6.DataAugmentation-TransferLearning.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"6.DataAugmentation-TransferLearning.ipynb","version":"0.3.2","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","metadata":{"id":"1Lq8oCcoWTNg","colab_type":"text"},"source":["## 6. *Data Augmentation* y *Transfer Learning*\n","### Deep Learning, Introducción práctica con Keras - Segunda parte"]},{"cell_type":"code","metadata":{"id":"cl24hf_DpcvV","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":505},"outputId":"f4b5081b-c38c-47a0-ec0e-41739a2b1aa6","executionInfo":{"status":"ok","timestamp":1567503156605,"user_tz":-120,"elapsed":46671,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}}},"source":["!pip install tensorflow-gpu==2.0.0-alpha0"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Collecting tensorflow-gpu==2.0.0-alpha0\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/1a/66/32cffad095253219d53f6b6c2a436637bbe45ac4e7be0244557210dc3918/tensorflow_gpu-2.0.0a0-cp36-cp36m-manylinux1_x86_64.whl (332.1MB)\n","\u001b[K     |████████████████████████████████| 332.1MB 63kB/s \n","\u001b[?25hRequirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.1.0)\n","Collecting tb-nightly<1.14.0a20190302,>=1.14.0a20190301 (from tensorflow-gpu==2.0.0-alpha0)\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/a9/51/aa1d756644bf4624c03844115e4ac4058eff77acd786b26315f051a4b195/tb_nightly-1.14.0a20190301-py3-none-any.whl (3.0MB)\n","\u001b[K     |████████████████████████████████| 3.0MB 26.7MB/s \n","\u001b[?25hRequirement already satisfied: grpcio>=1.8.6 in 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tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow-gpu==2.0.0-alpha0) (3.1.1)\n","Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow-gpu==2.0.0-alpha0) (0.15.5)\n","Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.6.1->tensorflow-gpu==2.0.0-alpha0) (41.2.0)\n","Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.6->tensorflow-gpu==2.0.0-alpha0) (2.8.0)\n","Installing collected packages: tb-nightly, tf-estimator-nightly, tensorflow-gpu\n","Successfully installed tb-nightly-1.14.0a20190301 tensorflow-gpu-2.0.0a0 tf-estimator-nightly-1.14.0.dev2019030115\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"7j8fvlLyachD","colab_type":"text"},"source":["\n","Carga de los datos\n"]},{"cell_type":"code","metadata":{"id":"P2XgvYTVBrGw","colab_type":"code","outputId":"dc631b77-439f-44a6-9390-d6c6d74a0218","executionInfo":{"status":"ok","timestamp":1567503161201,"user_tz":-120,"elapsed":51259,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":546}},"source":["!wget --no-check-certificate \\\n","  https://www.dropbox.com/s/sshnskxxolkrq9h/cats_and_dogs_small.zip?dl=0 \\\n","  -O /tmp/cats_and_dogs_small.zip\n","\n"],"execution_count":2,"outputs":[{"output_type":"stream","text":["--2019-09-03 09:32:36--  https://www.dropbox.com/s/sshnskxxolkrq9h/cats_and_dogs_small.zip?dl=0\n","Resolving www.dropbox.com (www.dropbox.com)... 162.125.8.1, 2620:100:601b:1::a27d:801\n","Connecting to www.dropbox.com (www.dropbox.com)|162.125.8.1|:443... connected.\n","HTTP request sent, awaiting response... 301 Moved Permanently\n","Location: /s/raw/sshnskxxolkrq9h/cats_and_dogs_small.zip [following]\n","--2019-09-03 09:32:37--  https://www.dropbox.com/s/raw/sshnskxxolkrq9h/cats_and_dogs_small.zip\n","Reusing existing connection to www.dropbox.com:443.\n","HTTP request sent, awaiting response... 302 Found\n","Location: https://uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com/cd/0/inline/An2N0GrDCtW2vKGvCXTIQjfOapqRkjSelxlmm3k1jQLDFF_VAD2N34Il0DjXVU_4q2VfwyJR3VV9CavvcdFnIVqyBJ8fh65nqO7c2_AFluK6dZIWcgfO0MWw5n_mRvWzK0Y/file# [following]\n","--2019-09-03 09:32:37--  https://uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com/cd/0/inline/An2N0GrDCtW2vKGvCXTIQjfOapqRkjSelxlmm3k1jQLDFF_VAD2N34Il0DjXVU_4q2VfwyJR3VV9CavvcdFnIVqyBJ8fh65nqO7c2_AFluK6dZIWcgfO0MWw5n_mRvWzK0Y/file\n","Resolving uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com (uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com)... 162.125.8.6, 2620:100:601b:6::a27d:806\n","Connecting to uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com (uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com)|162.125.8.6|:443... connected.\n","HTTP request sent, awaiting response... 302 FOUND\n","Location: /cd/0/inline2/An1D37ye1gc-m--Qvv882Si9fQMw51BUEQgzFaM4k7uFWPxrrYyvSl168_wsp4vDAz4LJFCtuzT5JzUi53WHhwe672K1YKT8HDHwKfz3dFEk53eSB-UiT9wPQIGkkbphBykt_jbtkPHbzjooulET7K2aHXaG0BK0LWyVczFezqRcbBZTPV3uhit1DbffmsidDrPzjAnua4wPhdONJDHDmsWuYzRL999nniDczlFbz7js0Mp5j69dgqNcZmHIhNjFFO0HVP3kX5JdrTk_giiXk9DRM9cXhvFArNWQsgGpn3ZN9XdMgTnEz6bRNbbpxCoQXuqKuF7wUk0HAO2RqAY38aJDUJoriKJduZ8C8A2_nquL_g/file [following]\n","--2019-09-03 09:32:37--  https://uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com/cd/0/inline2/An1D37ye1gc-m--Qvv882Si9fQMw51BUEQgzFaM4k7uFWPxrrYyvSl168_wsp4vDAz4LJFCtuzT5JzUi53WHhwe672K1YKT8HDHwKfz3dFEk53eSB-UiT9wPQIGkkbphBykt_jbtkPHbzjooulET7K2aHXaG0BK0LWyVczFezqRcbBZTPV3uhit1DbffmsidDrPzjAnua4wPhdONJDHDmsWuYzRL999nniDczlFbz7js0Mp5j69dgqNcZmHIhNjFFO0HVP3kX5JdrTk_giiXk9DRM9cXhvFArNWQsgGpn3ZN9XdMgTnEz6bRNbbpxCoQXuqKuF7wUk0HAO2RqAY38aJDUJoriKJduZ8C8A2_nquL_g/file\n","Reusing existing connection to uc7fb7cf40d9d30b76e22a09a3f3.dl.dropboxusercontent.com:443.\n","HTTP request sent, awaiting response... 200 OK\n","Length: 92708484 (88M) [application/zip]\n","Saving to: ‘/tmp/cats_and_dogs_small.zip’\n","\n","/tmp/cats_and_dogs_ 100%[===================>]  88.41M  39.9MB/s    in 2.2s    \n","\n","2019-09-03 09:32:40 (39.9 MB/s) - ‘/tmp/cats_and_dogs_small.zip’ saved [92708484/92708484]\n","\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"sJN-eZ0YBsYl","colab_type":"code","colab":{}},"source":["import os\n","import zipfile\n","\n","local_zip = '/tmp/cats_and_dogs_small.zip'\n","\n","zip_ref = zipfile.ZipFile(local_zip, 'r')\n","\n","zip_ref.extractall('/tmp')\n","zip_ref.close()\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"ZtsbWwXcBscw","colab_type":"code","colab":{}},"source":["\n","base_dir = '/tmp/cats_and_dogs_small'\n","\n","train_dir =      os.path.join(base_dir, 'train')\n","validation_dir = os.path.join(base_dir, 'validation')\n","test_dir =       os.path.join(base_dir, 'test')\n","\n","# Directorio con las imagenes de training \n","train_cats_dir = os.path.join(train_dir, 'cats')\n","train_dogs_dir = os.path.join(train_dir, 'dogs')\n","\n","# Directorio con las imagenes de validation\n","validation_cats_dir = os.path.join(validation_dir, 'cats')\n","validation_dogs_dir = os.path.join(validation_dir, 'dogs')\n","\n","# Directorio con las imagenes de test\n","test_cats_dir = os.path.join(test_dir, 'cats')\n","test_dogs_dir = os.path.join(test_dir, 'dogs')\n","\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"W9r7wCYmBsix","colab_type":"code","outputId":"94aa1dc1-e4c7-45d8-e625-a8ec3046cfa2","executionInfo":{"status":"ok","timestamp":1567503164479,"user_tz":-120,"elapsed":54520,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":119}},"source":["print('total training cat images :', len(os.listdir(train_cats_dir ) ))\n","print('total training dog images :', len(os.listdir(train_dogs_dir ) ))\n","\n","print('total validation cat images :', len(os.listdir( validation_cats_dir ) ))\n","print('total validation dog images :', len(os.listdir( validation_dogs_dir ) ))\n","\n","print('total test cat images :', len(os.listdir( test_cats_dir ) ))\n","print('total test dog images :', len(os.listdir( test_dogs_dir ) ))\n"],"execution_count":5,"outputs":[{"output_type":"stream","text":["total training cat images : 1000\n","total training dog images : 1000\n","total validation cat images : 500\n","total validation dog images : 500\n","total test cat images : 500\n","total test dog images : 500\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"apH1SGz6n4LA","colab_type":"code","outputId":"c6df5dd5-670a-4447-9514-e05dbaa803d8","executionInfo":{"status":"ok","timestamp":1567503174506,"user_tz":-120,"elapsed":64540,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"resources":{"http://localhost:8080/nbextensions/google.colab/files.js":{"data":"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","ok":true,"headers":[["content-type","application/javascript"]],"status":200,"status_text":""}},"base_uri":"https://localhost:8080/","height":327}},"source":["from numpy import expand_dims\n","from tensorflow.keras.preprocessing.image import load_img\n","from tensorflow.keras.preprocessing.image import img_to_array\n","from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","from matplotlib import pyplot\n","\n","from google.colab import files\n","from tensorflow.keras.preprocessing import image\n"," \n","uploaded=files.upload()\n","for fn in uploaded.keys():\n","  path='/content/' + fn\n","  img=image.load_img(path)\n","  data = img_to_array(img)\n","  samples = expand_dims(data, 0)\n","  \n","  # example of \"rotation_range\"\n","  datagen = ImageDataGenerator(rotation_range=45)\n","\n","  it = datagen.flow(samples, batch_size=1)\n","  for i in range(6):\n","  \tpyplot.subplot(230 + 1 + i)\n","  \tbatch = it.next()\n","  \timage = batch[0].astype('uint8')\n","  \tpyplot.imshow(image)\n","pyplot.show()"],"execution_count":6,"outputs":[{"output_type":"display_data","data":{"text/html":["\n","     <input type=\"file\" id=\"files-24c4a6e2-baa3-4ba9-be4f-460d6a165db5\" name=\"files[]\" multiple disabled />\n","     <output id=\"result-24c4a6e2-baa3-4ba9-be4f-460d6a165db5\">\n","      Upload widget is only available when the cell has been executed in the\n","      current browser session. Please rerun this cell to enable.\n","      </output>\n","      <script src=\"/nbextensions/google.colab/files.js\"></script> "],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Saving Wiliams-foto1.jpg to 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8wTvee8HSHYBZxdhuIoYjnLDV1kRTMm+hzoJhDK0MeKFwqNwSRJF9mWkxqHxKEzVyzXv4+MU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FC37Hr2kn1I4TweN/2AMIirZdizudzivkJKgyI45RD3bIoMpI0YRg8L3o2m02mJtoYksRD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\n74ilZn54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DVivrjo7589xfu9R/uk/+T3yZMTf+OhT/Oxf/wH2bz3Lxz/xaUQSTuidNXTG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\nQmCC\n","text/plain":["<Figure size 432x288 with 6 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"5RgKnvsfKkr8","colab_type":"text"},"source":["### ModelDA: Modelo con *Data Augmentation*"]},{"cell_type":"code","metadata":{"id":"JaBxETn7Kjwj","colab_type":"code","colab":{}},"source":["import tensorflow as tf\n","\n","modelDA = tf.keras.models.Sequential([\n","    tf.keras.layers.Conv2D(32, (3,3), activation='relu', input_shape=(150, 150, 3)),\n","    tf.keras.layers.MaxPooling2D(2, 2),\n","    tf.keras.layers.Conv2D(64, (3,3), activation='relu'),\n","    tf.keras.layers.MaxPooling2D(2,2),\n","    tf.keras.layers.Conv2D(128, (3,3), activation='relu'),\n","    tf.keras.layers.MaxPooling2D(2,2),\n","    tf.keras.layers.Conv2D(128, (3,3), activation='relu'),\n","    tf.keras.layers.MaxPooling2D(2,2),\n","    tf.keras.layers.Flatten(),\n","    tf.keras.layers.Dense(512, activation='relu'),\n","    tf.keras.layers.Dense(1, activation='sigmoid')\n","])\n","\n","from tensorflow.keras.optimizers import RMSprop\n","\n","modelDA.compile(loss='binary_crossentropy',\n","              optimizer=RMSprop(lr=1e-4),\n","              metrics=['acc'])\n","\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"elvc8kFYKj0Y","colab_type":"code","outputId":"8543bb86-ebdd-4f50-87e6-7f2e2b4f4d50","executionInfo":{"status":"ok","timestamp":1567503175410,"user_tz":-120,"elapsed":65430,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","\n","train_datagen = ImageDataGenerator(\n","      rescale=1./255,\n","      rotation_range=40,\n","      width_shift_range=0.2,\n","      height_shift_range=0.2,\n","      shear_range=0.2,\n","      zoom_range=0.2,\n","      horizontal_flip=True,\n","      fill_mode='nearest')\n","\n","validation_datagen  = ImageDataGenerator( rescale = 1.0/255. )\n","test_datagen  = ImageDataGenerator( rescale = 1.0/255. )\n","\n","\n","train_generator = train_datagen.flow_from_directory(train_dir,\n","                                                    batch_size=20,\n","                                                    class_mode='binary',\n","                                                    target_size=(150, 150))     \n","\n","validation_generator =  validation_datagen.flow_from_directory(validation_dir,\n","                                                         batch_size=20,\n","                                                         class_mode  = 'binary',\n","                                                         target_size = (150, 150))\n","\n","\n","test_generator =  test_datagen.flow_from_directory(validation_dir,\n","                                                         batch_size=20,\n","                                                         class_mode  = 'binary',\n","                                                         target_size = (150, 150))\n"],"execution_count":8,"outputs":[{"output_type":"stream","text":["Found 2000 images belonging to 2 classes.