.flatten(y_true)\n    y_pred_f = K.flatten(y_pred)\n    intersection = K.sum(y_true_f * y_pred_f)\n    return (2. * intersection + smooth) / (K.sum(y_true_f) + K.sum(y_pred_f) + smooth)\n\ndef iou_coef(y_true, y_pred, smooth=1):\n    intersection = K.sum(K.abs(y_true * y_pred), axis=[1,2,3])\n    union = K.sum(y_true,[1,2,3])+K.sum(y_pred,[1,2,3])-intersection\n    iou = K.mean((intersection + smooth) / (union + smooth), axis=0)\n    return iou\n\n\ndef dice_loss(y_true, y_pred):\n    smooth = 1.\n    y_true_f = K.flatten(y_true)\n    y_pred_f = K.flatten(y_pred)\n    intersection = y_true_f * y_pred_f\n    score = (2. * K.sum(intersection) + smooth) / (K.sum(y_true_f) + K.sum(y_pred_f) + smooth)\n    return 1. - score\n\ndef bce_dice_loss(y_true, y_pred):\n    return binary_crossentropy(tf.cast(y_true, tf.float32), y_pred) + 0.5 * dice_loss(tf.cast(y_true, tf.float32), y_pred)\n\ndef weighted_loss(y_true, y_pred):\n    # Calculate the base loss\n    ce = K.sparse_categorical_crossentropy(y_true, y_pred)\n    # Apply the weights\n    one_weight = 1.0\n    zero_weight = 1e-2\n    weight_vector = y_true * one_weight + (1. - y_true) * zero_weight\n    weight_vector = K.squeeze(weight_vector, axis=-1)\n    weighted_ce = weight_vector * ce\n\n    # Return the mean error\n    return K.mean(weighted_ce)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:44:26.218090Z","iopub.execute_input":"2023-03-08T19:44:26.219289Z","iopub.status.idle":"2023-03-08T19:44:26.231769Z","shell.execute_reply.started":"2023-03-08T19:44:26.219246Z","shell.execute_reply":"2023-03-08T19:44:26.230414Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### **Model Parameters**","metadata":{}},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split as tts\nfrom tensorflow.keras.callbacks import ModelCheckpoint\n\n#We will be training a model for each organ\norgans = train.organ.unique()\nepochs = 30\nimage_size = 512\nbatch_size = 4\nprint(\"Organs:\", organs)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:44:26.233291Z","iopub.execute_input":"2023-03-08T19:44:26.233735Z","iopub.status.idle":"2023-03-08T19:44:26.258889Z","shell.execute_reply.started":"2023-03-08T19:44:26.233688Z","shell.execute_reply":"2023-03-08T19:44:26.257836Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# **Model Training and Evaluation**","metadata":{}},{"cell_type":"code","source":"def train_organ(organ):\n    print(\"Training for organ:\", organ)\n\n    model = Unet('efficientnetb4',input_shape=(512, 512, 3), classes=1, activation='sigmoid', encoder_weights=None)\n    model.compile(loss=bce_dice_loss, optimizer=tf.keras.optimizers.Adam(learning_rate=1e-4),metrics=['accuracy', dice_coef])\n\n    save_best = ModelCheckpoint(f\"{organ}_model.h5\", monitor='val_dice_coef', save_best_only=True, mode='max', verbose=True)\n\n    X = train[train.organ == organ].reset_index(drop=True)\n    train_X, valid_X = tts(X, test_size=0.15, shuffle=True, random_state=2021)\n    train_loader = ImageDataGenerator(train_X, batch_size, True, image_size)\n    valid_loader = ImageDataGenerator(valid_X, batch_size, True, image_size)\n\n    history = model.fit(train_loader,validation_data=valid_loader,epochs=epochs,use_multiprocessing=False,callbacks=[PlotLearning(), save_best])\n\n    # Model Evaluation and Predidtion\n    model = tf.keras.models.load_model(f\"{organ}_model.h5\",compile=False)\n    tx, ty = valid_loader[0]\n    pty = model.predict(tx).round()\n\n    # Orginal Image VS Mask\n    plt.figure(figsize=(20, 20))\n    for i in range(4):\n        plt.figure(figsize=(20, 20))\n        plt.subplot(1, 2, 1)\n        plt.title('Orginal')\n        plt.imshow(tx[i])\n        plt.imshow(ty[i], cmap='coolwarm', alpha=0.5)\n        plt.subplot(1, 2, 2)\n        plt.title('Predicted')\n        plt.imshow(tx[i])\n        