{"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)\nfrom keras.preprocessing.image import ImageDataGenerator\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/cats_dogs/CATS_DOGS/train\"))\n\ntrain_datagen=ImageDataGenerator(rotation_range=30,width_shift_range=0.1,height_shift_range=0.1,rescale=1/255,\n                             shear_range=0.2,zoom_range=0.2\n                            ,horizontal_flip=True,fill_mode='nearest')\ntrain_datagen.flow_from_directory('../input/cats_dogs/CATS_DOGS/train')\n\ntest_datagen=ImageDataGenerator(rotation_range=30,width_shift_range=0.1,height_shift_range=0.1,rescale=1/255,\n                             shear_range=0.2,zoom_range=0.2\n                            ,horizontal_flip=True,fill_mode='nearest')\ntest_datagen.flow_from_directory('../input/cats_dogs/CATS_DOGS/test')    \n\n# Any results you write to the current directory are saved as output.","execution_count":17,"outputs":[{"output_type":"stream","text":"['CAT', 'DOG']\nFound 18743 images belonging to 2 classes.\nFound 6251 images belonging to 2 classes.\n","name":"stdout"},{"output_type":"execute_result","execution_count":17,"data":{"text/plain":"<keras_preprocessing.image.directory_iterator.DirectoryIterator at 0x7f4c61bcca90>"},"metadata":{}}]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"from keras.models import Sequential\nfrom keras.layers import Dense, Conv2D, Flatten,MaxPooling2D,Dropout\nfrom keras import layers\n\n\nmodel = Sequential()\nmodel.add(layers.Conv2D(32, (3, 3), input_shape=(64,64,3)))\nmodel.add(layers.Activation('relu'))\nmodel.add(layers.MaxPooling2D(pool_size=(2, 2)))\n\nmodel.add(layers.Conv2D(32, (3, 3)))\nmodel.add(layers.Activation('relu'))\nmodel.add(layers.MaxPooling2D(pool_size=(2, 2)))\n\nmodel.add(layers.Conv2D(64, (3, 3)))\nmodel.add(layers.Activation('relu'))\nmodel.add(layers.MaxPooling2D(pool_size=(2, 2)))\n\nmodel.add(layers.Flatten())\nmodel.add(layers.Dense(64))\nmodel.add(layers.Activation('relu'))\n#model.add(layers.Dropout(0.5))\nmodel.add(layers.Dense(1))\nmodel.add(layers.Activation('sigmoid'))\n\nmodel.compile(optimizer='adam',loss='binary_crossentropy',metrics=['accuracy'])\n\nmodel.summary()\n#model.fit(Xtr, Ytr,batch_size=32, validation_data=(Xte, Yte), epochs=8)\n\n     \n        ","execution_count":18,"outputs":[{"output_type":"stream","text":"_________________________________________________________________\nLayer (type)                 Output Shape              Param #   \n=================================================================\nconv2d_7 (Conv2D)            (None, 62, 62, 32)        896       \n_________________________________________________________________\nactivation_11 (Activation)   (None, 62, 62, 32)        0         \n_________________________________________________________________\nmax_pooling2d_7 (MaxPooling2 (None, 31, 31, 32)        0         \n_________________________________________________________________\nconv2d_8 (Conv2D)            (None, 29, 29, 32)        9248      \n_________________________________________________________________\nactivation_12 (Activation)   (None, 29, 29, 32)        0         \n_________________________________________________________________\nmax_pooling2d_8 (MaxPooling2 (None, 14, 14, 32)        0         \n_________________________________________________________________\nconv2d_9 (Conv2D)            (None, 12, 12, 64)        18496     \n_________________________________________________________________\nactivation_13 (Activation)   (None, 12, 12, 64)        0         \n_________________________________________________________________\nmax_pooling2d_9 (MaxPooling2 (None, 6, 6, 64)          0         \n_________________________________________________________________\nflatten_3 (Flatten)          (None, 2304)              0         \n_________________________________________________________________\ndense_5 (Dense)              (None, 64)                147520    \n_________________________________________________________________\nactivation_14 (Activation)   (None, 64)                0         \n_________________________________________________________________\ndense_6 (Dense)              (None, 1)                 65        \n_________________________________________________________________\nactivation_15 (Activation)   (None, 1)                 0         \n=================================================================\nTotal params: 176,225\nTrainable params: 176,225\nNon-trainable params: 0\n_________________________________________________________________\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"training_set=train_datagen.flow_from_directory(directory=\"../input/cats_dogs/CATS_DOGS/train\",target_size=(64,64),class_mode='binary')\ntesting_set=test_datagen.flow_from_directory(directory=\"../input/cats_dogs/CATS_DOGS/train\",target_size=(64,64),class_mode='binary')\n\nmodel.fit_generator(training_set,steps_per_epoch = 8000//32,epochs =20 ,validation_data = testing_set,validation_steps = 2000//32)","execution_count":19,"outputs":[{"output_type":"stream","text":"Found 18743 images belonging to 2 classes.\nFound 18743 images belonging to 2 classes.