\n","Found 1000 images belonging to 2 classes.\n","Found 1000 images belonging to 2 classes.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"xU48fLeFKj3I","colab_type":"code","outputId":"88be7262-630e-4284-ad8f-38c7b9f046e0","executionInfo":{"status":"ok","timestamp":1567505110202,"user_tz":-120,"elapsed":2000210,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["batch_size = 20\n","steps_per_epoch = train_generator.n // batch_size\n","validation_steps = validation_generator.n // batch_size\n","\n","historyDA = modelDA.fit_generator(\n","      train_generator,\n","      steps_per_epoch= steps_per_epoch,\n","      epochs= 100,\n","      validation_data= validation_generator,\n","      validation_steps= validation_steps,\n","      verbose=2)"],"execution_count":9,"outputs":[{"output_type":"stream","text":["Epoch 1/100\n","100/100 - 24s - loss: 0.6946 - acc: 0.5060 - val_loss: 0.6840 - val_acc: 0.5420\n","Epoch 2/100\n","100/100 - 19s - loss: 0.6825 - acc: 0.5675 - val_loss: 0.6717 - val_acc: 0.5710\n","Epoch 3/100\n","100/100 - 19s - loss: 0.6662 - acc: 0.5920 - val_loss: 0.6413 - val_acc: 0.6020\n","Epoch 4/100\n","100/100 - 19s - loss: 0.6437 - acc: 0.6325 - val_loss: 0.6056 - val_acc: 0.6540\n","Epoch 5/100\n","100/100 - 19s - loss: 0.6285 - acc: 0.6310 - val_loss: 0.6064 - val_acc: 0.6550\n","Epoch 6/100\n","100/100 - 19s - loss: 0.6204 - acc: 0.6510 - val_loss: 0.5842 - val_acc: 0.6840\n","Epoch 7/100\n","100/100 - 19s - loss: 0.6084 - acc: 0.6625 - val_loss: 0.5678 - val_acc: 0.6930\n","Epoch 8/100\n","100/100 - 19s - loss: 0.5957 - acc: 0.6850 - val_loss: 0.5951 - val_acc: 0.6660\n","Epoch 9/100\n","100/100 - 19s - loss: 0.5927 - acc: 0.6910 - val_loss: 0.5866 - val_acc: 0.6770\n","Epoch 10/100\n","100/100 - 19s - loss: 0.5854 - acc: 0.6875 - val_loss: 0.6144 - val_acc: 0.6670\n","Epoch 11/100\n","100/100 - 20s - loss: 0.5673 - acc: 0.6980 - val_loss: 0.5463 - val_acc: 0.7160\n","Epoch 12/100\n","100/100 - 19s - loss: 0.5647 - acc: 0.7000 - val_loss: 0.5455 - val_acc: 0.7190\n","Epoch 13/100\n","100/100 - 19s - loss: 0.5682 - acc: 0.6980 - val_loss: 0.5439 - val_acc: 0.7150\n","Epoch 14/100\n","100/100 - 19s - loss: 0.5618 - acc: 0.7095 - val_loss: 0.5525 - val_acc: 0.7080\n","Epoch 15/100\n","100/100 - 19s - loss: 0.5615 - acc: 0.7075 - val_loss: 0.5143 - val_acc: 0.7320\n","Epoch 16/100\n","100/100 - 19s - loss: 0.5580 - acc: 0.7010 - val_loss: 0.5191 - val_acc: 0.7290\n","Epoch 17/100\n","100/100 - 19s - loss: 0.5505 - acc: 0.7145 - val_loss: 0.5220 - val_acc: 0.7320\n","Epoch 18/100\n","100/100 - 20s - loss: 0.5475 - acc: 0.7245 - val_loss: 0.5307 - val_acc: 0.7190\n","Epoch 19/100\n","100/100 - 19s - loss: 0.5370 - acc: 0.7230 - val_loss: 0.5615 - val_acc: 0.6870\n","Epoch 20/100\n","100/100 - 19s - loss: 0.5432 - acc: 0.7115 - val_loss: 0.5258 - val_acc: 0.7340\n","Epoch 21/100\n","100/100 - 19s - loss: 0.5321 - acc: 0.7220 - val_loss: 0.5983 - val_acc: 0.7020\n","Epoch 22/100\n","100/100 - 19s - loss: 0.5340 - acc: 0.7375 - val_loss: 0.5052 - val_acc: 0.7340\n","Epoch 23/100\n","100/100 - 20s - loss: 0.5198 - acc: 0.7425 - val_loss: 0.5832 - val_acc: 0.6850\n","Epoch 24/100\n","100/100 - 20s - loss: 0.5230 - acc: 0.7495 - val_loss: 0.5226 - val_acc: 0.7350\n","Epoch 25/100\n","100/100 - 19s - loss: 0.5218 - acc: 0.7380 - val_loss: 0.5299 - val_acc: 0.7220\n","Epoch 26/100\n","100/100 - 19s - loss: 0.5123 - acc: 0.7465 - val_loss: 0.4984 - val_acc: 0.7450\n","Epoch 27/100\n","100/100 - 19s - loss: 0.5062 - acc: 0.7525 - val_loss: 0.5092 - val_acc: 0.7430\n","Epoch 28/100\n","100/100 - 19s - loss: 0.5071 - acc: 0.7490 - val_loss: 0.4951 - val_acc: 0.7480\n","Epoch 29/100\n","100/100 - 19s - loss: 0.4976 - acc: 0.7495 - val_loss: 0.5277 - val_acc: 0.7350\n","Epoch 30/100\n","100/100 - 19s - loss: 0.4950 - acc: 0.7580 - val_loss: 0.5167 - val_acc: 0.7240\n","Epoch 31/100\n","100/100 - 19s - loss: 0.5026 - acc: 0.7595 - val_loss: 0.5595 - val_acc: 0.7200\n","Epoch 32/100\n","100/100 - 19s - loss: 0.4877 - acc: 0.7660 - val_loss: 0.4657 - val_acc: 0.7740\n","Epoch 33/100\n","100/100 - 19s - loss: 0.4887 - acc: 0.7565 - val_loss: 0.4968 - val_acc: 0.7570\n","Epoch 34/100\n","100/100 - 19s - loss: 0.4776 - acc: 0.7660 - val_loss: 0.5521 - val_acc: 0.7140\n","Epoch 35/100\n","100/100 - 19s - loss: 0.4888 - acc: 0.7490 - val_loss: 0.4579 - val_acc: 0.7840\n","Epoch 36/100\n","100/100 - 20s - loss: 0.4808 - acc: 0.7620 - val_loss: 0.5638 - val_acc: 0.7180\n","Epoch 37/100\n","100/100 - 19s - loss: 0.4805 - acc: 0.7685 - val_loss: 0.5062 - val_acc: 0.7410\n","Epoch 38/100\n","100/100 - 19s - loss: 0.4668 - acc: 0.7690 - val_loss: 0.5276 - val_acc: 0.7490\n","Epoch 39/100\n","100/100 - 19s - loss: 0.4768 - acc: 0.7575 - val_loss: 0.6237 - val_acc: 0.6990\n","Epoch 40/100\n","100/100 - 20s - loss: 0.4711 - acc: 0.7720 - val_loss: 0.4494 - val_acc: 0.7800\n","Epoch 41/100\n","100/100 - 20s - loss: 0.4560 - acc: 0.7845 - val_loss: 0.4862 - val_acc: 0.7680\n","Epoch 42/100\n","100/100 - 19s - loss: 0.4674 - acc: 0.7700 - val_loss: 0.4901 - val_acc: 0.7550\n","Epoch 43/100\n","100/100 - 19s - loss: 0.4654 - acc: 0.7865 - val_loss: 0.4593 - val_acc: 0.7830\n","Epoch 44/100\n","100/100 - 20s - loss: 0.4514 - acc: 0.7865 - val_loss: 0.5003 - val_acc: 0.7590\n","Epoch 45/100\n","100/100 - 19s - loss: 0.4517 - acc: 0.7940 - val_loss: 0.4924 - val_acc: 0.7660\n","Epoch 46/100\n","100/100 - 19s - loss: 0.4433 - acc: 0.7940 - val_loss: 0.5091 - val_acc: 0.7530\n","Epoch 47/100\n","100/100 - 20s - loss: 0.4597 - acc: 0.7770 - val_loss: 0.5295 - val_acc: 0.7310\n","Epoch 48/100\n","100/100 - 19s - loss: 0.4404 - acc: 0.7960 - val_loss: 0.4606 - val_acc: 0.7810\n","Epoch 49/100\n","100/100 - 19s - loss: 0.4464 - acc: 0.7840 - val_loss: 0.4788 - val_acc: 0.7750\n","Epoch 50/100\n","100/100 - 19s - loss: 0.4466 - acc: 0.7840 - val_loss: 0.4778 - val_acc: 0.7770\n","Epoch 51/100\n","100/100 - 19s - loss: 0.4319 - acc: 0.7980 - val_loss: 0.4673 - val_acc: 0.7890\n","Epoch 52/100\n","100/100 - 20s - loss: 0.4527 - acc: 0.7830 - val_loss: 0.4702 - val_acc: 0.7690\n","Epoch 53/100\n","100/100 - 19s - loss: 0.4344 - acc: 0.7980 - val_loss: 0.4737 - val_acc: 0.7830\n","Epoch 54/100\n","100/100 - 19s - loss: 0.4330 - acc: 0.8000 - val_loss: 0.4562 - val_acc: 0.7740\n","Epoch 55/100\n","100/100 - 20s - loss: 0.4235 - acc: 0.8030 - val_loss: 0.4847 - val_acc: 0.7880\n","Epoch 56/100\n","100/100 - 19s - loss: 0.4340 - acc: 0.8055 - val_loss: 0.5200 - val_acc: 0.7570\n","Epoch 57/100\n","100/100 - 19s - loss: 0.4224 - acc: 0.8105 - val_loss: 0.6278 - val_acc: 0.7160\n","Epoch 58/100\n","100/100 - 19s - loss: 0.4266 - acc: 0.8035 - val_loss: 0.4793 - val_acc: 0.7830\n","Epoch 59/100\n","100/100 - 19s - loss: 0.4238 - acc: 0.8050 - val_loss: 0.4831 - val_acc: 0.7720\n","Epoch 60/100\n","100/100 - 20s - loss: 0.4314 - acc: 0.8055 - val_loss: 0.4864 - val_acc: 0.7550\n","Epoch 61/100\n","100/100 - 19s - loss: 0.4104 - acc: 0.8185 - val_loss: 0.4626 - val_acc: 0.7720\n","Epoch 62/100\n","100/100 - 19s - loss: 0.4262 - acc: 0.8025 - val_loss: 0.4305 - val_acc: 0.7940\n","Epoch 63/100\n","100/100 - 19s - loss: 0.4108 - acc: 0.8140 - val_loss: 0.5177 - val_acc: 0.7530\n","Epoch 64/100\n","100/100 - 19s - loss: 0.4094 - acc: 0.8160 - val_loss: 0.4277 - val_acc: 0.8020\n","Epoch 65/100\n","100/100 - 19s - loss: 0.4036 - acc: 0.8180 - val_loss: 0.4801 - val_acc: 0.7770\n","Epoch 66/100\n","100/100 - 19s - loss: 0.4019 - acc: 0.8160 - val_loss: 0.4701 - val_acc: 0.7770\n","Epoch 67/100\n","100/100 - 19s - loss: 0.4174 - acc: 0.8030 - val_loss: 0.4470 - val_acc: 0.7990\n","Epoch 68/100\n","100/100 - 19s - loss: 0.3964 - acc: 0.8075 - val_loss: 0.4698 - val_acc: 0.7800\n","Epoch 69/100\n","100/100 - 19s - loss: 0.4002 - acc: 0.8190 - val_loss: 0.4385 - val_acc: 0.8010\n","Epoch 70/100\n","100/100 - 19s - loss: 0.3928 - acc: 0.8250 - val_loss: 0.5078 - val_acc: 0.7640\n","Epoch 71/100\n","100/100 - 19s - loss: 0.3970 - acc: 0.8255 - val_loss: 0.4468 - val_acc: 0.7910\n","Epoch 72/100\n","100/100 - 19s - loss: 0.3849 - acc: 0.8185 - val_loss: 0.5338 - val_acc: 0.7570\n","Epoch 73/100\n","100/100 - 19s - loss: 0.3961 - acc: 0.8240 - val_loss: 0.4197 - val_acc: 0.8140\n","Epoch 74/100\n","100/100 - 20s - loss: 0.3978 - acc: 0.8155 - val_loss: 0.4751 - val_acc: 0.7740\n","Epoch 75/100\n","100/100 - 19s - loss: 0.3768 - acc: 0.8265 - val_loss: 0.4283 - val_acc: 0.8050\n","Epoch 76/100\n","100/100 - 19s - loss: 0.3856 - acc: 0.8250 - val_loss: 0.4257 - val_acc: 0.8080\n","Epoch 77/100\n","100/100 - 19s - loss: 0.3862 - acc: 0.8335 - val_loss: 0.4434 - val_acc: 0.8140\n","Epoch 78/100\n","100/100 - 19s - loss: 0.3980 - acc: 0.8230 - val_loss: 0.5363 - val_acc: 0.7570\n","Epoch 79/100\n","100/100 - 19s - loss: 0.3776 - acc: 0.8315 - val_loss: 0.4552 - val_acc: 0.7930\n","Epoch 80/100\n","100/100 - 19s - loss: 0.3818 - acc: 0.8260 - val_loss: 0.4301 - val_acc: 0.8030\n","Epoch 81/100\n","100/100 - 19s - loss: 0.3854 - acc: 0.8195 - val_loss: 0.4192 - val_acc: 0.8080\n","Epoch 82/100\n","100/100 - 20s - loss: 0.3838 - acc: 0.8230 - val_loss: 0.5044 - val_acc: 0.7760\n","Epoch 83/100\n","100/100 - 19s - loss: 0.3678 - acc: 0.8460 - val_loss: 0.4191 - val_acc: 0.8060\n","Epoch 84/100\n","100/100 - 19s - loss: 0.3635 - acc: 0.8450 - val_loss: 0.4190 - val_acc: 0.8120\n","Epoch 85/100\n","100/100 - 19s - loss: 0.3623 - acc: 0.8370 - val_loss: 0.5004 - val_acc: 0.7930\n","Epoch 86/100\n","100/100 - 19s - loss: 0.3808 - acc: 0.8340 - val_loss: 0.4212 - val_acc: 0.8260\n","Epoch 87/100\n","100/100 - 19s - loss: 0.3636 - acc: 0.8260 - val_loss: 0.5051 - val_acc: 0.7820\n","Epoch 88/100\n","100/100 - 19s - loss: 0.3589 - acc: 0.8435 - val_loss: 0.4865 - val_acc: 0.7860\n","Epoch 89/100\n","100/100 - 19s - loss: 0.3647 - acc: 0.8215 - val_loss: 0.4233 - val_acc: 0.8160\n","Epoch 90/100\n","100/100 - 19s - loss: 0.3609 - acc: 0.8250 - val_loss: 0.4574 - val_acc: 0.8040\n","Epoch 91/100\n","100/100 - 20s - loss: 0.3607 - acc: 0.8390 - val_loss: 0.4741 - val_acc: 0.8030\n","Epoch 92/100\n","100/100 - 20s - loss: 0.3653 - acc: 0.8355 - val_loss: 0.4142 - val_acc: 0.8230\n","Epoch 93/100\n","100/100 - 19s - loss: 0.3563 - acc: 0.8355 - val_loss: 0.4609 - val_acc: 0.8050\n","Epoch 94/100\n","100/100 - 19s - loss: 0.3602 - acc: 0.8410 - val_loss: 0.4167 - val_acc: 0.8330\n","Epoch 95/100\n","100/100 - 19s - loss: 0.3568 - acc: 0.8460 - val_loss: 0.4287 - val_acc: 0.8020\n","Epoch 96/100\n","100/100 - 19s - loss: 0.3398 - acc: 0.8520 - val_loss: 0.4351 - val_acc: 0.8260\n","Epoch 97/100\n","100/100 - 19s - loss: 0.3497 - acc: 0.8425 - val_loss: 0.5159 - val_acc: 0.7580\n","Epoch 