plt.imshow(pty[i], cmap='coolwarm', alpha=0.5)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:44:26.260228Z","iopub.execute_input":"2023-03-08T19:44:26.261222Z","iopub.status.idle":"2023-03-08T19:44:26.272496Z","shell.execute_reply.started":"2023-03-08T19:44:26.261185Z","shell.execute_reply":"2023-03-08T19:44:26.271520Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_organ(organs[0])\nprint(\"Training Complected for\", organs[0])","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:44:26.274114Z","iopub.execute_input":"2023-03-08T19:44:26.274500Z","iopub.status.idle":"2023-03-08T19:46:12.930664Z","shell.execute_reply.started":"2023-03-08T19:44:26.274462Z","shell.execute_reply":"2023-03-08T19:46:12.929159Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_organ(organs[1])\nprint(\"Training Complected for\", organs[1])","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:46:12.931927Z","iopub.status.idle":"2023-03-08T19:46:12.933390Z","shell.execute_reply.started":"2023-03-08T19:46:12.933029Z","shell.execute_reply":"2023-03-08T19:46:12.933060Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_organ(organs[2])\nprint(\"Training Complected for\", organs[2])","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:46:12.935104Z","iopub.status.idle":"2023-03-08T19:46:12.935589Z","shell.execute_reply.started":"2023-03-08T19:46:12.935335Z","shell.execute_reply":"2023-03-08T19:46:12.935358Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_organ(organs[3])\nprint(\"Training Complected for\", organs[3])","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:46:12.937728Z","iopub.status.idle":"2023-03-08T19:46:12.938821Z","shell.execute_reply.started":"2023-03-08T19:46:12.938538Z","shell.execute_reply":"2023-03-08T19:46:12.938563Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_organ(organs[4])\nprint(\"Training Complected for\", organs[4])","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2023-03-08T19:46:12.940365Z","iopub.status.idle":"2023-03-08T19:46:12.941167Z","shell.execute_reply.started":"2023-03-08T19:46:12.940904Z","shell.execute_reply":"2023-03-08T19:46:12.940930Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# **Test Prediction**","metadata":{}},{"cell_type":"code","source":"test_df = pd.read_csv('../input/hubmap-organ-segmentation/test.csv')\nsub = {'id':[], 'rle':[]}\n\nfor organ in organs:\n    print(\"Predicting on organ:\", organ)\n\n    test_X = test_df[test_df.organ == organ].reset_index(drop=True)\n    if len(test_X) == 0: continue #Skip organs without item in test\n        \n    model = tf.keras.models.load_model(f\"./{organ}_model.h5\", compile=False)\n    \n    test_loader = ImageDataGenerator(test_X, batch_size, False,512)\n    preds = model.predict(test_loader)\n    rle = [mask2rle(m, d) for m,d in zip(preds.round(), test_X.img_width)]\n    sub['id'] += test_X.id.values.tolist()\n    sub['rle'] += rle\n    \n    \nsub = pd.DataFrame(sub)\ntest_df = test_df.merge(sub, on='id')\nsub = test_df[['id', 'rle']].copy()\nsub.to_csv('submission.csv', index=False)\nsub","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:46:12.942571Z","iopub.status.idle":"2023-03-08T19:46:12.943352Z","shell.execute_reply.started":"2023-03-08T19:46:12.943088Z","shell.execute_reply":"2023-03-08T19:46:12.943113Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(20, 20))\nfor i in range(1):\n    plt.figure(figsize=(20, 20))\n    plt.subplot(1, 2, 1)\n    plt.title('Orginal')\n    plt.imshow(test_loader[0][0])\n    plt.subplot(1, 2, 2)\n    plt.title('Predicted')\n    plt.imshow(test_loader[0][0])\n    plt.imshow(preds[i], cmap='coolwarm', alpha=0.5)","metadata":{"execution":{"iopub.status.busy":"2023-03-08T19:46:12.944776Z","iopub.status.idle":"2023-03-08T19:46:12.945575Z","shell.execute_reply.started":"2023-03-08T19:46:12.945303Z","shell.execute_reply":"2023-03-08T19:46:12.945328Z"},"trusted":true},"execution_count":null,"outputs":[]}]}