{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(os.listdir(\"../input\"))\n\n# Any results you write to the current directory are saved as output.","execution_count":51,"outputs":[{"output_type":"stream","text":"['train', 'test', 'metadata.csv', 'train_masks.csv', 'sample_submission.csv', 'train_masks']\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from glob import glob\nfrom sklearn.model_selection import train_test_split\nfrom skimage.transform import resize\nimport cv2\nfrom scipy.misc import imresize\nfrom PIL import Image\nfrom scipy import ndimage\nimport matplotlib.pyplot as plt","execution_count":62,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"input_folder = '../input'\n\ntrain= glob('/'.join([input_folder,'train/*.jpg']))\ntrain_masks= glob('/'.join([input_folder,'train_masks/*.gif']))\ntest= glob('/'.join([input_folder,'test/*.jpg']))\nprint('Number of training images: ', len(train), 'Number of corresponding masks: ', len(train_masks), 'Number of test images: ', len(test))","execution_count":63,"outputs":[{"output_type":"stream","text":"Number of training images:  5088 Number of corresponding masks:  5088 Number of test images:  100064\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"tt_ratio = 0.8\nimg_rows, img_cols = 1024,1024\nbatch_size = 8\ndef dice_coef(y_true, y_pred, smooth=0):\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)","execution_count":64,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#split the training set into train and validation samples\ntrain_images, validation_images = train_test_split(train, train_size=tt_ratio, test_size=1-tt_ratio)\nprint('Size of the training sample=', len(train_images), 'and size of the validation sample=', len(validation_images), ' images')","execution_count":65,"outputs":[{"output_type":"stream","text":"Size of the training sample= 4070 and size of the validation sample= 1018  images\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"#utility function to convert greyscale images to rgb\ndef grey2rgb(img):\n    new_img = []\n    for i in range(img.shape[0]):\n        for j in range(img.shape[1]):\n            new_img.append(list(img[i][j])*3)\n    new_img = np.array(new_img).reshape(img.shape[0], img.shape[1], 3)\n    return new_img","execution_count":66,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#generator that will be used to read data from the directory\ndef data_generator(data_dir, masks, images, dims, batch_size=batch_size):\n    while True:\n        ix=np.random.choice(np.arange(len(images)), batch_size)\n        imgs = []\n        labels = []\n        for i in ix:\n            # images\n            original_img = cv2.imread(images[i])\n            resized_img = imresize(original_img, dims + [3]) \n            array_img = resized_img/255\n            #array_img = array_img.swapaxes(0, 2)\n            imgs.append(array_img)\n            #imgs is a numpy array with dim: (batch size X 128 X 128 3)\n            #print('shape of imgs ', array_img.shape)\n            # masks\n            try:\n                mask_filename = images[i].split(\"/\")[-1]\n                file_name = os.path.splitext(mask_filename)[0]\n                correct_mask = '/'.join([input_folder,'train_masks',file_name+'_mask.gif'])\n                original_mask = Image.open(correct_mask).convert('L')\n                data = np.asarray(original_mask, dtype=\"int32\")\n                resized_mask = imresize(original_mask, dims+[3])\n                array_mask = resized_mask / 255\n                labels.append(array_mask)\n            except Exception as e:\n                labels=None\n            \n        imgs = np.array(imgs)\n        labels = np.array(labels)\n        try:\n            relabel = labels.reshape(-1, dims[0], dims[1], 1)\n            #relabel = relabel.swapaxes(1, 3)\n        except Exception as e:\n            relabel=labels\n        yield imgs, relabel","execution_count":98,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_gen = data_generator('train/', train_masks, train_images, dims=[img_rows, img_cols])\nimg, msk = next(train_gen)\n# train_img = img[0].swapaxes(0,2)\n# train_msk = msk.swapaxes(1,3)\n\nfig, ax = plt.subplots(1,2, figsize=(16, 16))\nax = ax.ravel()\nax[0].imshow(img[0], cmap='gray') \nax[0].set_title('Training Image')\nax[1].imshow(grey2rgb(msk[0]), cmap='gray')\nax[1].set_title('Training Image mask')","execution_count":99,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:10: DeprecationWarning: `imresize` is deprecated!