98/100\n","100/100 - 19s - loss: 0.3404 - acc: 0.8480 - val_loss: 0.4515 - val_acc: 0.8130\n","Epoch 99/100\n","100/100 - 19s - loss: 0.3522 - acc: 0.8505 - val_loss: 0.4090 - val_acc: 0.8270\n","Epoch 100/100\n","100/100 - 19s - loss: 0.3228 - acc: 0.8545 - val_loss: 0.4401 - val_acc: 0.8210\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"zkmHqrzCKj8g","colab_type":"code","outputId":"b46bfd8b-ff9e-45ba-b867-e49019bf4523","executionInfo":{"status":"ok","timestamp":1567505113442,"user_tz":-120,"elapsed":2003440,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["print (steps_per_epoch)\n","print (validation_steps)\n","test_lost, test_acc= modelDA.evaluate_generator(test_generator)\n","print (\"Test Accuracy:\", test_acc)"],"execution_count":10,"outputs":[{"output_type":"stream","text":["100\n","50\n","Test Accuracy: 0.821\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"GP2sz8eoKj_T","colab_type":"code","outputId":"191edc68-e730-4575-cb0b-e636a0cd3f20","executionInfo":{"status":"ok","timestamp":1567505114037,"user_tz":-120,"elapsed":2004028,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":641}},"source":["%matplotlib inline\n","\n","import matplotlib.pyplot as plt\n","\n","\n","acc      = historyDA.history[     'acc' ]\n","val_acc  = historyDA.history[ 'val_acc' ]\n","loss     = historyDA.history[    'loss' ]\n","val_loss = historyDA.history['val_loss' ]\n","\n","epochs    = range(1,len(acc)+1,1) # obtener número de epochs\n","\n","plt.plot  ( epochs,     acc, 'r--', label='Training acc'  )\n","plt.plot  ( epochs, val_acc,  'b', label='Validation acc')\n","plt.title ('Training and validation accuracy')\n","plt.ylabel('acc')\n","plt.xlabel('epochs')\n","\n","plt.legend()\n","plt.figure()\n","\n","\n","plt.plot  ( epochs,     loss, 'r--' )\n","plt.plot  ( epochs, val_loss ,  'b' )\n","plt.title ('Training and validation loss'   )\n","plt.ylabel('loss')\n","plt.xlabel('epochs')\n","\n","plt.legend()\n","plt.figure()\n","\n"],"execution_count":11,"outputs":[{"output_type":"stream","text":["WARNING: Logging before flag parsing goes to stderr.\n","W0903 10:05:13.133433 140067097810816 legend.py:1289] No handles with labels found to put in legend.\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]},"execution_count":11},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYsAAAEWCAYAAACXGLsWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzsnXd4lFXWwH8nofcWpEpXCCWUiAUF\nRVDsig3UVWyoKy5rWfsqsmtbe0FX1i4qIqKLK6goiij6SQ1VektoofcScr4/zryZdyYzyQCZTID7\ne555Zt5+ZwL33NNFVXE4HA6HoyCSEj0Ah8PhcJR8nLBwOBwOR6E4YeFwOByOQnHCwuFwOByF4oSF\nw+FwOArFCQuHw+FwFIoTFo6YEZFkEdkuIscW5bmJRESai0iRx4+LSA8RWebbni8ip8Vy7kE8600R\nefBgr3c4YqFUogfgiB8ist23WQHYA+wPbN+iqh8eyP1UdT9QqajPPRpQ1eOL4j4ichNwjaqe7rv3\nTUVxb4ejIJywOIJR1bzJOrByvUlVv4t2voiUUtWc4hibw1EY7t9jycKZoY5iROSfIvKJiHwsItuA\na0TkZBH5TUQ2i8hqEXlZREoHzi8lIioijQPbwwLHx4rINhH5VUSaHOi5gePniMgCEdkiIq+IyC8i\n0i/KuGMZ4y0iskhENonIy75rk0XkBRHZICJLgF4F/D4PicjwsH1DROT5wOebRGRe4PssDqz6o90r\nU0ROD3yuICIfBMY2B+gUdu7DIrIkcN85InJhYH9b4FXgtICJb73vtx3ku/7WwHffICJfiEjdWH6b\nA/mdvfGIyHcislFE1ojIvb7n/D3wm2wVkSkiUi+SyU9Efvb+zoHf86fAczYCD4tICxH5IfCM9YHf\nrarv+kaB75gdOP6SiJQLjLmV77y6IrJTRGpG+76OQlBV9zoKXsAyoEfYvn8Ce4ELsIVDeeAE4ERM\n62wKLAAGBM4vBSjQOLA9DFgPpAOlgU+AYQdxbm1gG3BR4NhdwD6gX5TvEssY/wtUBRoDG73vDgwA\n5gANgJrAT/bfIOJzmgLbgYq+e68D0gPbFwTOEaA7sAtoFzjWA1jmu1cmcHrg87PAj0B1oBEwN+zc\nK4C6gb/JVYExHBM4dhPwY9g4hwGDAp/PCoyxPVAOeA0YH8tvc4C/c1VgLTAQKAtUAToHjj0AZAAt\nAt+hPVADaB7+WwM/e3/nwHfLAW4DkrF/j8cBZwJlAv9OfgGe9X2f2YHfs2Lg/C6BY0OBx33PuRv4\nPNH/Dw/nV8IH4F7F9IeOLizGF3LdPcCngc+RBMC/fedeCMw+iHNvACb6jgmwmijCIsYxnuQ7Pgq4\nJ/D5J8wc5x07N3wCC7v3b8BVgc/nAPMLOPd/wO2BzwUJixX+vwXwZ/+5Ee47Gzgv8LkwYfEe8ITv\nWBXMT9WgsN/mAH/nPwGTo5y32Btv2P5YhMWSQsZwmfdc4DRgDZAc4bwuwFJAAtszgN5F/f/qaHo5\nM5RjpX9DRFqKyFcBs8JWYDBQq4Dr1/g+76Rgp3a0c+v5x6H2vzsz2k1iHGNMzwKWFzBegI+AvoHP\nVwW2vXGcLyL/FzCRbMZW9QX9Vh51CxqDiPQTkYyAKWUz0DLG+4J9v7z7qepWYBNQ33dOTH+zQn7n\nhphQiERBxwoj/N9jHREZISJZgTG8GzaGZWrBFCGo6i+YlnKqiLQBjgW+OsgxOXA+C4etNP28ga1k\nm6tqFeARbKUfT1ZjK18AREQIndzCOZQxrsYmGY/CQntHAD1EpD5mJvsoMMbywEjgScxEVA34NsZx\nrIk2BhFpCryOmWJqBu77h+++hYX5rsJMW979KmPmrqwYxhVOQb/zSqBZlOuiHdsRGFMF3746YeeE\nf7+nsSi+toEx9AsbQyMRSY4yjveBazAtaISq7olyniMGnLBwhFMZ2ALsCDgIbymGZ/4P6CgiF4hI\nKcwOnhKnMY4A/ioi9QPOzvsKOllV12CmkncxE9TCwKGymB09G9gvIudjtvVYx/CgiFQTy0MZ4DtW\nCZswszG5eTOmWXisBRr4Hc1hfAzcKCLtRKQsJswmqmpUTa0ACvqdRwPHisgAESkrIlVEpHPg2JvA\nP0WkmRjtRaQGJiTXYIEUySLSH59gK2AMO4AtItIQM4V5/ApsAJ4QCxooLyJdfMc/wMxWV2GCw3EI\nOGHhCOdu4DrM4fwG5oiOK6q6FrgSeB77z98MmI6tKIt6jK8D3wOzgMmYdlAYH2E+iDwTlKpuBu4E\nPsecxJdhQi8WHsU0nGXAWHwTmarOBF4Bfg+cczzwf75rxwELgbUi4jcnedd/jZmLPg9cfyxwdYzj\nCifq76yqW4CewKWYAFsAdAscfgb4Avudt2LO5nIB8+LNwINYsEPzsO8WiUeBzpjQGg185htDDnA+\n0ArTMlZgfwfv+DLs77xHVScd4Hd3hOE5fxyOEkPArLAKuExVJyZ6PI7DFxF5H3OaD0r0WA53XFKe\no0QgIr2wyKNdWOjlPmx17XAcFAH/z0VA20SP5UjAmaEcJYVTgSWYrf5s4BLnkHQcLCLyJJbr8YSq\nrkj0eI4EnBnK4XA4HIXiNAuHw+FwFMoR47OoVauWNm7cONHDcDgcjsOKqVOnrlfVgkLVgSNIWDRu\n3JgpU6YkehgOh8NxWCEihVUxAJwZyuFwOBwx4ISFw+FwOArFCQuHw+FwFMoR47OIxL59+8jMzGT3\n7t2JHoqjAMqVK0eDBg0oXTpauSOHw5FojmhhkZmZSeXKlWncuDFWyNRR0lBVNmzYQGZmJk2aNCn8\nAofDkRCOaDPU7t27qVmzphMUJRgRoWbNmk77czhKOEe0sACcoDgMcH8jh6Pkc8QLC4fD4TiiWXyw\nTQkPjLgKCxHpJSLzRWSRiNwf4fixIvKDiEwXkZkicm5gf2MR2SUiMwKvf8dznPFiw4YNtG/fnvbt\n21OnTh3q16+ft713796Y7nH99dczf/78As8ZMmQIH374YVEM2eFwJJqcnNjO27MH/vpXOP54+D3+\nBZrj5uAO9CQYgjVIyQQmi8hoVZ3rO+1hrN3h6yKSCowBGgeOLVbV9vEaX3FQs2ZNZsyYAcCgQYOo\nVKkS99xzT8g5ec3QkyLL7XfeeafQ59x+++2HPliHw5F4Zs2CM86Ae+6B+/Otr0N59ll46SX4y18g\nLS3uQ4unZtEZWKSqS1R1LzAcqy3vR4Eqgc9VsYY3RzyLFi0iNTWVq6++mtatW7N69Wr69+9Peno6\nrVu3ZvDgwXnnnnrqqcyYMYOcnByqVavG/fffT1paGieffDLr1q0D4OGHH+bFF1/MO//++++nc+fO\nHH/88UyaZA3CduzYwaWXXkpqaiqXXXYZ6enpeYLMz6OPPsoJJ5xAmzZtuPXWW/GqEi9YsIDu3buT\nlpZGx44dWbZsGQBPPPEEbdu2JS0tjYceeiieP5vDceTTqBFs2AAPPAArIlRWnzEDJgb6gd15J3z9\ntQmMsmXjPrR4Cov6WKtDj8zAPj+DsH68mZhWcYfvWJOAeWqCiJwW6QEi0l9EpojIlOzs7MJHdPrp\n+V+vvWbHdu6MfPzdd+34+vX5jx0Cf/zxB3feeSdz586lfv36PPXUU0yZMoWMjAzGjRvH3Llz812z\nZcsWunXrRkZGBieffDJvv/12xHurKr///jvPPPNMnuB55ZVXqFOnDnPnzuXvf/8706dPj3jtwIED\nmTx5MrNmzWLLli18/fXXAPTt25c777yTjIwMJk2aRO3atfnyyy8ZO3Ysv//+OxkZGdx9992H9Js4\nHEct69fbHFSlCixbBuXKhWoWu3fDFVdAhw5wX6BtfIUKcPbZxTbERDu4+wLvqmoD4FzgAxFJItA7\nWFU7AHcBH4lIlfCLVXWoqqaranpKSqFFE0sUzZo1Iz09PW/7448/pmPHjnTs2JF58+ZFFBbly5fn\nnHPOAaBTp055q/twevfune+cn3/+mT59+gCQlpZG69atI177/fff07lzZ9LS0pgwYQJz5sxh06ZN\nrF+/ngsuuACwJLoKFSrw3XffccMNN1C+fHkAatSoceA/hMORCF59Fd5+G6ZNg9zcxI5l40bo1Qsu\nuABUTbu45x74+GOYNMl8E717w6efwqOPwpgxCRlmPJPysoCGvu0GgX1+bgR6AajqryJSDqilquuA\nPYH9U0VkMXAccGhlZX/8MfqxChUKPl6rVsHHD5CKFSvmfV64cCEvvfQSv//+O9WqVeOaa66JmHdQ\npkyZvM/JycnkRHGElQ2opAWdE4mdO3cyYMAApk2bRv369Xn44Ydd/oPjyOSZZ4JmnmuugQ8+iO26\nrVvt1aBB0Yxj1SrTDhYsgFGjwAsjv+8++PZbM0ldfjmMHQtDh8LNNxfNcw+CeGoWk4EWItJERMoA\nfYDRYeesAM4EEJFWQDkgW0RSAg5yr49uC6zl5hHJ1q1bqVy5MlWqVGH16tV88803Rf6MLl26MGLE\nCABmzZoVUXPZtWsXSUlJ1KpVi23btvHZZ58BUL16dVJSUvjyyy8BS3bcuXMnPXv25O2332bXrl0A\nbNy4scjH7XAUKdu3myaxZAnMn292/2HDIPB/o1C6doWGDU0DOFQWLYIuXczsNGYMnHde8FilSvDb\nb3DuuVCtGrz+ekIFBcRRWKhqDjAA+AaYh0U9zRGRwSJyYeC0u4GbRSQD+Bjop+ZR7QrMFJEZwEjg\nVlU9Ymeijh07kpqaSsuWLbn22mvp0qVLkT/jjjvuICsri9TUVB577DFSU1O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DRtan+LrCz7bk5YOIoTJyyOIv7yl/wtIPj1V15Y0ZvjJg8jJMQAc1gPHWrluQFITubnn62P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\nidguEOkGVAW+V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iwPiayLMIiEN7HT5heLGKFzC+p6mlIloUXSnNDGfki3wFuIw26dtXJIV3LYtkyDWQP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\nEl17EisWXbpEusIm8ulv3qzZ0b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K1Gv7+90hxgGfCBC1MOO889X2ccIKm4W7dmv1ItREX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\nt49dzwAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"ccc5u4fembNS"},"source":["### ModelFE: Modelo con *Feature Extraction*"]},{"cell_type":"code","metadata":{"id":"V2uilIo5hY4y","colab_type":"code","outputId":"63ae9cac-b9e5-464e-ad14-9827bcd887bd","executionInfo":{"status":"ok","timestamp":1567505115820,"user_tz":-120,"elapsed":2005805,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["import tensorflow as tf\n","\n","from tensorflow.keras.applications import VGG16\n","\n","pre_trained_model = VGG16(input_shape = (150, 150, 3), \n","                                include_top = False, \n","                                weights = 'imagenet')\n","\n","\n","pre_trained_model.summary()\n","\n","for layer in pre_trained_model.layers:\n","  layer.trainable = False\n","\n","\n","pre_trained_model.summary()\n","\n","\n"],"execution_count":12,"outputs":[{"output_type":"stream","text":["Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n","58892288/58889256 [==============================] - 1s 0us/step\n","Model: \"vgg16\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","input_1 (InputLayer)         [(None, 150, 150, 3)]     0         \n","_________________________________________________________________\n","block1_conv1 (Conv2D)        (None, 150, 150, 64)      1792      \n","_________________________________________________________________\n","block1_conv2 (Conv2D)        (None, 150, 150, 64)      36928     \n","_________________________________________________________________\n","block1_pool (MaxPooling2D)   (None, 75, 75, 64)        0         \n","_________________________________________________________________\n","block2_conv1 (Conv2D)        (None, 75, 75, 128)       73856     \n","_________________________________________________________________\n","block2_conv2 (Conv2D)        (None, 75, 75, 128)       147584    \n","_________________________________________________________________\n","block2_pool (MaxPooling2D)   (None, 37, 37, 128)       0         \n","_________________________________________________________________\n","block3_conv1 (Conv2D)        (None, 37, 37, 256)       295168    \n","_________________________________________________________________\n","block3_conv2 (Conv2D)        (None, 37, 37, 256)       590080    \n","_________________________________________________________________\n","block3_conv3 (Conv2D)        (None, 37, 37, 256)       590080    \n","_________________________________________________________________\n","block3_pool (MaxPooling2D)   (None, 18, 18, 256)       0         \n","_________________________________________________________________\n","block4_conv1 (Conv2D)        (None, 18, 18, 512)       1180160   \n","_________________________________________________________________\n","block4_conv2 (Conv2D)        (None, 18, 18, 512)       2359808   \n","_________________________________________________________________\n","block4_conv3 (Conv2D)        (None, 18, 18, 512)       2359808   \n","_________________________________________________________________\n","block4_pool (MaxPooling2D)   (None, 9, 9, 512)         0         \n","_________________________________________________________________\n","block5_conv1 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_conv2 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_conv3 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_pool (MaxPooling2D)   (None, 4, 4, 512)         0         \n","=================================================================\n","Total params: 14,714,688\n","Trainable params: 14,714,688\n","Non-trainable params: 0\n","_________________________________________________________________\n","Model: \"vgg16\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","input_1 (InputLayer)         [(None, 150, 150, 3)]     0         \n","_________________________________________________________________\n","block1_conv1 (Conv2D)        (None, 150, 150, 64)      1792      \n","_________________________________________________________________\n","block1_conv2 (Conv2D)        (None, 150, 150, 64)      36928     \n","_________________________________________________________________\n","block1_pool (MaxPooling2D)   (None, 75, 75, 64)        0         \n","_________________________________________________________________\n","block2_conv1 (Conv2D)        (None, 75, 75, 128)       73856     \n","_________________________________________________________________\n","block2_conv2 (Conv2D)        (None, 75, 75, 128)       147584    \n","_________________________________________________________________\n","block2_pool (MaxPooling2D)   (None, 37, 37, 128)       0         \n","_________________________________________________________________\n","block3_conv1 (Conv2D)        (None, 37, 37, 256)       295168    \n","_________________________________________________________________\n","block3_conv2 (Conv2D)        (None, 37, 37, 256)       590080    \n","_________________________________________________________________\n","block3_conv3 (Conv2D)        (None, 37, 37, 256)       590080    \n","_________________________________________________________________\n","block3_pool (MaxPooling2D)   (None, 18, 18, 256)       0         \n","_________________________________________________________________\n","block4_conv1 (Conv2D)        (None, 18, 18, 512)       1180160   \n","_________________________________________________________________\n","block4_conv2 (Conv2D)        (None, 18, 18, 512)       2359808   \n","_________________________________________________________________\n","block4_conv3 (Conv2D)        (None, 18, 18, 512)       2359808   \n","_________________________________________________________________\n","block4_pool (MaxPooling2D)   (None, 9, 9, 512)         0         \n","_________________________________________________________________\n","block5_conv1 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_conv2 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_conv3 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_pool (MaxPooling2D)   (None, 4, 4, 512)         0         \n","=================================================================\n","Total params: 14,714,688\n","Trainable params: 0\n","Non-trainable params: 14,714,688\n","_________________________________________________________________\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"LSbSk4CKd4ev","colab_type":"code","colab":{}},"source":["modelFE = tf.keras.models.Sequential([\n","    pre_trained_model,\n","    tf.keras.layers.Flatten(),\n","    tf.keras.layers.Dense(256, activation='relu'),\n","    tf.keras.layers.Dense(1, activation='sigmoid')\n","])\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"p1KRETLXuHpZ","colab_type":"code","outputId":"d0d4030d-b41e-4565-c914-84f26da0359c","executionInfo":{"status":"ok","timestamp":1567505115992,"user_tz":-120,"elapsed":2005965,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":289}},"source":["modelFE.summary()"],"execution_count":14,"outputs":[{"output_type":"stream","text":["Model: \"sequential_1\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","vgg16 (Model)                (None, 4, 4, 512)         14714688  \n","_________________________________________________________________\n","flatten_1 (Flatten)          (None, 8192)              0         \n","_________________________________________________________________\n","dense_2 (Dense)              (None, 256)               2097408   \n","_________________________________________________________________\n","dense_3 (Dense)              (None, 1)                 257       \n","=================================================================\n","Total params: 16,812,353\n","Trainable params: 2,097,665\n","Non-trainable params: 14,714,688\n","_________________________________________________________________\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"InQuF32GiBRP","colab_type":"code","outputId":"d2233af1-dce2-4aad-d6fc-35913b64d0ed","executionInfo":{"status":"ok","timestamp":1567505116392,"user_tz":-120,"elapsed":2006358,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["\n","from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","\n","train_datagen = ImageDataGenerator(\n","      rescale=1./255,\n","      rotation_range=40,\n","      width_shift_range=0.2,\n","      height_shift_range=0.2,\n","      shear_range=0.2,\n","      zoom_range=0.2,\n","      horizontal_flip=True,\n","      fill_mode='nearest')\n","\n","validation_datagen  = ImageDataGenerator( rescale = 1.0/255. )\n","test_datagen  = ImageDataGenerator( rescale = 1.0/255. )\n","\n","\n","train_generator = train_datagen.flow_from_directory(train_dir,\n","                                                    batch_size=20,\n","                                                    class_mode='binary',\n","                                                    target_size=(150, 150))     \n","\n","validation_generator =  validation_datagen.flow_from_directory(validation_dir,\n","                                                         batch_size=20,\n","                                                         class_mode  = 'binary',\n","                                                         target_size = (150, 150))\n","\n","test_generator =  test_datagen.flow_from_directory(validation_dir,\n","                                                         batch_size=20,\n","                                                         class_mode  = 'binary',\n","                                                         target_size = (150, 150))\n","\n","\n","\n"],"execution_count":15,"outputs":[{"output_type":"stream","text":["Found 2000 images belonging to 2 classes.\n","Found 1000 images belonging to 2 classes.\n","Found 1000 images belonging to 2 classes.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"DCSzluJsiBXA","colab_type":"code","outputId":"14f15ea0-75f1-44a1-e775-bfcd6bcfec86","executionInfo":{"status":"ok","timestamp":1567507634600,"user_tz":-120,"elapsed":4524560,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["from tensorflow.keras.optimizers import RMSprop\n","\n","modelFE.compile(loss='binary_crossentropy',\n","              optimizer=RMSprop(lr=1e-4),\n","              metrics=['acc'])\n","\n","batch_size = 20\n","steps_per_epoch = train_generator.n // batch_size\n","validation_steps = validation_generator.n // batch_size\n","\n","historyFE = modelFE.fit_generator(\n","            train_generator,\n","            validation_data = validation_generator,\n","            steps_per_epoch = steps_per_epoch,\n","            epochs = 100,\n","            validation_steps = validation_steps,\n","            verbose = 2)\n","\n"],"execution_count":16,"outputs":[{"output_type":"stream","text":["Epoch 1/100\n","100/100 - 28s - loss: 0.5403 - acc: 0.7215 - val_loss: 0.3155 - val_acc: 0.8770\n","Epoch 2/100\n","100/100 - 25s - loss: 0.4322 - acc: 0.8015 - val_loss: 0.2698 - val_acc: 0.8940\n","Epoch 3/100\n","100/100 - 25s - loss: 0.3738 - acc: 0.8350 - val_loss: 0.2601 - val_acc: 0.8900\n","Epoch 4/100\n","100/100 - 25s - loss: 0.3596 - acc: 0.8415 - val_loss: 0.2557 - val_acc: 0.8910\n","Epoch 5/100\n","100/100 - 25s - loss: 0.3423 - acc: 0.8435 - val_loss: 0.2517 - val_acc: 0.8990\n","Epoch 6/100\n","100/100 - 25s - loss: 0.3359 - acc: 0.8555 - val_loss: 0.2396 - val_acc: 0.9070\n","Epoch 7/100\n","100/100 - 25s - loss: 0.3333 - acc: 0.8545 - val_loss: 0.2650 - val_acc: 0.8930\n","Epoch 8/100\n","100/100 - 25s - loss: 0.3344 - acc: 0.8475 - val_loss: 0.2468 - val_acc: 0.9020\n","Epoch 9/100\n","100/100 - 25s - loss: 0.3141 - acc: 0.8615 - val_loss: 0.2988 - val_acc: 0.8740\n","Epoch 10/100\n","100/100 - 25s - loss: 0.3184 - acc: 0.8585 - val_loss: 0.2455 - val_acc: 0.9020\n","Epoch 11/100\n","100/100 - 25s - loss: 0.3215 - acc: 0.8575 - val_loss: 0.2487 - val_acc: 0.8960\n","Epoch 12/100\n","100/100 - 25s - loss: 0.3097 - acc: 0.8580 - val_loss: 0.2475 - val_acc: 0.8960\n","Epoch 13/100\n","100/100 - 25s - loss: 0.3138 - acc: 0.8600 - val_loss: 0.2368 - val_acc: 0.9090\n","Epoch 14/100\n","100/100 - 25s - loss: 0.2854 - acc: 0.8735 - val_loss: 0.2384 - val_acc: 0.9110\n","Epoch 15/100\n","100/100 - 25s - loss: 0.2890 - acc: 0.8700 - val_loss: 0.2510 - val_acc: 0.9000\n","Epoch 16/100\n","100/100 - 25s - loss: 0.2977 - acc: 0.8725 - val_loss: 0.2759 - val_acc: 0.8890\n","Epoch 17/100\n","100/100 - 25s - loss: 0.3102 - acc: 0.8620 - val_loss: 0.2461 - val_acc: 0.9040\n","Epoch 18/100\n","100/100 - 25s - loss: 0.2783 - acc: 0.8780 - val_loss: 0.2417 - val_acc: 0.9050\n","Epoch 19/100\n","100/100 - 25s - loss: 0.2762 - acc: 0.8795 - val_loss: 0.2614 - val_acc: 0.9010\n","Epoch 20/100\n","100/100 - 25s - loss: 0.2779 - acc: 0.8795 - val_loss: 0.2774 - val_acc: 0.8950\n","Epoch 21/100\n","100/100 - 25s - loss: 0.2664 - acc: 0.8800 - val_loss: 0.2575 - val_acc: 0.8920\n","Epoch 22/100\n","100/100 - 25s - loss: 0.2687 - acc: 0.8940 - val_loss: 0.2972 - val_acc: 0.8860\n","Epoch 23/100\n","100/100 - 25s - loss: 0.2722 - acc: 0.8835 - val_loss: 0.2604 - val_acc: 0.8970\n","Epoch 24/100\n","100/100 - 25s - loss: 0.2622 - acc: 0.8895 - val_loss: 0.2477 - val_acc: 0.9080\n","Epoch 25/100\n","100/100 - 25s - loss: 0.2504 - acc: 0.8880 - val_loss: 0.2452 - val_acc: 0.9030\n","Epoch 26/100\n","100/100 - 25s - loss: 0.2753 - acc: 0.8850 - val_loss: 0.2805 - val_acc: 0.8820\n","Epoch 27/100\n","100/100 - 25s - loss: 0.2547 - acc: 0.8915 - val_loss: 0.2420 - val_acc: 0.9010\n","Epoch 28/100\n","100/100 - 25s - loss: 0.2572 - acc: 0.8885 - val_loss: 0.2453 - val_acc: 0.9050\n","Epoch 29/100\n","100/100 - 25s - loss: 0.2600 - acc: 0.8885 - val_loss: 0.2593 - val_acc: 0.9050\n","Epoch 30/100\n","100/100 - 25s - loss: 0.2549 - acc: 0.8910 - val_loss: 0.2496 - val_acc: 0.9040\n","Epoch 31/100\n","100/100 - 25s - loss: 0.2415 - acc: 0.8920 - val_loss: 0.2579 - val_acc: 0.9090\n","Epoch 32/100\n","100/100 - 25s - loss: 0.2492 - acc: 0.8925 - val_loss: 0.2563 - val_acc: 0.9080\n","Epoch 33/100\n","100/100 - 25s - loss: 0.2499 - acc: 0.8930 - val_loss: 0.2420 - val_acc: 0.9100\n","Epoch 34/100\n","100/100 - 25s - loss: 0.2501 - acc: 0.8935 - val_loss: 0.2372 - val_acc: 0.9070\n","Epoch 35/100\n","100/100 - 25s - loss: 0.2607 - acc: 0.8900 - val_loss: 0.2459 - val_acc: 0.9060\n","Epoch 36/100\n","100/100 - 25s - loss: 0.2341 - acc: 0.8995 - val_loss: 0.2483 - val_acc: 0.9070\n","Epoch 37/100\n","100/100 - 25s - loss: 0.2444 - acc: 0.9010 - val_loss: 0.2895 - val_acc: 0.8920\n","Epoch 38/100\n","100/100 - 25s - loss: 0.2263 - acc: 0.9035 - val_loss: 0.2524 - val_acc: 0.9050\n","Epoch 39/100\n","100/100 - 25s - loss: 0.2264 - acc: 0.9035 - val_loss: 0.2682 - val_acc: 0.9090\n","Epoch 40/100\n","100/100 - 25s - loss: 0.2318 - acc: 0.8955 - val_loss: 0.2630 - val_acc: 0.9060\n","Epoch 41/100\n","100/100 - 25s - loss: 0.2382 - acc: 0.8895 - val_loss: 0.2656 - val_acc: 0.9050\n","Epoch 42/100\n","100/100 - 25s - loss: 0.2381 - acc: 0.9055 - val_loss: 0.2752 - val_acc: 0.9050\n","Epoch 43/100\n","100/100 - 25s - loss: 0.2331 - acc: 0.9010 - val_loss: 0.2856 - val_acc: 0.8980\n","Epoch 44/100\n","100/100 - 25s - loss: 0.2315 - acc: 0.9040 - val_loss: 0.2658 - val_acc: 0.9060\n","Epoch 45/100\n","100/100 - 25s - loss: 0.2242 - acc: 0.9040 - val_loss: 0.2561 - val_acc: 0.9140\n","Epoch 46/100\n","100/100 - 25s - loss: 0.2309 - acc: 0.8995 - val_loss: 0.2562 - val_acc: 0.9060\n","Epoch 47/100\n","100/100 - 25s - loss: 0.2388 - acc: 0.8965 - val_loss: 0.2615 - val_acc: 0.9040\n","Epoch 48/100\n","100/100 - 25s - loss: 0.2072 - acc: 0.9130 - val_loss: 0.2863 - val_acc: 0.8960\n","Epoch 49/100\n","100/100 - 25s - loss: 0.2302 - acc: 0.9050 - val_loss: 0.2482 - val_acc: 0.9080\n","Epoch 50/100\n","100/100 - 25s - loss: 0.2221 - acc: 0.9085 - val_loss: 0.3958 - val_acc: 0.8580\n","Epoch 51/100\n","100/100 - 25s - loss: 0.2251 - acc: 0.9095 - val_loss: 0.2538 - val_acc: 0.9050\n","Epoch 52/100\n","100/100 - 25s - loss: 0.2279 - acc: 0.9000 - val_loss: 0.2884 - val_acc: 0.8980\n","Epoch 53/100\n","100/100 - 25s - loss: 0.2226 - acc: 0.9130 - val_loss: 0.2647 - val_acc: 0.9030\n","Epoch 54/100\n","100/100 - 25s - loss: 0.2116 - acc: 0.9130 - val_loss: 0.2548 - val_acc: 0.9040\n","Epoch 55/100\n","100/100 - 25s - loss: 0.2217 - acc: 0.9085 - val_loss: 