\nWARNING:tensorflow:From /opt/conda/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\nInstructions for updating:\nUse tf.cast instead.\nEpoch 1/20\n 27/250 [==>...........................] - ETA: 1:15 - loss: 0.6954 - acc: 0.5058","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 80000 bytes but only got 0. Skipping tag 64640\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 65536 bytes but only got 0. Skipping tag 3\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 404094976 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 404619264 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 131072 bytes but only got 0. Skipping tag 3\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 425459712 bytes but only got 0. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 1385474 bytes but only got 6833. Skipping tag 513\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 3846701056 bytes but only got 0. Skipping tag 2\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 3300917248 bytes but only got 0. Skipping tag 7\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 196867 bytes but only got 6833. Skipping tag 0\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:756: UserWarning: Corrupt EXIF data.  Expecting to read 12 bytes but only got 8. \n  warnings.warn(str(msg))\n","name":"stderr"},{"output_type":"stream","text":" 39/250 [===>..........................] - ETA: 1:09 - loss: 0.6942 - acc: 0.5184","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 262146 bytes but only got 0. Skipping tag 2\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 262151 bytes but only got 0. Skipping tag 56\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:756: UserWarning: Corrupt EXIF data.  Expecting to read 12 bytes but only got 0. \n  warnings.warn(str(msg))\n","name":"stderr"},{"output_type":"stream","text":" 46/250 [====>.........................] - ETA: 1:06 - loss: 0.6933 - acc: 0.5190","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 18350080 bytes but only got 0. Skipping tag 0\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:756: UserWarning: Corrupt EXIF data.  Expecting to read 12 bytes but only got 6. \n  warnings.warn(str(msg))\n","name":"stderr"},{"output_type":"stream","text":"250/250 [==============================] - 90s 359ms/step - loss: 0.6811 - acc: 0.5599 - val_loss: 0.6355 - val_acc: 0.6598\nEpoch 2/20\n 25/250 [==>...........................] - ETA: 51s - loss: 0.6733 - acc: 0.5800","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 307363840 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 307888128 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 328728576 bytes but only got 0. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 1385474 bytes but only got 5357. Skipping tag 513\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 196867 bytes but only got 5357. Skipping tag 0\n  \" Skipping tag %s\" % (size, len(data), tag))\n","name":"stderr"},{"output_type":"stream","text":"211/250 [========================>.....] - ETA: 11s - loss: 0.6453 - acc: 0.6238","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 209715200 bytes but only got 0. Skipping tag 48\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 52428800 bytes but only got 0. Skipping tag 0\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 6468665344 bytes but only got 0. Skipping tag 0\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 1050744 bytes but only got 7027. Skipping tag 48\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 422313984 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 422838272 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 3368026112 bytes but only got 0. Skipping tag 7\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 134479872 bytes but only got 0. Skipping tag 7\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 428867584 bytes but only got 0. Skipping tag 10\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 429391872 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 2031616 bytes but only got 0. Skipping tag 3\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 429916160 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 21299200 bytes but only got 0. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 24313856 bytes but only got 0. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 453771264 bytes but only got 7032. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 131073 bytes but only got 7028. Skipping tag 0\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 393216 bytes but only got 0. Skipping tag 3\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 416415744 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 416940032 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 524288 bytes but only got 0. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 415825920 bytes but only got 7032. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:756: UserWarning: Corrupt EXIF data.  