\n`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\nUse ``skimage.transform.resize`` instead.\n  # Remove the CWD from sys.path while we load stuff.\n/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:23: DeprecationWarning: `imresize` is deprecated!\n`imresize` is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.\nUse ``skimage.transform.resize`` instead.\n","name":"stderr"},{"output_type":"execute_result","execution_count":99,"data":{"text/plain":"Text(0.5, 1.0, 'Training Image mask')"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1152x1152 with 2 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# create an instance of a validation generator:\nvalidation_gen = data_generator('train/', train_masks, validation_images, dims=[img_rows, img_cols])","execution_count":100,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from keras import backend as K\nfrom keras.models import Sequential, Model \nfrom keras.layers import Input, Conv2D, MaxPooling2D, UpSampling2D, Conv2DTranspose, Flatten,concatenate\nfrom keras.callbacks import ModelCheckpoint\nfrom keras.optimizers import Adam, SGD","execution_count":102,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"K.set_image_data_format('channels_last')","execution_count":103,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Model Creation\ninput_x = Input((img_rows, img_cols, 3))\nconv0 = Conv2D(8, 3, activation = 'relu', padding = 'same')(input_x)\nconv0 = Conv2D(8, 3, activation = 'relu', padding = 'same')(conv0)\npool0 = MaxPooling2D(pool_size=(2, 2))(conv0)\n\nconv1 = Conv2D(16, 3, activation = 'relu', padding = 'same')(pool0)\nconv1 = Conv2D(16, 3, activation = 'relu', padding = 'same')(conv1)\npool1 = MaxPooling2D(pool_size=(2, 2))(conv1)\n\nconv2 = Conv2D(32, 3, activation = 'relu', padding = 'same')(pool1)\nconv2 = Conv2D(32, 3, activation = 'relu', padding = 'same')(conv2)\npool2 = MaxPooling2D(pool_size=(2, 2))(conv2)\n\nconv3 = Conv2D(64, 3, activation = 'relu', padding = 'same')(pool2)\nconv3 = Conv2D(64, 3, activation = 'relu', padding = 'same')(conv3)\npool3 = MaxPooling2D(pool_size=(2, 2))(conv3)\n\nconv4 = Conv2D(128, 3, activation = 'relu', padding = 'same')(pool3)\nconv4 = Conv2D(128, 3, activation = 'relu', padding = 'same')(conv4)\npool4 = MaxPooling2D(pool_size=(2, 2))(conv4)\n\nconv5 = Conv2D(256, 3, activation = 'relu', padding = 'same')(pool4)\nconv5 = Conv2D(256, 3, activation = 'relu', padding = 'same')(conv5)\n\nup6 = UpSampling2D(size = (2,2))(conv5)\nup6 = Conv2D(128, 2, activation = 'relu', padding = 'same')(up6)\nmerge6 = concatenate([conv4,up6], axis = 1)\nconv6 = Conv2D(128, 3, activation = 'relu', padding = 'same')(merge6)\nconv6 = Conv2D(128, 3, activation = 'relu', padding = 'same')(conv6)\n\nup7 = UpSampling2D(size = (2,2))(conv6)\nup7 = Conv2D(64, 2, activation = 'relu', padding = 'same')(up7)\nmerge7 = concatenate([conv3,up7], axis = 1)\nconv7 = Conv2D(64, 3, activation = 'relu', padding = 'same')(merge7)\nconv7 = Conv2D(64, 3, activation = 'relu', padding = 'same')(conv7)\n\nup8 = UpSampling2D(size = (2,2))(conv7)\nup8 = Conv2D(32, 2, activation = 'relu', padding = 'same')(up8)\nmerge8 = concatenate([conv2,up8], axis = 1)\nconv8 = Conv2D(32, 3, activation = 'relu', padding = 'same')(merge8)\nconv8 = Conv2D(32, 3, activation = 'relu', padding = 'same')(conv8)\n\nup9 = UpSampling2D(size = (2,2))(conv8)\nup9 = Conv2D(16, 2, activation = 'relu', padding = 'same')(up9)\nmerge9 = concatenate([conv1,up9], axis = 1)\nconv9 = Conv2D(16, 3, activation = 'relu', padding = 'same')(merge9)\nconv9 = Conv2D(16, 3, activation = 'relu', padding = 'same')(conv9)\n\nup10 = UpSampling2D(size = (2,2))(conv9)\nup10 = Conv2D(16, 2, activation = 'relu', padding = 'same')(up10)\n\nconv10 = Conv2D(8, 3, activation = 'relu', padding = 'same')(up10)\nconv11 = Conv2D(1, 1, activation = 'sigmoid')(conv10)\n\nmodel = Model(inputs = input_x, outputs = conv11)\n\nmodel.compile(optimizer= Adam(lr=0.0005), loss='binary_crossentropy', metrics=[dice_coef])","execution_count":106,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"model.summary()","execution_count":107,"outputs":[{"output_type":"stream","text":"__________________________________________________________________________________________________\nLayer (type)                    Output Shape         Param #     Connected to                     \n==================================================================================================\ninput_9 (InputLayer)            (None, 1024, 1024, 3 0                                            \n__________________________________________________________________________________________________\nconv2d_90 (Conv2D)              (None, 1024, 1024, 8 224         input_9[0][0]                    \n__________________________________________________________________________________________________\nconv2d_91 (Conv2D)              (None, 1024, 1024, 8 584         conv2d_90[0][0]                  \n__________________________________________________________________________________________________\nmax_pooling2d_19 (MaxPooling2D) (None, 512, 512, 8)  0           conv2d_91[0][0]                  \n__________________________________________________________________________________________________\nconv2d_92 (Conv2D)              (None, 512, 512, 16) 1168        max_pooling2d_19[0][0]           \n__________________________________________________________________________________________________\nconv2d_93 (Conv2D)              (None, 512, 512, 16) 2320        conv2d_92[0][0]                  \n__________________________________________________________________________________________________\nmax_pooling2d_20 (MaxPooling2D) (None, 256, 256, 16) 0           conv2d_93[0][0]                  \n__________________________________________________________________________________________________\nconv2d_94 (Conv2D)              (None, 256, 256, 32) 4640        max_pooling2d_20[0][0]           \n__________________________________________________________________________________________________\nconv2d_95 (Conv2D)              (None, 256, 256, 32) 9248        conv2d_94[0][0]                  \n__________________________________________________________________________________________________\nmax_pooling2d_21 (MaxPooling2D) (None, 128, 128, 32) 0           conv2d_95[0][0]                  \n__________________________________________________________________________________________________\nconv2d_96 (Conv2D)              (None, 128, 128, 64) 18496       max_pooling2d_21[0][0]           \n__________________________________________________________________________________________________\nconv2d_97 (Conv2D)              (None, 128, 128, 64) 36928       conv2d_96[0][0]                  \n__________________________________________________________________________________________________\nmax_pooling2d_22 (MaxPooling2D) (None, 64, 64, 64)   0           conv2d_97[0][0]                  \n__________________________________________________________________________________________________\nconv2d_98 (Conv2D)              (None, 64, 64, 128)  73856       max_pooling2d_22[0][0]           \n__________________________________________________________________________________________________\nconv2d_99 (Conv2D)              (None, 64, 64, 128)  147584      conv2d_98[0][0]                  \n__________________________________________________________________________________________________\nmax_pooling2d_23 (MaxPooling2D) (None, 32, 32, 128)  0           conv2d_99[0][0]                  \n__________________________________________________________________________________________________\nconv2d_100 (Conv2D)             (None, 32, 32, 256)  295168      max_pooling2d_23[0][0]           \n__________________________________________________________________________________________________\nconv2d_101 (Conv2D)             (None, 32, 32, 256)  590080      conv2d_100[0][0]                 \n__________________________________________________________________________________________________\nup_sampling2d_18 (UpSampling2D) (None, 64, 64, 256)  0           conv2d_101[0][0]                 \n__________________________________________________________________________________________________\nconv2d_102 (Conv2D)             (None, 64, 64, 128)  131200      up_sampling2d_18[0][0]           \n__________________________________________________________________________________________________\nconcatenate_13 (Concatenate)    (None, 128, 64, 128) 0           conv2d_99[0][0]                  \n                                                                 conv2d_102[0][0]                 \n__________________________________________________________________________________________________\nconv2d_103 (Conv2D)             (None, 128, 64, 128) 147584      concatenate_13[0][0]             \n__________________________________________________________________________________________________\nconv2d_104 (Conv2D)             (None, 128, 64, 128) 147584      conv2d_103[0][0]                 \n__________________________________________________________________________________________________\nup_sampling2d_19 (UpSampling2D) (None, 256, 128, 128 0           conv2d_104[0][0]                 \n__________________________________________________________________________________________________\nconv2d_105 (Conv2D)             (None, 256, 128, 64) 32832       up_sampling2d_19[0][0]           \n__________________________________________________________________________________________________\nconcatenate_14 (Concatenate)    (None, 384, 128, 64) 0           conv2d_97[0][0]                  \n                                                                 conv2d_105[0][0]                 \n__________________________________________________________________________________________________\nconv2d_106 (Conv2D)             (None, 384, 128, 64) 36928       concatenate_14[0][0]             \n__________________________________________________________________________________________________\nconv2d_107 (Conv2D)             (None, 384, 128, 64) 36928       conv2d_106[0][0]                 \n__________________________________________________________________________________________________\nup_sampling2d_20 (UpSampling2D) (None, 768, 256, 64) 0           conv2d_107[0][0]                 \n__________________________________________________________________________________________________\nconv2d_108 (Conv2D)             (None, 768, 256, 32) 8224        up_sampling2d_20[0][0]           \n__________________________________________________________________________________________________\nconcatenate_15 (Concatenate)    (None, 1024, 256, 32 0           conv2d_95[0][0]                  \n                                                                 conv2d_108[0][0]                 \n__________________________________________________________________________________________________\nconv2d_109 (Conv2D)             (None, 1024, 256, 32 9248        concatenate_15[0][0]             \n__________________________________________________________________________________________________\nconv2d_110 (Conv2D)             (None, 1024, 256, 32 9248        conv2d_109[0][0]                 \n__________________________________________________________________________________________________\nup_sampling2d_21 (UpSampling2D) (None, 2048, 512, 32 0           conv2d_110[0][0]                 \n__________________________________________________________________________________________________\nconv2d_111 (Conv2D)             (None, 2048, 512, 16 2064        up_sampling2d_21[0][0]           \n__________________________________________________________________________________________________\nconcatenate_16 (Concatenate)    (None, 2560, 512, 16 0           conv2d_93[0][0]                  \n                                                                 conv2d_111[0][0]                 \n__________________________________________________________________________________________________\nconv2d_112 (Conv2D)             (None, 2560, 512, 16 2320        concatenate_16[0][0]             \n__________________________________________________________________________________________________\nconv2d_113 (Conv2D)             (None, 2560, 512, 16 2320        conv2d_112[0][0]                 \n__________________________________________________________________________________________________\nup_sampling2d_22 (UpSampling2D) (None, 5120, 1024, 1 0           conv2d_113[0][0]                 \n__________________________________________________________________________________________________\nconv2d_114 (Conv2D)             (None, 5120, 1024, 1 1040        up_sampling2d_22[0][0]           \n__________________________________________________________________________________________________\nconv2d_115 (Conv2D)             (None, 5120, 1024, 8 1160        conv2d_114[0][0]                 \n__________________________________________________________________________________________________\nconv2d_116 (Conv2D)             (None, 5120, 1024, 1 9           conv2d_115[0][0]                 \n==================================================================================================\nTotal params: 1,748,985\nTrainable params: 1,748,985\nNon-trainable params: 0\n__________________________________________________________________________________________________\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from keras.utils import plot_model\nplot_model(model, to_file='unet_model.png')","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}