0.2670 - val_acc: 0.9020\n","Epoch 56/100\n","100/100 - 25s - loss: 0.2154 - acc: 0.9120 - val_loss: 0.2872 - val_acc: 0.9000\n","Epoch 57/100\n","100/100 - 25s - loss: 0.2144 - acc: 0.9140 - val_loss: 0.2688 - val_acc: 0.9020\n","Epoch 58/100\n","100/100 - 25s - loss: 0.2045 - acc: 0.9100 - val_loss: 0.2676 - val_acc: 0.9050\n","Epoch 59/100\n","100/100 - 25s - loss: 0.2111 - acc: 0.9140 - val_loss: 0.2745 - val_acc: 0.8980\n","Epoch 60/100\n","100/100 - 25s - loss: 0.2206 - acc: 0.9005 - val_loss: 0.2650 - val_acc: 0.9010\n","Epoch 61/100\n","100/100 - 25s - loss: 0.2109 - acc: 0.9115 - val_loss: 0.2895 - val_acc: 0.8880\n","Epoch 62/100\n","100/100 - 25s - loss: 0.2036 - acc: 0.9145 - val_loss: 0.2825 - val_acc: 0.9040\n","Epoch 63/100\n","100/100 - 25s - loss: 0.2118 - acc: 0.9105 - val_loss: 0.2744 - val_acc: 0.8990\n","Epoch 64/100\n","100/100 - 25s - loss: 0.2140 - acc: 0.9130 - val_loss: 0.2731 - val_acc: 0.9110\n","Epoch 65/100\n","100/100 - 25s - loss: 0.1974 - acc: 0.9245 - val_loss: 0.2731 - val_acc: 0.9050\n","Epoch 66/100\n","100/100 - 25s - loss: 0.2038 - acc: 0.9130 - val_loss: 0.2722 - val_acc: 0.9090\n","Epoch 67/100\n","100/100 - 25s - loss: 0.2080 - acc: 0.9120 - val_loss: 0.2657 - val_acc: 0.9060\n","Epoch 68/100\n","100/100 - 25s - loss: 0.1966 - acc: 0.9210 - val_loss: 0.2770 - val_acc: 0.9030\n","Epoch 69/100\n","100/100 - 25s - loss: 0.2091 - acc: 0.9150 - val_loss: 0.2767 - val_acc: 0.9060\n","Epoch 70/100\n","100/100 - 25s - loss: 0.1977 - acc: 0.9220 - val_loss: 0.2629 - val_acc: 0.9140\n","Epoch 71/100\n","100/100 - 25s - loss: 0.2023 - acc: 0.9120 - val_loss: 0.2646 - val_acc: 0.9110\n","Epoch 72/100\n","100/100 - 25s - loss: 0.1904 - acc: 0.9340 - val_loss: 0.2998 - val_acc: 0.8970\n","Epoch 73/100\n","100/100 - 25s - loss: 0.1994 - acc: 0.9185 - val_loss: 0.2691 - val_acc: 0.9040\n","Epoch 74/100\n","100/100 - 25s - loss: 0.1852 - acc: 0.9275 - val_loss: 0.2706 - val_acc: 0.9090\n","Epoch 75/100\n","100/100 - 25s - loss: 0.1966 - acc: 0.9160 - val_loss: 0.2929 - val_acc: 0.9040\n","Epoch 76/100\n","100/100 - 25s - loss: 0.1870 - acc: 0.9240 - val_loss: 0.2903 - val_acc: 0.8960\n","Epoch 77/100\n","100/100 - 25s - loss: 0.1920 - acc: 0.9230 - val_loss: 0.2855 - val_acc: 0.9030\n","Epoch 78/100\n","100/100 - 25s - loss: 0.1901 - acc: 0.9260 - val_loss: 0.2843 - val_acc: 0.8980\n","Epoch 79/100\n","100/100 - 25s - loss: 0.1903 - acc: 0.9275 - val_loss: 0.2771 - val_acc: 0.9070\n","Epoch 80/100\n","100/100 - 25s - loss: 0.1919 - acc: 0.9245 - val_loss: 0.2888 - val_acc: 0.8980\n","Epoch 81/100\n","100/100 - 25s - loss: 0.1734 - acc: 0.9335 - val_loss: 0.3004 - val_acc: 0.8970\n","Epoch 82/100\n","100/100 - 25s - loss: 0.1944 - acc: 0.9185 - val_loss: 0.2800 - val_acc: 0.9000\n","Epoch 83/100\n","100/100 - 25s - loss: 0.1934 - acc: 0.9240 - val_loss: 0.2833 - val_acc: 0.9050\n","Epoch 84/100\n","100/100 - 25s - loss: 0.1802 - acc: 0.9305 - val_loss: 0.2789 - val_acc: 0.9070\n","Epoch 85/100\n","100/100 - 25s - loss: 0.1817 - acc: 0.9210 - val_loss: 0.2906 - val_acc: 0.9110\n","Epoch 86/100\n","100/100 - 25s - loss: 0.1749 - acc: 0.9310 - val_loss: 0.3025 - val_acc: 0.8980\n","Epoch 87/100\n","100/100 - 25s - loss: 0.1896 - acc: 0.9240 - val_loss: 0.2699 - val_acc: 0.9100\n","Epoch 88/100\n","100/100 - 25s - loss: 0.1743 - acc: 0.9220 - val_loss: 0.2824 - val_acc: 0.9070\n","Epoch 89/100\n","100/100 - 25s - loss: 0.1757 - acc: 0.9315 - val_loss: 0.3083 - val_acc: 0.8930\n","Epoch 90/100\n","100/100 - 25s - loss: 0.1617 - acc: 0.9330 - val_loss: 0.2790 - val_acc: 0.9040\n","Epoch 91/100\n","100/100 - 25s - loss: 0.1707 - acc: 0.9350 - val_loss: 0.2959 - val_acc: 0.9050\n","Epoch 92/100\n","100/100 - 25s - loss: 0.1641 - acc: 0.9360 - val_loss: 0.3136 - val_acc: 0.8980\n","Epoch 93/100\n","100/100 - 25s - loss: 0.1845 - acc: 0.9295 - val_loss: 0.2896 - val_acc: 0.9090\n","Epoch 94/100\n","100/100 - 25s - loss: 0.1803 - acc: 0.9370 - val_loss: 0.2776 - val_acc: 0.9080\n","Epoch 95/100\n","100/100 - 25s - loss: 0.1755 - acc: 0.9280 - val_loss: 0.2853 - val_acc: 0.9070\n","Epoch 96/100\n","100/100 - 25s - loss: 0.1906 - acc: 0.9325 - val_loss: 0.2718 - val_acc: 0.9100\n","Epoch 97/100\n","100/100 - 25s - loss: 0.1818 - acc: 0.9275 - val_loss: 0.2786 - val_acc: 0.9060\n","Epoch 98/100\n","100/100 - 25s - loss: 0.1646 - acc: 0.9345 - val_loss: 0.2875 - val_acc: 0.9140\n","Epoch 99/100\n","100/100 - 25s - loss: 0.1887 - acc: 0.9260 - val_loss: 0.2912 - val_acc: 0.9040\n","Epoch 100/100\n","100/100 - 25s - loss: 0.1659 - acc: 0.9335 - val_loss: 0.2892 - val_acc: 0.9000\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"mcMMuw_oSRAq","colab_type":"code","outputId":"0e39aa10-9353-4126-f100-24c3e105c953","executionInfo":{"status":"ok","timestamp":1567507641203,"user_tz":-120,"elapsed":4531157,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["test_lost, test_acc= modelFE.evaluate_generator(test_generator)\n","print (\"Test Accuracy:\", test_acc)"],"execution_count":17,"outputs":[{"output_type":"stream","text":["Test Accuracy: 0.9\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"0KxNfD7QiJpU","colab_type":"code","outputId":"af9eb9ea-fef1-4b95-af90-583cada9674c","executionInfo":{"status":"ok","timestamp":1567507641820,"user_tz":-120,"elapsed":4531767,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":624}},"source":["%matplotlib inline\n","\n","import matplotlib.pyplot as plt\n","\n","\n","acc      = historyFE.history[     'acc' ]\n","val_acc  = historyFE.history[ 'val_acc' ]\n","loss     = historyFE.history[    'loss' ]\n","val_loss = historyFE.history['val_loss' ]\n","\n","epochs    = range(1,len(acc)+1,1) # obtener número de epochs\n","\n","plt.plot  ( epochs,     acc, 'r--', label='Training acc'  )\n","plt.plot  ( epochs, val_acc,  'b', label='Validation acc')\n","plt.title ('Training and validation accuracy')\n","plt.ylabel('acc')\n","#plt.ylim(0,1)\n","plt.xlabel('epochs')\n","\n","plt.legend()\n","plt.figure()\n","\n","\n","plt.plot  ( epochs,     loss, 'r--' )\n","plt.plot  ( epochs, val_loss ,  'b' )\n","plt.title ('Training and validation loss'   )\n","plt.ylabel('loss')\n","plt.xlabel('epochs')\n","#plt.ylim(0,1)\n","\n","plt.legend()\n","plt.figure()\n","\n","\n"],"execution_count":18,"outputs":[{"output_type":"stream","text":["W0903 10:47:21.038351 140067097810816 legend.py:1289] No handles with labels found to put in legend.\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]},"execution_count":18},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYsAAAEWCAYAAACXGLsWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npEmWkygWmzZZ3P/33+csX7rUfAoaEe3022+W/K5pU/s+caKlqJgzx6KO9tw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7nJdcYr3J\n6D9nMNM4Mow/K8tsyNG9xngIlM/DD4fLgvDR6D94ZqbZeatWjR0BmggeeshkWfbFT6rdu2sauyuo\nPnhvRKjSKaeE4w1j0bOn6sEH69FHZWmTaqt1c+Vaei0PaBXZocuWRj20oKc+b1520Y4dqntUX6lH\n1jD746JFJtPll9v7Sy/lPMTll1tvMyUlSwelmG3v99+tl3/ssTl/Oxs3WohktWr2G3rwQdOJ8+aF\np0YceWS4EbvhBmu4g9GCquq0Oz7RKXTLod23bzf/2r77hp/vwQerdusW753PycqV8Y0Us7LMiR00\n5j16mEKM1chlZVnwWIcO4WOvWmW/e7DjrFtn/QGRcGfoiivsfkWHvQYE9/qYYwqW+aSTbH5Ip06q\nhx+ee/uIEXa/g/sf9E0irQt//WX/icsuMwUXz8insASmrYsuKt6IvSwoi+7A/yK+3wTcFFXnZ2CP\n0GcB/gl9HgCMiqg3ChiQ3/lKU1kE4WsPPGDfoxvrVavC5oHoeOirr9Zsy0a0vfSnn2zbCy/EPm9g\nE//005zll11mPZfoyWzbtpn5Ojp2viAeftjOEzlKyMiwkL9oR2JgHotULIkmsBu/wymqderoK5dN\nVsg5hSE7KiiW3S4jw1qfK6/Ur7+2avc1uk9Tq23U0/vHmBG4Y0fMeRQjhy5VsEb8mWc023cV636c\ndZZ1LoYOVa0q2/VP9tCerZZpnTp5hybPn29mMTCTQ5UqZqJ54omcv53ly+3ZBPb/V19VrVIlS5vV\n26BZGWG7x8yZdqzXXze/ekqKNXpFHX0WhgEDbMT8zTc5RxmxCEyxgSku8A2+8ILJO2iQ6t135/yN\nBr/DWD6xrVutb5DfvY7kkUc025x4zz25t0cHnD39tGb/DiIZPNiey6mnmqIqbtBJLG66qfj/v7Kg\nLPoDz0V8Pwd4IqrO68BVoc+nAgo0AK4HhkfUuxW4PsY5hgDTgel77rln0e9WIbnoIuslBg3w4sU5\n/wDBvAiwH3Ekp5wSViTRQ+3A1JOXI3nLFmvjLr00Z3nnznmH0s2ZkzN2Ph6OOMKUWTTt2+eOagnC\nLufPj//4xWXrVtVq1bL0uiOmq65ZkyvUWFWtq9WmTexu8/z5NlJ49VXNyjLTTKVKWQrWmOXLmDHZ\nBu8VK6w3e/nl9lz33NP0UCzz33HHWfjp4sXWkLeqtijfjkHkZXzwge07aFBuZ2fA0KHhIKjArBX9\nXEaNCjewS5ea4inJ4Iz8CEJQ99/fRs/5TbrcuNFkO+MM672nplrUsaqZhsA6QJHRgVlZduzosNb1\n6+2/AdYTj4fAgQyqP/4YW74qVayhVjWFvs8+uXv3CxaE55Ccckp85y4smZl27N69i575oLwoi92B\nd4GZwKNAGpAar7KIfJXWyGLtWuslRJmwdY89wlEpBx5ovRhQfeednPW6dLGGo0cP+9NE2vFPPtl6\nkPlx6qnm4A1+mBs2WLs3fHhIxoltAAAgAElEQVTe+wwaZA1JpJkiL9asseMFf4RITj89t3xXX22K\ns1RSdGRlmf3l8ce1e3dr5PMKNVZVax1uvz12mMymTdlO608+CTdk+Q7n//nHnNNNmph39c03deCA\nHVq7tpmLhgyxanXrmlkkkm7d7LmrWuQRmJ+rpGYtmxKy455+us28hpyTtwYNMqUanPO992yEURpp\nLIJRc7zBINdcY9cTjMSDKKKtW8MRadGT+AI/3YgRNspfutRMWlWqxK8oVK0BDh5zXg7pgw6y//CG\nDdZhuPba2PWCcO4XX4z//IUlSC1WVMqCsijQDBVVvxaQFvpcZs1QgYkmusdx9tmWRO3nn217EDES\nnWunYUNzdP3wg22/5RYrz8iwHlRkKGEsXnrJ9gusIl99pQXaQ5ctsxFJzAY1itGj7XixnPNBRtHI\nXuGRR8bOp5MQAvvfU0/pddfZEH/ePCuKDjUuDFlZZsqLNu/FZN48006gKqKTx2/KbgSDjkGLFrn9\nTnvvbQ2Hqk08O++8nCGsJcFDD1m4a2Zmbj+BqvkBAoVV2mRmmqJKTc3tMI5FMEUEzM8QyaxZdl0b\nNuQsX7XKzE3BflWq2O8+Oq9iPDzxRP5h3tdfb0oi+L/k5a9buNBkLSgrSzIpC8qiSsgx3TLCwd0u\nqk5DoFLo80jgztDn+sCikHO7Xuhz/fzOVxrKIjPThpvdu+feFtisTzvNeuZ//20/1KuvDtfZuNHq\njBxp3wcMsLq77RYOXnn99fxlWLnShrYjRtj3kSNtv4J8EnfcYfWiQzqjOeMMkyVWjyqIAIt0pDdu\nbLH3pcINN1gLkJ6enUYimJQVHWqczY4dFhQfOUHl4otjh+LES9Bl7dEjOwy0cuVwg9C5c+7ouHr1\nzFxVmpx7rvWQMzPttxdrUlhp8vzz4Ul+8RBMnCts4MTy5XauSy7JO2VXcfngA5OtVSt7tqUxOksU\nSVcWJgPHA/NDUVG3hMruBE4Kfe6PhcbOB54DdonY90Is5HYhcEFB5yopZZGfOSWIahg9Ove2YEQB\n4Um5bdvmtFX+8ottDybUrlhhw+2LLrLX1VfHl+GhR49w6F7fvvElGdy40UJv99svj8lTWVm6bZuZ\nz6JNbAFBxz6IrlqxQkvPuZ2Zaba+kNMkyGdUtapdV57mnJ9/tuFQkFxn82ZTOFEhpYUmKyvbYzl1\nak7d07t3zg5FRkbOyJ3SIhiFzpljzmJQ/ah8ZAtXVTNdPfxw8hIM5sfq1eH/e17Ri+WFMqEsSvNV\nEspi+3ZreCJzvUVy4onWk46V2iMrK+xUDGZ39uljvc6AQNkUNOGqIO67z47z5592znh79uPH22in\nefOopIT33KNaqZJ+8el2hbwTxm3ebI1eMKoJokK+/LIYFxPJqlXhm/v11xYWE7QUQRhNhKYOrEEF\n/lnPPddsBosWWUY7CGdpTAD9+5tvPWDVKjtl9KzzRBPkFHvkkfBk7pJKEeGYjwsKN1oqi8SrLHwN\n7gjmzbPVIx98EEaNyrlt8WL4+GO46CLYZZfc+4pAr17QoAH07Wtle+6Zc6nkYP3c5s2LJ+dJJ9n7\nQw/Z6pjdu8e3X+/e8PXXtgzzIYfA5MmhDTfdBFlZfDRqGSkpcNRRsfevXt1W8wyWeZ47197bty/C\nRSxZAnffbWs5d+9uN65hQ/j++/D2IUPgjjvse4MGdvODiyd83b17F3CukSNt+dCbb7aFjAG6dSuC\n0PFRrx6sXRv+vmaNvdevn7BTxmTPPWGffWwl1qlT7XuTJqUrQ0XmiCOsLTj22GRLUkrEo1HKw6sk\nRhZBGGiXLmaDHj/eyjMyLLqlcuX847SXL88Zax3EggempVtusWOUhH1z333DeZjmzi3cvgsXmsO1\nXr3QzN3hwzULtEXt9FxJy6I54QQLoVW1SX+NG2Wad3/ChPx3nDrVQkaCYUjg4W/a1GJ1L7nEPLRB\nes3MzHAiolgpS9X8RJUrx5mpNIg4aNXKzplAbrjBnk0wKApSaiRjFbYhQ8y02Ly5jXickmPNmvjW\nsyrr4GaowjN0qIVArl1r4XmpqWbiaNDA7lR0PqKCCHLXBM7XgQPNdFISBOkP6tQpWr6ZuXPN4XnV\nVfZ9zjHXKqj+99n8DcTXX29RSBkZFiJ8ZPeQ1x5i5O9W04y33GL2q2rVzB4SlEeHs0STkWE3HWyp\nwCjj9Y4dhUhN/c8/5kjYa6+Ee+SDzKRBIsdgMmWsCLNEE6xeB9n5Dh0nB/EqCzdDRfDjj9C5M6Sm\nwkcf2RDzs8/g+OPhzTfhhRcKd7zA3BSYn/78s/gmqIDAGnPQQVCpCE9x//1h0CB48kllwZwtfLj/\nLQD0PVHClT7/HFq1gttugxUrAGjTBrZtg99/h59+gvYH1YTVq6FHDzjzTHjkEcjKsv2XLjUb0ciR\ncP75kJ4O115r26pUgVq18heycmV45RU48UR45x3IyMixuUoV2HffOC+4dm2YNMkEL+yDLCT16tl7\nYIpavdreS9sMBWYaDTjwwNI/v1NxcGURIiMDZs2CAw6w7y1bwqJF1ka+8gqcfrrZ7AtDtLJYsqTk\nlEX37tbgn3JK0Y9x552Qolu4scf3fPhdfQ46CHbdNbRxxw644gpYuRLuussM3uPGsd9+tvmTT8z3\n0aHlBmsFv/jChLnmGnjrLas0d65p4FdesQa6Tp3CC1m1Knz4Ifz6q30uBwRKIfBVBO8NGpS+LE2a\n2O9EBLp0Kf3zOxUHVxYhfvvNGr/IP1T16ta5LSq77Wb7L1liyigtzdrckqBKFWuLL7206MfYtXEW\nN1Z9mPc2HMXUqXDSvr/CgAFmtfjuO1i4EEaPtob64ouhe/dsZTF29HYA2o9/xApSUmDsWHjuOejQ\nwcratjVlcc45xbjSEOVEUUDukUWgLFJTkyPPoEHW2aldOznndyoGVZItQFlhxgx7D0YWJUGVKtCs\nmY0sli2DzMySG1mUCD//zLVbR/JMvatZurYmJ+0zD0aMgRtusFCPBQtsiCUCjz0GQL1162iyizJl\nRj2ELNqOPDt8vMqVrWUKKCnNWM6IpSxSU4vX8SgOV1+dnPM6FQsfWYT48UeoUQNaty7Z4zZvbsoi\nCKEtU8pi4kRqsIX/PvAPQ4ZAu0sOMwdISDGw116mKCJZtoz9dB4A+9RNp8b+e5Wy0GWfWD6LZPgr\nHKckcWURYsYM6NSp5Ht/wVyLwG9Rpjrb334LTZvS54JdGTUKpHEj02YvvQRPPx17n7Zt2e9fNrGi\n/aF1S0/WckSskUUy/BWOU5K4ssCCd2bOTIwDsHlz81X88Yd9L1PK4sYb4Zlnco4ebrvNnDURk9+i\nadPNHNXtD0xJtITlkrp17ZZGKgsfWTjlHVcWwPz5sGlTyforApo3N1/FlCk2QblmzZI/R5Hp3Dk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VFu3a2kHM8ZXHllfDAA3nb9tvP3gv6b4xDqCwqempfeSErK2JNgFsWkFdZfPtt4n7X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\nUyj/D3PH3GTGrh33AAAAAElFTkSuQmCC\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"C1ISi6Wdl4_x","colab_type":"text"},"source":["### ModelFT : Modelo con *Fine Tuning*"]},{"cell_type":"code","metadata":{"id":"QZfhhNnptlH0","colab_type":"code","outputId":"d6217403-fa58-4132-9de5-22a21cbbb5ff","executionInfo":{"status":"ok","timestamp":1567507642249,"user_tz":-120,"elapsed":4532190,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":799}},"source":["import tensorflow as tf\n","\n","from tensorflow.keras.applications import VGG16\n","\n","pre_trained_model = VGG16(input_shape = (150, 150, 3), \n","                                include_top = False, \n","                                weights = 'imagenet')\n","\n","pre_trained_model.trainable = True\n","\n","set_trainable = False\n","\n","\n","for layer in pre_trained_model.layers:\n","  if layer.name == 'block5_conv1':\n","    set_trainable = True\n","  if set_trainable: \n","    layer.trainable = True\n","  else:\n","    layer.trainable = False\n","\n","pre_trained_model.summary()\n","\n","\n"],"execution_count":19,"outputs":[{"output_type":"stream","text":["Model: \"vgg16\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","input_2 (InputLayer)         [(None, 150, 150, 3)]     0         \n","_________________________________________________________________\n","block1_conv1 (Conv2D)        (None, 150, 150, 64)      1792      \n","_________________________________________________________________\n","block1_conv2 (Conv2D)        (None, 150, 150, 64)      36928     \n","_________________________________________________________________\n","block1_pool (MaxPooling2D)   (None, 75, 75, 64)        0         \n","_________________________________________________________________\n","block2_conv1 (Conv2D)        (None, 75, 75, 128)       73856     \n","_________________________________________________________________\n","block2_conv2 (Conv2D)        (None, 75, 75, 128)       147584    \n","_________________________________________________________________\n","block2_pool (MaxPooling2D)   (None, 37, 37, 128)       0         \n","_________________________________________________________________\n","block3_conv1 (Conv2D)        (None, 37, 37, 256)       295168    \n","_________________________________________________________________\n","block3_conv2 (Conv2D)        (None, 37, 37, 256)       590080    \n","_________________________________________________________________\n","block3_conv3 (Conv2D)        (None, 37, 37, 256)       590080    \n","_________________________________________________________________\n","block3_pool (MaxPooling2D)   (None, 18, 18, 256)       0         \n","_________________________________________________________________\n","block4_conv1 (Conv2D)        (None, 18, 18, 512)       1180160   \n","_________________________________________________________________\n","block4_conv2 (Conv2D)        (None, 18, 18, 512)       2359808   \n","_________________________________________________________________\n","block4_conv3 (Conv2D)        (None, 18, 18, 512)       2359808   \n","_________________________________________________________________\n","block4_pool (MaxPooling2D)   (None, 9, 9, 512)         0         \n","_________________________________________________________________\n","block5_conv1 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_conv2 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_conv3 (Conv2D)        (None, 9, 9, 512)         2359808   \n","_________________________________________________________________\n","block5_pool (MaxPooling2D)   (None, 4, 4, 512)         0         \n","=================================================================\n","Total params: 14,714,688\n","Trainable params: 7,079,424\n","Non-trainable params: 7,635,264\n","_________________________________________________________________\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"xN8OOenogf3N","colab_type":"code","outputId":"acea2e1b-f3ad-4279-be8b-0793ae4c672b","executionInfo":{"status":"ok","timestamp":1567507642250,"user_tz":-120,"elapsed":4532185,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":289}},"source":["modelFT = tf.keras.models.Sequential([\n","    pre_trained_model,\n","    tf.keras.layers.Flatten(),\n","    tf.keras.layers.Dense(256, activation='relu'),\n","    tf.keras.layers.Dense(1, activation='sigmoid')\n","])\n","\n","modelFT.summary()"],"execution_count":20,"outputs":[{"output_type":"stream","text":["Model: \"sequential_2\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","vgg16 (Model)                (None, 4, 4, 512)         14714688  \n","_________________________________________________________________\n","flatten_2 (Flatten)          (None, 8192)              0         \n","_________________________________________________________________\n","dense_4 (Dense)              (None, 256)               2097408   \n","_________________________________________________________________\n","dense_5 (Dense)              (None, 1)                 257       \n","=================================================================\n","Total params: 16,812,353\n","Trainable params: 9,177,089\n","Non-trainable params: 7,635,264\n","_________________________________________________________________\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"YuZLpjNFghlD","colab_type":"code","colab":{}},"source":["from tensorflow.keras.optimizers import RMSprop\n","\n","modelFT.compile(loss='binary_crossentropy',\n","              optimizer=RMSprop(lr=1e-4), \n","              metrics=['acc'])"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"UnRIx8pDR_wq","colab_type":"code","outputId":"5c4258d3-a366-4ab7-e158-c28e610c80c1","executionInfo":{"status":"ok","timestamp":1567507642814,"user_tz":-120,"elapsed":4532737,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["from tensorflow.keras.preprocessing.image import ImageDataGenerator\n","\n","\n","train_datagen = ImageDataGenerator(\n","      rescale=1./255,\n","      rotation_range=40,\n","      width_shift_range=0.2,\n","      height_shift_range=0.2,\n","      shear_range=0.2,\n","      zoom_range=0.2,\n","      horizontal_flip=True,\n","      fill_mode='nearest')\n","\n","validation_datagen  = ImageDataGenerator( rescale = 1.0/255. )\n","test_datagen  = ImageDataGenerator( rescale = 1.0/255. )\n","\n","\n","train_generator = train_datagen.flow_from_directory(train_dir,\n","                                                    batch_size=20,\n","                                                    class_mode='binary',\n","                                                    target_size=(150, 150))     \n","\n","validation_generator =  validation_datagen.flow_from_directory(validation_dir,\n","                                                         batch_size=20,\n","                                                         class_mode  = 'binary',\n","                                                         target_size = (150, 150))\n","\n","\n","test_generator =  test_datagen.flow_from_directory(validation_dir,\n","                                                         batch_size=20,\n","                                                         class_mode  = 'binary',\n","                                                         target_size = (150, 150))\n","\n"],"execution_count":22,"outputs":[{"output_type":"stream","text":["Found 2000 images belonging to 2 classes.\n","Found 1000 images belonging to 2 classes.\n","Found 1000 images belonging to 2 classes.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"4fSK81y-tlLa","colab_type":"code","outputId":"8f174186-9ff5-4ac4-e256-41664f59e025","executionInfo":{"status":"ok","timestamp":1567510270900,"user_tz":-120,"elapsed":7160816,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["batch_size = 20\n","steps_per_epoch = train_generator.n // batch_size\n","validation_steps = validation_generator.n // batch_size\n","\n","historyFT = modelFT.fit_generator(\n","            train_generator,\n","            validation_data = validation_generator,\n","            steps_per_epoch = steps_per_epoch,\n","            epochs = 100,\n","            validation_steps = validation_steps,\n","            verbose = 2)\n"],"execution_count":23,"outputs":[{"output_type":"stream","text":["Epoch 1/100\n","100/100 - 29s - loss: 0.5147 - acc: 0.7550 - val_loss: 0.3326 - val_acc: 0.8700\n","Epoch 2/100\n","100/100 - 26s - loss: 0.3605 - acc: 0.8450 - val_loss: 0.2648 - val_acc: 0.8800\n","Epoch 3/100\n","100/100 - 26s - loss: 0.2781 - acc: 0.8805 - val_loss: 0.1782 - val_acc: 0.9230\n","Epoch 4/100\n","100/100 - 26s - loss: 0.2684 - acc: 0.8955 - val_loss: 0.1695 - val_acc: 0.9220\n","Epoch 5/100\n","100/100 - 26s - loss: 0.2433 - acc: 0.8975 - val_loss: 0.1893 - val_acc: 0.9180\n","Epoch 6/100\n","100/100 - 26s - loss: 0.2358 - acc: 0.9035 - val_loss: 0.1749 - val_acc: 0.9280\n","Epoch 7/100\n","100/100 - 26s - loss: 0.2572 - acc: 0.9085 - val_loss: 0.1784 - val_acc: 0.9310\n","Epoch 8/100\n","100/100 - 26s - loss: 0.2101 - acc: 0.9195 - val_loss: 0.1819 - val_acc: 0.9290\n","Epoch 9/100\n","100/100 - 26s - loss: 0.1979 - acc: 0.9250 - val_loss: 0.1911 - val_acc: 0.9260\n","Epoch 10/100\n","100/100 - 26s - loss: 0.1958 - acc: 0.9285 - val_loss: 0.2873 - val_acc: 0.8960\n","Epoch 11/100\n","100/100 - 26s - loss: 0.2073 - acc: 0.9225 - val_loss: 0.2322 - val_acc: 0.9300\n","Epoch 12/100\n","100/100 - 26s - loss: 0.1864 - acc: 0.9220 - val_loss: 0.1846 - val_acc: 0.9350\n","Epoch 13/100\n","100/100 - 26s - loss: 0.1689 - acc: 0.9375 - val_loss: 0.2812 - val_acc: 0.9390\n","Epoch 14/100\n","100/100 - 26s - loss: 0.1838 - acc: 0.9390 - val_loss: 0.2531 - val_acc: 0.9360\n","Epoch 15/100\n","100/100 - 26s - loss: 0.1762 - acc: 0.9380 - val_loss: 0.3067 - val_acc: 0.9160\n","Epoch 16/100\n","100/100 - 26s - loss: 0.1740 - acc: 0.9420 - val_loss: 0.3313 - val_acc: 0.9040\n","Epoch 17/100\n","100/100 - 26s - loss: 0.1545 - acc: 0.9420 - val_loss: 0.3211 - val_acc: 0.9340\n","Epoch 18/100\n","100/100 - 26s - loss: 0.2292 - acc: 0.9370 - val_loss: 0.2118 - val_acc: 0.9280\n","Epoch 19/100\n","100/100 - 26s - loss: 0.1453 - acc: 0.9410 - val_loss: 0.2227 - val_acc: 0.9280\n","Epoch 20/100\n","100/100 - 26s - loss: 0.2455 - acc: 0.9455 - val_loss: 0.1971 - val_acc: 0.9400\n","Epoch 21/100\n","100/100 - 26s - loss: 0.1775 - acc: 0.9440 - val_loss: 0.2363 - val_acc: 0.9390\n","Epoch 22/100\n","100/100 - 26s - loss: 0.1626 - acc: 0.9485 - val_loss: 0.1802 - val_acc: 0.9300\n","Epoch 23/100\n","100/100 - 26s - loss: 0.1744 - acc: 0.9485 - val_loss: 0.1833 - val_acc: 0.9360\n","Epoch 24/100\n","100/100 - 26s - loss: 0.1349 - acc: 0.9550 - val_loss: 0.3447 - val_acc: 0.9000\n","Epoch 25/100\n","100/100 - 26s - loss: 0.1478 - acc: 0.9495 - val_loss: 0.8002 - val_acc: 0.9000\n","Epoch 26/100\n","100/100 - 26s - loss: 0.1634 - acc: 0.9565 - val_loss: 0.2292 - val_acc: 0.9280\n","Epoch 27/100\n","100/100 - 26s - loss: 0.1238 - acc: 0.9560 - val_loss: 0.4442 - val_acc: 0.9290\n","Epoch 28/100\n","100/100 - 26s - loss: 0.1466 - acc: 0.9500 - val_loss: 0.8985 - val_acc: 0.9310\n","Epoch 29/100\n","100/100 - 26s - loss: 0.1596 - acc: 0.9465 - val_loss: 3.1479 - val_acc: 0.7470\n","Epoch 30/100\n","100/100 - 26s - loss: 0.1696 - acc: 0.9510 - val_loss: 0.6715 - val_acc: 0.9250\n","Epoch 31/100\n","100/100 - 26s - loss: 0.1326 - acc: 0.9580 - val_loss: 0.3718 - val_acc: 0.9330\n","Epoch 32/100\n","100/100 - 26s - loss: 0.1339 - acc: 0.9605 - val_loss: 5.6248 - val_acc: 0.8460\n","Epoch 33/100\n","100/100 - 26s - loss: 0.1595 - acc: 0.9580 - val_loss: 0.4294 - val_acc: 0.9350\n","Epoch 34/100\n","100/100 - 26s - loss: 0.1403 - acc: 0.9600 - val_loss: 0.6552 - val_acc: 0.9270\n","Epoch 35/100\n","100/100 - 26s - loss: 0.1270 - acc: 0.9635 - val_loss: 0.6607 - val_acc: 0.9390\n","Epoch 36/100\n","100/100 - 26s - loss: 0.1149 - acc: 0.9615 - val_loss: 0.2563 - val_acc: 0.9370\n","Epoch 37/100\n","100/100 - 26s - loss: 0.0965 - acc: 0.9660 - val_loss: 0.5680 - val_acc: 