Expecting to read 12 bytes but only got 2. \n  warnings.warn(str(msg))\n","name":"stderr"},{"output_type":"stream","text":"213/250 [========================>.....] - ETA: 10s - loss: 0.6454 - acc: 0.6232","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 6553600 bytes but only got 0. Skipping tag 49\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 1050744 bytes but only got 4951. Skipping tag 51\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 293339136 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 293863424 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 295698432 bytes but only got 0. Skipping tag 10\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 296222720 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 14745600 bytes but only got 0. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 25624576 bytes but only got 0. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 317718528 bytes but only got 4956. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 131073 bytes but only got 4952. Skipping tag 0\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 287178752 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 287703040 bytes but only got 0. Skipping tag 5\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 286654464 bytes but only got 4956. Skipping tag 4\n  \" Skipping tag %s\" % (size, len(data), tag))\n","name":"stderr"},{"output_type":"stream","text":"250/250 [==============================] - 83s 332ms/step - loss: 0.6417 - acc: 0.6286 - val_loss: 0.6273 - val_acc: 0.6310\nEpoch 3/20\n 18/250 [=>............................] - ETA: 43s - loss: 0.6165 - acc: 0.6667","name":"stdout"},{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 32 bytes but only got 0. Skipping tag 270\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 5 bytes but only got 0. Skipping tag 271\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 8 bytes but only got 0. Skipping tag 272\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 8 bytes but only got 0. Skipping tag 282\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 8 bytes but only got 0. Skipping tag 283\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 20 bytes but only got 0. Skipping tag 306\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:739: UserWarning: Possibly corrupt EXIF data.  Expecting to read 48 bytes but only got 0. Skipping tag 532\n  \" Skipping tag %s\" % (size, len(data), tag))\n/opt/conda/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:756: UserWarning: Corrupt EXIF data.  Expecting to read 2 bytes but only got 0. \n  warnings.warn(str(msg))\n","name":"stderr"},{"output_type":"stream","text":"250/250 [==============================] - 74s 297ms/step - loss: 0.5987 - acc: 0.6814 - val_loss: 0.5903 - val_acc: 0.6875\nEpoch 4/20\n250/250 [==============================] - 72s 288ms/step - loss: 0.5766 - acc: 0.6965 - val_loss: 0.6226 - val_acc: 0.6704\nEpoch 5/20\n250/250 [==============================] - 72s 287ms/step - loss: 0.5681 - acc: 0.7084 - val_loss: 0.5448 - val_acc: 0.7238\nEpoch 6/20\n250/250 [==============================] - 71s 283ms/step - loss: 0.5465 - acc: 0.7240 - val_loss: 0.5201 - val_acc: 0.7359\nEpoch 7/20\n250/250 [==============================] - 71s 282ms/step - loss: 0.5366 - acc: 0.7298 - val_loss: 0.5253 - val_acc: 0.7450\nEpoch 8/20\n250/250 [==============================] - 71s 283ms/step - loss: 0.5279 - acc: 0.7351 - val_loss: 0.4993 - val_acc: 0.7606\nEpoch 9/20\n250/250 [==============================] - 72s 287ms/step - loss: 0.5144 - acc: 0.7495 - val_loss: 0.5060 - val_acc: 0.7545\nEpoch 10/20\n250/250 [==============================] - 70s 281ms/step - loss: 0.5043 - acc: 0.7533 - val_loss: 0.5241 - val_acc: 0.7458\nEpoch 11/20\n250/250 [==============================] - 71s 283ms/step - loss: 0.4975 - acc: 0.7598 - val_loss: 0.5044 - val_acc: 0.7495\nEpoch 12/20\n250/250 [==============================] - 70s 282ms/step - loss: 0.4829 - acc: 0.7653 - val_loss: 0.4287 - val_acc: 0.7979\nEpoch 13/20\n250/250 [==============================] - 71s 284ms/step - loss: 0.4717 - acc: 0.7734 - val_loss: 0.4688 - val_acc: 0.7792\nEpoch 14/20\n250/250 [==============================] - 71s 285ms/step - loss: 0.4719 - acc: 0.7729 - val_loss: 0.4282 - val_acc: 0.7974\nEpoch 15/20\n250/250 [==============================] - 71s 282ms/step - loss: 0.4546 - acc: 0.7896 - val_loss: 0.4794 - val_acc: 0.7732\nEpoch 16/20\n250/250 [==============================] - 71s 282ms/step - loss: 0.4553 - acc: 0.7855 - val_loss: 0.4660 - val_acc: 0.7727\nEpoch 17/20\n250/250 [==============================] - 71s 284ms/step - loss: 0.4434 - acc: 0.7898 - val_loss: 0.4285 - val_acc: 0.7944\nEpoch 18/20\n250/250 [==============================] - 73s 290ms/step - loss: 0.4210 - acc: 0.8021 - val_loss: 0.4127 - val_acc: 0.8095\nEpoch 19/20\n250/250 [==============================] - 72s 289ms/step - loss: 0.4448 - acc: 0.7880 - val_loss: 0.4354 - val_acc: 0.7995\nEpoch 20/20\n250/250 [==============================] - 71s 284ms/step - loss: 0.4314 - acc: 0.8006 - val_loss: 0.4085 - val_acc: 0.8185\n","name":"stdout"},{"output_type":"execute_result","execution_count":19,"data":{"text/plain":"<keras.callbacks.History at 0x7f4c61cbd860>"},"metadata":{}}]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}