0.9240\n","Epoch 38/100\n","100/100 - 26s - loss: 0.1353 - acc: 0.9590 - val_loss: 0.8719 - val_acc: 0.9350\n","Epoch 39/100\n","100/100 - 26s - loss: 0.1315 - acc: 0.9635 - val_loss: 0.4600 - val_acc: 0.9370\n","Epoch 40/100\n","100/100 - 26s - loss: 0.0907 - acc: 0.9725 - val_loss: 0.8014 - val_acc: 0.9370\n","Epoch 41/100\n","100/100 - 26s - loss: 0.1161 - acc: 0.9690 - val_loss: 0.7092 - val_acc: 0.9340\n","Epoch 42/100\n","100/100 - 26s - loss: 0.1104 - acc: 0.9665 - val_loss: 0.6822 - val_acc: 0.9310\n","Epoch 43/100\n","100/100 - 26s - loss: 0.1023 - acc: 0.9695 - val_loss: 1.6983 - val_acc: 0.9430\n","Epoch 44/100\n","100/100 - 26s - loss: 0.1329 - acc: 0.9720 - val_loss: 0.7970 - val_acc: 0.9360\n","Epoch 45/100\n","100/100 - 26s - loss: 0.1048 - acc: 0.9695 - val_loss: 1.5540 - val_acc: 0.9190\n","Epoch 46/100\n","100/100 - 26s - loss: 0.1129 - acc: 0.9735 - val_loss: 2.6871 - val_acc: 0.9130\n","Epoch 47/100\n","100/100 - 26s - loss: 0.1571 - acc: 0.9670 - val_loss: 2.3150 - val_acc: 0.9180\n","Epoch 48/100\n","100/100 - 26s - loss: 0.0699 - acc: 0.9760 - val_loss: 1.6125 - val_acc: 0.9350\n","Epoch 49/100\n","100/100 - 26s - loss: 0.0895 - acc: 0.9730 - val_loss: 1.7127 - val_acc: 0.9360\n","Epoch 50/100\n","100/100 - 26s - loss: 0.1436 - acc: 0.9750 - val_loss: 0.6143 - val_acc: 0.9270\n","Epoch 51/100\n","100/100 - 26s - loss: 0.0887 - acc: 0.9805 - val_loss: 1.0784 - val_acc: 0.9360\n","Epoch 52/100\n","100/100 - 26s - loss: 0.1448 - acc: 0.9815 - val_loss: 0.5684 - val_acc: 0.9400\n","Epoch 53/100\n","100/100 - 26s - loss: 0.0867 - acc: 0.9760 - val_loss: 1.4111 - val_acc: 0.9300\n","Epoch 54/100\n","100/100 - 26s - loss: 0.1704 - acc: 0.9780 - val_loss: 0.9833 - val_acc: 0.9350\n","Epoch 55/100\n","100/100 - 26s - loss: 0.0895 - acc: 0.9700 - val_loss: 0.7777 - val_acc: 0.9330\n","Epoch 56/100\n","100/100 - 26s - loss: 0.1229 - acc: 0.9760 - val_loss: 0.7545 - val_acc: 0.9290\n","Epoch 57/100\n","100/100 - 26s - loss: 0.1379 - acc: 0.9750 - val_loss: 1.1466 - val_acc: 0.9280\n","Epoch 58/100\n","100/100 - 26s - loss: 0.0468 - acc: 0.9805 - val_loss: 1.7382 - val_acc: 0.9340\n","Epoch 59/100\n","100/100 - 26s - loss: 0.1076 - acc: 0.9680 - val_loss: 2.1631 - val_acc: 0.9360\n","Epoch 60/100\n","100/100 - 26s - loss: 0.0851 - acc: 0.9800 - val_loss: 1.5342 - val_acc: 0.9410\n","Epoch 61/100\n","100/100 - 26s - loss: 0.0845 - acc: 0.9750 - val_loss: 1.8658 - val_acc: 0.9370\n","Epoch 62/100\n","100/100 - 26s - loss: 0.0819 - acc: 0.9770 - val_loss: 1.2347 - val_acc: 0.9400\n","Epoch 63/100\n","100/100 - 26s - loss: 0.1699 - acc: 0.9750 - val_loss: 0.8054 - val_acc: 0.9330\n","Epoch 64/100\n","100/100 - 26s - loss: 0.0701 - acc: 0.9805 - val_loss: 1.3720 - val_acc: 0.9350\n","Epoch 65/100\n","100/100 - 26s - loss: 0.0807 - acc: 0.9790 - val_loss: 1.6991 - val_acc: 0.9310\n","Epoch 66/100\n","100/100 - 26s - loss: 0.0829 - acc: 0.9790 - val_loss: 2.1548 - val_acc: 0.8520\n","Epoch 67/100\n","100/100 - 26s - loss: 0.0882 - acc: 0.9810 - val_loss: 1.7728 - val_acc: 0.9360\n","Epoch 68/100\n","100/100 - 26s - loss: 0.0571 - acc: 0.9860 - val_loss: 1.5555 - val_acc: 0.9340\n","Epoch 69/100\n","100/100 - 26s - loss: 0.1502 - acc: 0.9725 - val_loss: 0.9860 - val_acc: 0.9430\n","Epoch 70/100\n","100/100 - 26s - loss: 0.0678 - acc: 0.9800 - val_loss: 2.1036 - val_acc: 0.8760\n","Epoch 71/100\n","100/100 - 26s - loss: 0.0726 - acc: 0.9815 - val_loss: 1.6511 - val_acc: 0.9270\n","Epoch 72/100\n","100/100 - 26s - loss: 0.1432 - acc: 0.9800 - val_loss: 0.9822 - val_acc: 0.9380\n","Epoch 73/100\n","100/100 - 26s - loss: 0.0532 - acc: 0.9850 - val_loss: 2.4210 - val_acc: 0.9370\n","Epoch 74/100\n","100/100 - 26s - loss: 0.0642 - acc: 0.9850 - val_loss: 1.6140 - val_acc: 0.9470\n","Epoch 75/100\n","100/100 - 26s - loss: 0.0794 - acc: 0.9820 - val_loss: 1.6657 - val_acc: 0.9400\n","Epoch 76/100\n","100/100 - 26s - loss: 0.1449 - acc: 0.9785 - val_loss: 1.3473 - val_acc: 0.9330\n","Epoch 77/100\n","100/100 - 26s - loss: 0.0695 - acc: 0.9830 - val_loss: 0.8823 - val_acc: 0.9300\n","Epoch 78/100\n","100/100 - 26s - loss: 0.1030 - acc: 0.9790 - val_loss: 1.1929 - val_acc: 0.9150\n","Epoch 79/100\n","100/100 - 26s - loss: 0.0843 - acc: 0.9755 - val_loss: 0.7458 - val_acc: 0.9290\n","Epoch 80/100\n","100/100 - 26s - loss: 0.0537 - acc: 0.9890 - val_loss: 1.1176 - val_acc: 0.9380\n","Epoch 81/100\n","100/100 - 26s - loss: 0.0477 - acc: 0.9850 - val_loss: 2.4060 - val_acc: 0.9410\n","Epoch 82/100\n","100/100 - 26s - loss: 0.1374 - acc: 0.9820 - val_loss: 0.8478 - val_acc: 0.9210\n","Epoch 83/100\n","100/100 - 26s - loss: 0.0685 - acc: 0.9830 - val_loss: 3.2805 - val_acc: 0.9390\n","Epoch 84/100\n","100/100 - 26s - loss: 0.1143 - acc: 0.9805 - val_loss: 1.5843 - val_acc: 0.9410\n","Epoch 85/100\n","100/100 - 26s - loss: 0.0850 - acc: 0.9810 - val_loss: 1.4982 - val_acc: 0.9320\n","Epoch 86/100\n","100/100 - 26s - loss: 0.1075 - acc: 0.9850 - val_loss: 1.2640 - val_acc: 0.9390\n","Epoch 87/100\n","100/100 - 26s - loss: 0.0822 - acc: 0.9800 - val_loss: 0.9531 - val_acc: 0.9370\n","Epoch 88/100\n","100/100 - 26s - loss: 0.0491 - acc: 0.9850 - val_loss: 2.1300 - val_acc: 0.9390\n","Epoch 89/100\n","100/100 - 26s - loss: 0.0732 - acc: 0.9845 - val_loss: 2.2533 - val_acc: 0.9400\n","Epoch 90/100\n","100/100 - 26s - loss: 0.0675 - acc: 0.9905 - val_loss: 3.7502 - val_acc: 0.9390\n","Epoch 91/100\n","100/100 - 26s - loss: 0.0546 - acc: 0.9835 - val_loss: 3.0349 - val_acc: 0.9200\n","Epoch 92/100\n","100/100 - 26s - loss: 0.0648 - acc: 0.9850 - val_loss: 1.1284 - val_acc: 0.9310\n","Epoch 93/100\n","100/100 - 26s - loss: 0.0817 - acc: 0.9875 - val_loss: 2.1876 - val_acc: 0.9370\n","Epoch 94/100\n","100/100 - 26s - loss: 0.0771 - acc: 0.9830 - val_loss: 1.5399 - val_acc: 0.9350\n","Epoch 95/100\n","100/100 - 26s - loss: 0.0639 - acc: 0.9890 - val_loss: 2.4183 - val_acc: 0.9270\n","Epoch 96/100\n","100/100 - 26s - loss: 0.0568 - acc: 0.9865 - val_loss: 2.3577 - val_acc: 0.9330\n","Epoch 97/100\n","100/100 - 26s - loss: 0.0640 - acc: 0.9850 - val_loss: 1.9573 - val_acc: 0.9220\n","Epoch 98/100\n","100/100 - 26s - loss: 0.1788 - acc: 0.9845 - val_loss: 1.3799 - val_acc: 0.9340\n","Epoch 99/100\n","100/100 - 26s - loss: 0.0620 - acc: 0.9845 - val_loss: 2.0226 - val_acc: 0.9290\n","Epoch 100/100\n","100/100 - 26s - loss: 0.1097 - acc: 0.9855 - val_loss: 2.3635 - val_acc: 0.9390\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"xnJPyi2KtlW5","colab_type":"code","outputId":"a21b117f-8cf4-4172-a4f2-e8760aba6e2c","executionInfo":{"status":"ok","timestamp":1567510271604,"user_tz":-120,"elapsed":7161514,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":624}},"source":["%matplotlib inline\n","\n","import matplotlib.pyplot as plt\n","\n","acc      = historyFT.history[     'acc' ]\n","val_acc  = historyFT.history[ 'val_acc' ]\n","loss     = historyFT.history[    'loss' ]\n","val_loss = historyFT.history['val_loss' ]\n","\n","epochs    = range(1,len(acc)+1,1) # obtener número de epochs\n","\n","plt.plot  ( epochs,     acc, 'r--', label='Training acc'  )\n","plt.plot  ( epochs, val_acc,  'b', label='Validation acc')\n","plt.title ('Training and validation accuracy')\n","plt.ylabel('acc')\n","#plt.ylim(0,1)\n","plt.xlabel('epochs')\n","\n","plt.legend()\n","plt.figure()\n","\n","\n","plt.plot  ( epochs,     loss, 'r--' )\n","plt.plot  ( epochs, val_loss ,  'b' )\n","plt.title ('Training and validation loss'   )\n","plt.ylabel('loss')\n","plt.xlabel('epochs')\n","plt.ylim(0,1)\n","\n","plt.legend()\n","plt.figure()\n","\n"],"execution_count":24,"outputs":[{"output_type":"stream","text":["W0903 11:31:10.621910 140067097810816 legend.py:1289] No handles with labels found to put in legend.\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]},"execution_count":24},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYsAAAEWCAYAAACXGLsWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n5JGmeKLdIvn55nqaPNkURyzee8+u8e671vBmZdlIorIowGjefNMUWPS1t2x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PnolbP5s3\nm0UxZEg47emn7Zr/+1847frrTaHk5obTpkyxcs8+q5qdbZ+vuy6c/9VXpriKk2XbNvvf/PWv8eVr\n396U5S67mAwjR6pu2pTY/cXjpJPM0xxL6SaKK4sqxrnnarhnctRRFmBQ+4E2bmwNYXE89ljhBiGS\noHceaWqr2p8AVB9+2I4/+UR39qJieblSzcCB9oePVFSDB5srJWjEtm61P9uFFxY+9557TO6LL7Ye\nbzSBv75Nm7C//uef7Zw77ihcdvBga3QTZfhw62H/7neqN9xgdd52Wzh/xw7zDka7RI49VrVt2/C9\nBdZG3brmLoxWbLG45x7rBdeqZd9JrHuPxUsv2bXuuUd11Kiw2+Xii+M3itOnW5nAUgHV444Lfwf7\n7hv/en36mDJNtPF/6imr/9VXEyv/5JNW/uOPw2nffKNFevv9+6t261b43IIC1U6d7C937LHm5Y1W\nuInQo4d1SGJx9dW601pascJcciLmkkuUxx4rbA2uWGH/62uuKb2skbiyqEI884w9ieuvDyXk5haK\nsh55pAVF41FQYBZCixbmo48m6J1H99pV7Q/SsaM1wp06We8IVP/zn3LdUrFcdpndczR9+9q1777b\njjdvtoYw2lV28snWyEY2PIceai684sjOtqBv3brWGAXumPnzC5cL/P7R1kE82rYt7DM+9ljrGQdu\nr/fes/omTCh83oQJlj5lir1q1LCe8bnn2ucGDVRfey3+dQPlfuKJhcc6JMKOHfZ9gTU4559vSgOK\ndioCPvgg3CBPmGBumU8/tbzzz7dYSCyCeNmYMYnLl5+vesAB1htfsqT4sgUFqgcfbIHnyN/Etm2m\nBK++OnzPTZpYjz6ahx8OK8D7709czkjOP9/qj1aI335r3/G55xZOHzzYykda9rm5lh7tSV6/3u5l\nl13CHbngdxr9+y0trizSwKZNqitXlu6c776zBvGoo+IHvy691H4k8UzN1avDP/Szzy6a//vfW+88\nVq8uUCRBgC6IbZTV7bVyZfEmcWDNnHJK0byg8dpzT1NekybZ8YcfFi43bpylz5ljx4sW2fFdd5Us\n3y+/hAPmjRqZgowmaITfeqvk+oKA6b33htPefNPSXn/djk86yeIsW7cWPjc316zGAQMsCN2pk42W\nUrWBB716WQPx738XvW6g3Nu2Lbsr45tvzH0W+M8LCqwhBQvqRhM8j6+/Lpr3t7+ZEo5FYPWVtlH7\n9FN7Rs2bm6KKR2DxPPpo0bxu3cziU7Xrg+oTTxQtt3GjasOGqu3aFX1OiTJ+vNUfqbjz860j07Kl\nWfiRBP+FO+8Mp113naX171+47IsvWnr9+uHfSadOqv/3f2WTNRJXFhXMrFnmB65d23poiSiNTZus\nV7/77hEjfJ55xkyMiJY9sDyCwF00M2ZY/sEH686eakC83nnAli1ht8Jpp1kDBqq33prYfQfMmWNK\nCeyHHY/Bg61M8AeOpGPH8IiWqEmpAAAgAElEQVST8eNVzzrL3FJBQDUgcB8Ff7IgSB09/DEe27eb\nbxkKxwwCcnPNrZOIeR8EGCNHOOfnmwXTr1/Yz3/DDbHPP/98Oz+yxxiwfr3FAerVK+xeUQ27rMoT\n2IxFfn54gEB08P2FFyw9VnD21lstL1ZDe+ihxcczimPBAnNf1ahhSicWwYisQNFGcs45pqgLClSf\nf153xk1i8dFHZgWUlZkzrf6XXw6nvfyypb3wQuxzjj3W4hhbtljHsVYtu5caNQpbtkOHWjvxn//Y\n7+nww8P/k/LiyqICeekl+7Pvuac1cDVr2iiM0aNjWAsFBTsHbwe9hUJ/+H79ijhVv/22+Eb41VfD\nDdY++5jvOAjgvfGGxuydR3LzzdbzCfzdzZoVjQnEYu1aayzPOMN+wLvuqjv94LGYN093WkBHHFE0\nv00bs4y6d7f7aNZM9Y9/jF1Xly7mnlNVPeggc4mUlrlzzVURi0MPDddfHFddZa676EbyH/+w+xw4\n0H4PwejnaL75xhqH55+Pnb96tTWWDRqY1Td/vgVs69Qx5Z4K3n3XZJ8+vXD6Y49Z+rJlRc8JLNLo\nOEtg9UX2nkvLb7/ZsNxYCmzlyvCIrFgEAwuWL7c4QfToqGQSBLn/9rdw2qBB1i7EGzgQBNcfecQs\nyRYtLK4BNihA1RRJgwZh91kw7Lh+/cIurLLiyqKCuOuucOMXNLbz55sPu8gInK1bzSm9yy6qy5fr\n7bdbmZ3DQLdts19A1C8/1o8wksB3uW5d2K8cmKitW8funUeyY0d42KCqNb4nnxy//OrV1rMRsWs1\naGCNZuCbjg4YB5x1lt16r15mBUXTrJlZQK+9FlYqb7wRu65rr7VGOJgU9tBD8eUtC3/5i8la0rj4\n3r2LBq5V7ZkHE+AiR+jEorhno2qNc5cu4e+kTh3zdScazC4tn36qMeNWd99t6bEaqMCdGT1sOLD6\nSoo7lMScOVbPk08WTg9ckt99F/u8adMs/9//tlFvffuWT46S6N7d3Jyq9n+sU8cGK8SjoMBGfQWx\nwqDTcMABNihA1Ub+QTi4nZ9vnarRo5Mjc6LKwpf7KAdbt9ryEAMGwJQpsMcelr7ffvDKK7acwWef\n2bIDMz/JtaU3XnvNFsNp1YqcHNuaepddQhVmZ9uqbH37FrpOnTq2DfY338SWY8kSaNLEXsceawux\nZWVZvR07wq23Qu3a8e+jRg1bdiEgKwuWLYtf/vPP7TVqFHzyiS1oe9dd4fvPyyt6zk8/2XqGf/4z\ntG1rSzJEs3mzbe09eLDJXa+e7e4aixNOsCUWzj/f5P/DH+LLWxYOP9w25Zk9O36ZvDx7ZIcfXjSv\nZcvwMhajRhV/reKeDcCee8K338LChbaZ4amn2m8r+L6TTYMG9r5pU+H04JlFbr8e0LixvW/cWDj9\ntdfs+2nbtnwyde5s3+nHHxdO/89/bAHlAw6IfV7Xrvb+1Vf2HfbsWT45SqJ7d1vzStWWkcnLC/8O\nYiFia5Ll5UH//nDGGZY+bJj9t3JyrJ6GDcMLONesac//pptSey9FSESjVIVXOiyLiRNN4xcXfJsx\nQ7VNVr42qblB82rULRQ5HnjcFu3aNaJw4LuIMWby3HPNVRQrSH3CCbF76mXlT38yP2o87rvPxFy9\nunB6QYGlxxoOGAzP/Plnu5esrML5+fl2brAESXa2BVTjsX27WUxgft9ks2SJ1R0MK47Fl19qscM7\nc3Is6JqOJSDKQ+A6evbZwul//avFT2Lx0Ue6c2hoJE2a2LNPBn/4g1nKwfeZn2+/gXPOKf68ffax\neCKovvJKcmSJR2Dp/PCDDStu377k579jh43Oi4xzLligO913LVtaHClV4JZF6nn6aVujr7jtIHr0\ngNEHvMb6HY1Y+shkOPtsyxg7lpwP/0fr5hHbg23dat2wli2L1NOtm62IumJF0WssWWKrkyeLrCxb\nKC3eQnc//ACNGkHz5oXTRcwKinXeK69Yj7hNG+uZltRr7d7dFtGNR61atpYiFN9zKyt77WW7wn7+\nefwyQV4sywLse7zggtirxldmirMsYlkVYL8HKLyYYH6+LZoY/TspK0cfbT3tH0KbK8+cCevWxbc+\nA7p1g8WL7XNFWBYA771n3oZhw0p+/jVqmLMhcjPJDh2srttvt//94MGpkzlRXFkUw623wuWXw7//\nDb/9VjgvJ8dM4LPOsoddHO2vOhWAJR36hxNPPJGlBVm0WfgRzJ1r/8TRo21J8RgcHNpUNtoVpZoa\nZaFqy1zHYvFiWxE91p+gdu3YymLzZnOngDU40W6o4lwc8Tj7bNh/fzjllMTPSRQRUwJxHgdgyqJN\nG/u+MomGDe09Wlls2hRWJNHEckOtW2fvyVQWYBs7gu3jBXDMMcWfF/x3dtutfLsFJ8KBB9p/4JZb\nzE06fHjZ6xo2zJRtnTrm6k43rizioGpLJt9/P5x0ksUWrrjC0gGee84+n3VWMZUsXQpr19Ju31qA\nNeoBW/doxxpa0nrpdPuFNWhgGyvEoUsXe//228Lpq1ebb719+9LfYzyCxi9e3OKHH2CffWLn1a4d\nO2axfbv96MFuNT+/cLmyKIvf/Q7+9z9o2jTxc0rD4YfbnhCrVsXO//zz+FZFVaZ+fVOW0R2k0loW\nweaMyVIW++9vcZogbvHBB6YIYhjihejWzd4PPTT1Vl7durY3x8qVFmc58MCy1zV0qL0fe2xYgacT\nVxZxWL/eGrjbb7ftpE8/3dauv/pqUxJPP21x6HiN5s5uRZ8+tG61gxo1Cm9Gk5Nj723GjLTdY267\nDfbdN648jRpZdrRlESigZFsWEFtZ7Nhh9xHvvmO5oVRNMQSB3KDBibQucnML51UGAkUQyxW1fLlt\n0pOJykLEFHp5LYtkKwsROOoosyw2bTKrr3//Ek/baVn06pUcOUoicEUl4oIqjr32gnHjzMNRGaiV\nbgEqK0Fvsm1bM3P79bM/yl13WQO9aJFtIxmXRx+1oVDPPUftejVp06awZREoi9a920K/xIaKdOtW\nVFkECiiZyiJwF8VSFsuXW8O/996xz43lhgo2homlLAKroCyWRarp3t1k/vzzovGTQIH83/9VvFwV\nQSxlUZxlUbeudRRSaVmAuaImToTHH7ffWSLKYs89LX7Qo8SNQ5NDnz7WmUxGLG3kyPLXkSzcsojD\nL7/YexB0ErEdwc48E1591f40Q4YUU8Hjj1tXZsQIwBrzSGWxdKm9t2mTuEwHH2wuoMg/ZCosixYt\nrJGMpSyC4GJxbqhoZRG4mwI3VCzLIvi8cxhxJaBePTjiCHM5rl9fOO/TTy0/cHFkGg0bls6yALMu\nUmlZgFkWYBZ/8HwSoV+/sKss1ZxxhsX1OnSomOtVFK4s4hBYFrvtFk6rUQOefNLGzY8eXcwfZ94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LyI1ABWAHup6sHAFcCLItIo+mRVHa+qPVS1R8tC29yVg7fe8n0sykmsmEU8r55bFo5TNUil\nslgGtIk4bh1Ki+RPwCsAqvo5UA/bO2Obqv4aSp8J/ADsl0JZwyxb5iOhyklpLQtXFo5T+UmlspgB\ndBCR9iJSBxgGvB1V5mfgGAAR6YQpi9Ui0jIUIEdE9gY6AItTKGsYVxblJtGYBcAee9jLcZzKTcqi\nuKqaLyKjgPeBmsBTqjpXRMYA2ar6NnAl8LiIXI4Fu89WVRWRvsAYEdkOFAAXqOraVMm6k/x8+PVX\nb73KSaLLfQA8/zzUrFkxcjmOU3ZSOuRHVd/BAteRaTdGfJ4H9I5x3uvA66mULSZbtkCzZvZyykyi\ny32A62XHqSr4+NBIGjY0y8IpF6WxLBzHqRqkezSUk4FExixKsiwcx6kauLKI5Icf4NRTITs73ZJU\naWJZFq4sHKdq48oikpUr4Y033BVVTmLFLNwN5ThVG1cWkeTm2rsP/C8XpRk66zhO1cCVRSSbN9u7\nK4tyUbs2FBTAjh1uWThOpuDKIhK3LJJCYEVs3+6WheNkCq4sIqlVy/axCPaSdMpELGXhi/g6TtXG\nlUUkQ4fC0qXQqlW6JanSBC6n7dvNDVW7tq1e6jhO1cWVhZN0oi0Lj1c4TtXHlUUkjz8OAwemW4oq\nT6As8vLCloXjOFUbVxaRzJ0L06alW4oqT7Rl4crCcao+riwi2bzZR0IlgeiYhbuhHKfq48oiElcW\nScEtC8fJPFxZRLJ5s28InQSiYxZuWThO1cdHv0eSleWWRRJwy8JxMg9XFpE88ki6JcgIImMWPnTW\ncTIDd0M5SSfSsvChs46TGbiyiOT3v4dbbkm3FFWeyJiFWxaOkxm4GyqSL7+E3XZLtxRVHrcsHCfz\ncMsiktxcHw2VBKJjFq4sHKfq48oiQNXnWSQJHzrrOJmHK4uAvDzbrceVRbnxobOOk3m4sgjYvh36\n9IH27dMtSZXHl/twnMzDA9wBDRr4IoJJwi0Lx8k83LJwko4PnXWczMOVRcCcOdCxI3z8cbolqfL4\n0FnHyTxcWQSsWwfz50N+frolqfL4ch+Ok3m4sgjYvNnefTRUuXHLwnEyD1cWAbm59u6T8spNrdCw\niSBm4crCcao+riwC3LJIGiKmMHzorONkDq4sAnbfHY4/Hpo0SbckGUGdOrBli312y8Jxqj4pVRYi\ncryIzBeRRSJyTYz8vURkqoh8IyKzReSEiLxrQ+fNF5HfpVJOAI47Dt59F1q0SPmlqgO1a4eNNbcs\nHKfqk7JJeSJSExgL9AdygBki8raqzosodgPwiqo+KiKdgXeAdqHPw4ADgD2BD0VkP1XdkSp5neQS\nqSzcsnCcqk8qLYuewCJVXayqecBEYFBUGQUahT43BpaHPg8CJqrqNlX9EVgUqi91jBkD++6b0ktU\nJ2rXDo8ZcMvCcao+qVQWWcDSiOOcUFoko4ERIpKDWRWXlOJcRGSkiGSLSPbq1avLJ+3q1bB2bfnq\ncHZSp45bFo6TSaQ7wD0ceEZVWwMnAM+LSMIyqep4Ve2hqj1atmxZPkl8efKk4jELx8ksUrmQ4DKg\nTcRx61BaJH8CjgdQ1c9FpB7QIsFzk8vmzT7HIolEuqHcsnCcqk8qLYsZQAcRaS8idbCA9dtRZX4G\njgEQkU5APWB1qNwwEakrIu2BDsBXKZTVLYsk424ox8ksUmZZqGq+iIwC3gdqAk+p6lwRGQNkq+rb\nwJXA4yJyORbsPltVFZgrIq8A84B84OKUj4Tq0wc2bUrpJaoT7oZynMwipftZqOo7WOA6Mu3GiM/z\ngN5xzr0NuC2V8hXi6qsr7FLVAR866ziZRboD3E6G4kNnHSezcGUR0KkTXHBBuqXIGOrUsbWhwC0L\nx8kEXFkE+ByLpBKpINyycJyqjyuLAB8NlVQilYVbFo5T9XFlAaBqDnZXFknDLQvHySxcWQBs3WoK\nwyflJY1IBeGWheNUfVxZgCmKCy+E7t3TLUnG4G4ox8ksUjrPosqwyy7wyCPpliKjcDeU42QWblkA\nFBRAfn66pcgo3LJwnMzCLQuAmTOhZ0+YPBlOOind0mQEkdaEWxaZz/bt28nJyWHr1q3pFsWJQ716\n9WjdujW1y9h7c2UB4XUpPMCdNNyyqF7k5OTQsGFD2rVrh4ikWxwnClXl119/JScnh/bt25epDndD\nQXhdCh86mzQ8ZlG92Lp1K82bN3dFUUkREZo3b14uy8+VBYQtC1cWScMti+qHK4rKTXmfjysLcGWR\nAiKtiVru7HScKo8rC4ADDoCrroJmzdItScYQWBO1a4N3OJ1U8+uvv9KtWze6devGHnvsQVZW1s7j\nvLy8hOo455xzmD9/frFlxo4dy4QJE5IhcpXD+3wAhx5qLydpBMrC4xVORdC8eXO+/fZbAEaPHk2D\nBg246qqrCpVRVVSVGjVi95GffvrpEq9z8cUXl1/YKopbFmA75G3YkG4pMopASXi8oppy1FFFX8HE\n19zc2PnPPGP5a9YUzSsjixYtonPnzpxxxhkccMABrFixgpEjR9KjRw8OOOAAxowZs7PsEUccwbff\nfkt+fj5NmjThmmuuoWvXrhx++OH88ssvANxwww3cf//9O8tfc8019OzZk/3335/p06cDsHnzZk49\n9VQ6d+7MkCFD6NGjx+TEMSEAABBGSURBVE5FFslNN93EoYceyoEHHsgFF1yAbRIKCxYsoF+/fnTt\n2pVDDjmEJUuWAHD77bdz0EEH0bVrV66//voyfydlxZUFwJgx0KpVuqXIKCLdUI6TTv73v/9x+eWX\nM2/ePLKysrjjjjvIzs5m1qxZfPDBB8ybN6/IORs2bODII49k1qxZHH744Tz11FMx61ZVvvrqK+66\n666diuehhx5ijz32YN68efz973/nm2++iXnupZdeyowZM/juu+/YsGED7733HgDDhw/n8ssvZ9as\nWUyfPp3ddtuNyZMn8+677/LVV18xa9YsrrzyyiR9O4njbijw5clTgLuhqjkffxw/b5ddis9v0aL4\n/FKyzz770KNHj53HL730Ek8++ST5+fksX76cefPm0blz50Ln1K9fnwEDBgDQvXt3Pvnkk5h1n3LK\nKTvLBBbAp59+ytWhbZq7du3KAQccEPPcKVOmcNddd7F161bWrFlD9+7d6dWrF2vWrGHgwIGATaQD\n+PDDDzn33HOpX78+AM3SEF91ZQGuLFKAWxZOZWHXiP/2woULeeCBB/jqq69o0qQJI0aMiDn3oE5E\nL6dmzZrkx1kOqG7duiWWiUVubi6jRo3i66+/JisrixtuuKHSz353NxSYsvDZ20kl+K+5ZeFUJjZu\n3EjDhg1p1KgRK1as4P3330/6NXr37s0rr7wCwHfffRfTzbVlyxZq1KhBixYt+O2333j99dcBaNq0\nKS1btmTy5MmATXbMzc2lf//+PPXUU2zZsgWAtWnY2dMtC3DLIgW4ZeFURg455BA6d+5Mx44dadu2\nLb179076NS655BLOPPNMOnfuvPPVuHHjQmWaN2/OWWedRefOnWnVqhWHHXbYzrwJEyZw/vnnc/31\n11OnTh1ef/11TjrpJGbNmkWPHj2oXbs2AwcO5JZbbkm67MUhQQS+qtOjRw/Nzs4u28kTJ8KWLXDO\nOckVqhozeTKcfDIcfDB8/XW6pXFSzffff0+nTp3SLUalID8/n/z8fOrVq8fChQs57rjjWLhwIbUq\nwezUWM9JRGaqao84p+wk/dJXBoYNS7cEGYdbFk51ZdOmTRxzzDHk5+ejqowbN65SKIryUvXvIBn8\n9BM0bOgzuJOIxyyc6kqTJk2YOXNmusVIOh7gBujbFy6/PN1SZBRuWThOZuHKAjzAnQJcWThOZuHK\nAlxZpACflOc4mYUri4IC2LrVlUWS8bWhHCezcGXhu+SlBLcsnIrk6KOPLjLB7v777+fCCy8s9rwG\nDRoAsHz5coYMGRKzzFFHHUVJw/Lvv/9+coO2BDjhhBNYv359IqJXGVxZ1KoFY8fCscemW5KMwmMW\nTkUyfPhwJk6cWCht4sSJDB8+PKHz99xzT1577bUyXz9aWbzzzjs0adKkzPVVRlI6dFZEjgceAGoC\nT6jqHVH59wFHhw53AXZT1SahvB3Ad6G8n1X15JQIWa8eXHRRSqquzvjQ2erLZZdBjBW5y0W3bhBa\nGTwmQ4YM4YYbbiAvL486deqwZMkSli9fTp8+fdi0aRODBg1i3bp1bN++nVtvvZVBgwYVOn/JkiWc\ndNJJzJkzhy1btnDOOecwa9YsOnbsuHOJDYALL7yQGTNmsGXLFoYMGcLNN9/Mgw8+yPLlyzn66KNp\n0aIFU6dOpV27dmRnZ9OiRQvuvffenavWnnfeeVx22WUsWbKEAQMGcMQRRzB9+nSysrJ46623di4U\nGDB58mRuvfVW8vLyaN68ORMmTGD33Xdn06ZNXHLJJWRnZyMi3HTTTZx66qm89957XHfddezYsYMW\nLVowZcqUpD2DlCkLEakJjAX6AznADBF5W1V3LpSiqpdHlL8EODiiii2q2i1V8jmpxS0LpyJp1qwZ\nPXv25N1332XQoEFMnDiRoUOHIiLUq1ePSZMm0ahRI9asWUOvXr04+eST4+5J/eijj7LLLrvw/fff\nM3v2bA455JCdebfddhvNmjVjx44dHHPMMcyePZu//OUv3HvvvUydOpUWLVoUqmvmzJk8/fTTfPnl\nl6gqhx12GEceeSRNmzZl4cKFvPTSSzz++OMMHTqU119/nREjRhQ6/4gjjuCLL75ARHjiiSe48847\nueeee7jlllto3Lgx331n/el169axevVq/vznPzNt2jTat2+f9PWjUmlZ9AQWqepiABGZCAwCiq6q\nZQwHbkqhPE4F4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uhloJSiIQpCjMA9COi3kTUFMDpACbFlHkNYiWAiDpB3EmLQmyT4kGspeDlPkrkOgLi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\nRFBRUBRFUSKoKCiKoigR/j8ihywSLXNoUwAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"9_0-Nfkrtlc0","colab_type":"code","outputId":"931d2d79-485e-4b73-9e0b-175e7b93343a","executionInfo":{"status":"ok","timestamp":1567510278037,"user_tz":-120,"elapsed":7167941,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["test_lost, test_acc= modelFT.evaluate_generator(test_generator)\n","print (\"Test Accuracy:\", test_acc)"],"execution_count":25,"outputs":[{"output_type":"stream","text":["Test Accuracy: 0.939\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"Jk6mBLCiHr2M","colab_type":"code","outputId":"6e8c7d14-4507-4b49-910d-c7e5d04a8d23","executionInfo":{"status":"ok","timestamp":1567510279011,"user_tz":-120,"elapsed":7168908,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["\n","accDA      = historyDA.history[     'acc' ]\n","val_accDA  = historyDA.history[ 'val_acc' ]\n","\n","accFE      = historyFE.history[     'acc' ]\n","val_accFE  = historyFE.history[ 'val_acc' ]\n","\n","accFT      = historyFT.history[     'acc' ]\n","val_accFT  = historyFT.history[ 'val_acc' ]\n","\n","epochs    = range(1,len(accDA)+1,1) \n","\n","plt.figure(figsize=(10,18))\n","\n","plt.plot  ( epochs,     accFT, 'k', label='Fine Tuning - Training acc '  )\n","plt.plot  ( epochs, val_accFT,  'b', label='Fine Tuning - Validation acc ')\n","\n","plt.plot  ( epochs,     accFE, 'r--', label='Feature Extraction - Training acc'  )\n","plt.plot  ( epochs, val_accFE,  'm--', label='Feature Extraction - Validation acc')\n","\n","plt.plot  ( epochs,     accDA, 'g:', label='Data Augmentation - Training acc'  )\n","plt.plot  ( epochs, val_accDA,  'c:', label='Data Augmentation - Validation acc')\n","\n","plt.title ('Training and validation accuracy')\n","plt.ylabel('acc')\n","plt.ylim(0.5,1)\n","plt.xlabel('epochs')\n","\n","\n","plt.legend()\n","plt.figure()\n","\n","\n","\n"],"execution_count":26,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]},"execution_count":26},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAmQAAAQPCAYAAAC+8vcfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n9jboudOKjo4mU1NTmjVrlso+Nzc3Mjc3p1OnThns/AkJCdSqVSvq3r17pmV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bS0WLFqWB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1GrVrlzLk7IWKYWLpTvgC1bEsnCwoImTZpEcXGyGd3MTA4c1aeNGzcSAJqlJaM6fZq0ji1q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PFWBob8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\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CFBQwQdaexkbg3/8GNmwAnn0WePnlNsE2bRrbv6LC9nhHj7a9he5iiFHUD7AbWUtLm56l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U2uX9wJVDKBV6YsYeXYRV3b4r29bXqRXZF1BRuu2kCgdyBeMhkJ3t49yohXRUezbdo0t08V+GtR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\nIIuIiIho7G+dn0Lpd52/qgAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 720x1296 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"eEr3A3-e3bKZ","colab_type":"code","outputId":"434758a5-bb8c-4207-b916-291df45c29d1","executionInfo":{"status":"ok","timestamp":1567510308008,"user_tz":-120,"elapsed":7197899,"user":{"displayName":"Jordi Torres","photoUrl":"https://lh3.googleusercontent.com/a-/AAuE7mDkD6udBQxc1Cx-zMrYPf0xjtQYxGjQEpB40wVHTg=s64","userId":"14559872433417615139"}},"colab":{"resources":{"http://localhost:8080/nbextensions/google.colab/files.js":{"data":"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numpy as np\n","\n","from google.colab import files\n","from keras.preprocessing import image\n","\n","uploaded=files.upload()\n","\n","for fn in uploaded.keys():\n"," \n","  # predicting images\n","  path='/content/' + fn\n","  img=image.load_img(path, target_size=(150, 150))\n","  \n","  x=image.img_to_array(img)\n","  x=np.expand_dims(x, axis=0)\n","  images = np.vstack([x])\n","  \n","  classes = modelFT.predict(images, batch_size=10)\n","  \n","  print(classes[0])\n","  \n","  plt.imshow(img)  \n","  plt.show()\n","  \n","  if classes[0]>0:\n","    print( fn + \" IS A DOG\")\n","    \n","  else:\n","    print( fn + \" IS A CAT\")\n","\n","\n","\n"],"execution_count":27,"outputs":[{"output_type":"stream","text":["Using TensorFlow backend.\n"],"name":"stderr"},{"output_type":"display_data","data":{"text/html":["\n","     <input type=\"file\" id=\"files-5d9c144b-d8f8-49e4-bcc9-7b747af4bb1f\" name=\"files[]\" multiple disabled />\n","     <output id=\"result-5d9c144b-d8f8-49e4-bcc9-7b747af4bb1f\">\n","      Upload widget is only available when the cell has been executed in the\n","      current browser session. Please rerun this cell to enable.\n","      </output>\n","      <script src=\"/nbextensions/google.colab/files.js\"></script> "],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Saving Wiliams-foto1.jpg to Wiliams-foto1 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cV7fzJmGJ4z7/XbOpV6QBlAUpP5ghMb3nyZm4pnnnmG97///QAMBv8L3/aeb/V3FMuMw6+W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\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s2AlXz/OQi5Re28ew8Rh2OOowK+TIjZAxg2zzB4CQR2jTFZiiWivzAgpvha3xEKyTcJ5V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\n21jPNovCxja2sZ79v5h+r27NRc2vAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Wiliams-foto1.jpg IS A CAT\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"Wq2e87drWlun","colab_type":"text"},"source":["Antes de pasar al siguiente capítulo, ejecutar el siguiente código para terminar el proceso y liberar los recursos."]},{"cell_type":"code","metadata":{"id":"XSxsHIDvtlaC","colab_type":"code","colab":{}},"source":["import os, signal\n","\n","os.kill( os.getpid() , \n","         signal.SIGKILL\n","       )\n"],"execution_count":0,"outputs":[]}]}