Image_Detection_Flowers17.ipynb

{"cells":[{"cell_type":"markdown","source":["# Submission details\n","## Name: Callum Freeburn\n","## Model: VGG16\n","\n","Note: I could not pass variables into shell commands, tried for hours but could not get it to work so hard coded when needed."],"metadata":{"id":"IEiiQe87Rfgh"}},{"cell_type":"markdown","metadata":{"id":"D6M3Sk-GtzhB"},"source":["# Import Libraries & Mount to Google Drive"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":11716,"status":"ok","timestamp":1652421196145,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"ght31gXYcqCG","outputId":"856d4c50-545f-4a60-908a-329055203699"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting wget\n","  Downloading wget-3.2.zip (10 kB)\n","Building wheels for collected packages: wget\n","  Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for wget: filename=wget-3.2-py3-none-any.whl size=9675 sha256=4390ff9917f01bfcbaad716deb303629b84b08c6bb764635c51e76576c8c0ba8\n","  Stored in directory: /root/.cache/pip/wheels/a1/b6/7c/0e63e34eb06634181c63adacca38b79ff8f35c37e3c13e3c02\n","Successfully built wget\n","Installing collected packages: wget\n","Successfully installed wget-3.2\n"]}],"source":["import numpy as np\n","import pandas as pd\n","import os \n","import tarfile\n","from PIL import Image \n","import random\n","!pip install wget\n","import wget\n","import cv2\n","import tensorflow as tf\n","import keras\n","import shutil\n","import matplotlib.pyplot as plt\n","\n","# for Models\n","from keras.preprocessing.image import ImageDataGenerator\n","from keras import applications\n","from keras.models import Sequential\n","from keras.layers import Conv2D, MaxPooling2D\n","from keras.layers import Activation, Dropout, Flatten, Dense\n","from keras.applications.vgg16 import preprocess_input, VGG16, decode_predictions\n","from keras.callbacks import ModelCheckpoint\n","from keras import optimizers\n","from keras.models import Sequential, Model\n","from keras.callbacks import CSVLogger\n","from keras.preprocessing import image\n","from sklearn.metrics import classification_report\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":20639,"status":"ok","timestamp":1652421216781,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"f3kM1B-ubg_Z","outputId":"00985d2c-ee6c-4265-bbd0-e7d0120cd40d"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"markdown","metadata":{"id":"vMgfx-ckuCmx"},"source":["# Flowers17 Data Preparation\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"xg9T3svNbswm","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421221907,"user_tz":-600,"elapsed":436,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"2d4e3b60-a181-4897-ad69-e836650430db"},"outputs":[{"output_type":"stream","name":"stdout","text":["Flowers17_Data folder created\n"]}],"source":["# create Flowers17 folder for data \n","dataset_dir = '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data'\n","tgz_filename = \"17flowers.tgz\"\n","download_url = 'http://www.robots.ox.ac.uk/~vgg/data/flowers/17/17flowers.tgz'\n","filepath = os.path.join(dataset_dir, tgz_filename)\n","\n","if not os.path.exists(dataset_dir):\n","  os.mkdir(dataset_dir)\n","  print(\"Flowers17_Data folder created\")"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"BJmS_P48iAg3","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421309068,"user_tz":-600,"elapsed":11764,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"b8ec5f76-b97d-4046-924b-909fbf2b0460"},"outputs":[{"output_type":"stream","name":"stdout","text":["file extracted\n"]}],"source":["# if tgz file containing has not been downloaded, download the file and extract it\n","extractedfilepath = '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/'\n","if not os.path.exists(filepath):\n","  wget.download(download_url, dataset_dir) \n","if os.path.exists(filepath):\n","  tar = tarfile.open(filepath)\n","  tar.extractall(extractedfilepath)\n","  tar.close()\n","  print('file extracted')"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":578},"executionInfo":{"elapsed":976,"status":"ok","timestamp":1652421312637,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"em076DiEg723","outputId":"c08ca1ce-f65f-4ab3-ecfc-ef43acba275f"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=500x561 at 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\n"},"metadata":{},"execution_count":7}],"source":["# display random image from flowers17 dataset to show that it has worked\n","random_flower = random.choice(os.listdir(extractedfilepath + \"/jpg/\"))\n","Image.open(extractedfilepath + \"/jpg/\" + random_flower)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"F5tkJkt9-sGq","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421370805,"user_tz":-600,"elapsed":437,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"7c5a4509-bf38-498c-e332-8c4f045f1efe"},"outputs":[{"output_type":"stream","name":"stdout","text":["All datasplit and class folders created\n"]}],"source":["# create folders for train, validation and test and then create a folder for each of the 17 classes within the dataset split folders\n","os.mkdir(r'/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/train')\n","os.mkdir(r'/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/validation')\n","os.mkdir(r'/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/test')\n","\n","for i in range(1, 18):\n","    os.mkdir(r'/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/train/' + str(i))\n","    os.mkdir(r'/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/validation/' + str(i))\n","    os.mkdir(r'/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/test/' + str(i))\n","print('All datasplit and class folders created')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"pHnvWC8MPTvE"},"outputs":[],"source":["# As the images are sorted in 80 image sections, meaning each 80 images represnt a class, this function read the split test file and places each image into its repected class folder within the split folder e.g (training)\n","def sort_flower_images(setType, setTxtFile):\n","  with open(extractedfilepath + setTxtFile, \"r\") as f:\n","    datafile = f.readlines()\n","\n","    for i in range(1, 1361):\n","\n","          findImage = \"image_\" +  str(i).zfill(4) + \".jpg\"\n","          for line in datafile:\n","            if findImage in line:\n","              imageNumber = int(findImage.replace('image_', '').replace('.jpg', ''))\n","              jpgorginalloc = '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/jpg/' + findImage\n","              newlocationbase = '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/'\n","\n","              if imageNumber <= 80:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/1/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 1')\n","\n","              elif imageNumber >= 81 and imageNumber <= 160:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/2/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 2') \n","\n","              elif imageNumber >= 161 and imageNumber <= 240:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/3/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 3')\n","\n","              elif imageNumber >= 241 and imageNumber <= 320:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/4/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 4')\n","\n","              elif imageNumber >= 321 and imageNumber <= 400:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/5/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 5')\n","\n","              elif imageNumber >= 401 and imageNumber <= 480:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/6/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 6')\n","\n","              elif imageNumber >= 481 and imageNumber <= 560:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/7/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 7')\n","\n","              elif imageNumber >= 561 and imageNumber <= 640:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/8/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 8')\n","\n","              elif imageNumber >= 641 and imageNumber <= 780:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/9/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 9') \n","\n","              elif imageNumber >= 781 and imageNumber <= 860:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/10/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 10') \n","\n","              elif imageNumber >= 861 and imageNumber <= 940:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/11/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 11')\n","\n","              elif imageNumber >= 941 and imageNumber <= 1020:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/12/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 12') \n","\n","              elif imageNumber >= 1021 and imageNumber <= 1100:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/13/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 13')\n","\n","              elif imageNumber >= 1101 and imageNumber <= 1180:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/14/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 14')\n","\n","              elif imageNumber >= 1181 and imageNumber <= 1260:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/15/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 15')\n","\n","              elif imageNumber >= 1261 and imageNumber <= 1340:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/16/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 16')\n","\n","              elif imageNumber >= 1341  and imageNumber <= 1361:\n","                shutil.copy(jpgorginalloc, newlocationbase + setType + '/17/' + findImage)\n","                # print('Inserted ' + findImage + 'into class 17')    \n","\n","              else:\n","                print('could not find number')\n","                pass\n","\n","  print('Sucessfully sorted all images from ' + setTxtFile)\n","  pass\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":11601,"status":"ok","timestamp":1652421519704,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"qEj0WBFISd__","outputId":"2c51674a-c646-43bf-bb68-f7074e03e304"},"outputs":[{"output_type":"stream","name":"stdout","text":["/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data\n","Sucessfully sorted all images from TrainSet1.txt\n","Sucessfully sorted all images from ValSet1.txt\n","Sucessfully sorted all images from TestSet1.txt\n"]}],"source":["# Using TrainSet1, ValSet1 and TestSet1 - Please import into Flowers17_Data dir as unable to automate download\n","# call the function above for the respected txt files\n","%cd '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data'\n","sort_flower_images('train', 'TrainSet1.txt')\n","sort_flower_images('validation', 'ValSet1.txt')\n","sort_flower_images('test', 'TestSet1.txt')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"mNW9G_NUD1ql","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421524805,"user_tz":-600,"elapsed":338,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"b35de8f0-24eb-4613-efc4-1abdcf0e0233"},"outputs":[{"output_type":"stream","name":"stdout","text":["created class dict\n"]}],"source":["# create a dict to give the class folders the correct names\n","correct_class_dict = {}\n","correct_class_dict['1'] = 'Daffodil'\n","correct_class_dict['2'] = 'Snowdrop'\n","correct_class_dict['3'] = 'LilyValley'\n","correct_class_dict['4'] = 'Bluebell'\n","correct_class_dict['5'] = 'Crocus'\n","correct_class_dict['6'] = 'Iris'\n","correct_class_dict['7'] = 'Tigerlily'\n","correct_class_dict['8'] = 'Tulip'\n","correct_class_dict['9'] = 'Fritillary'\n","correct_class_dict['10'] = 'Sunflower'\n","correct_class_dict['11'] = 'Daisy'\n","correct_class_dict['12'] = 'ColtsFoot'\n","correct_class_dict['13'] = 'Dandelion'\n","correct_class_dict['14'] = 'Cowslip'\n","correct_class_dict['15'] = 'Buttercup'\n","correct_class_dict['16'] = 'Windflower'\n","correct_class_dict['17'] = 'Pansy'\n","\n","print('created class dict')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"J3hVi-noFZrF","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421567674,"user_tz":-600,"elapsed":255,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"e68195b1-3d3c-40a4-b138-1e4b649c7334"},"outputs":[{"output_type":"stream","name":"stdout","text":["Successfuly renamed class folders\n"]}],"source":["# loop through dict to rename the folders\n","\n","for i in range(1, 18):\n","    os.rename('/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/train/' + str(i), '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/train/' + correct_class_dict[str(i)])\n","    os.rename('/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/validation/' + str(i), '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/validation/' + correct_class_dict[str(i)])\n","    os.rename('/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/test/' + str(i), '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/test/' + correct_class_dict[str(i)])\n","print('Successfuly renamed class folders')"]},{"cell_type":"markdown","metadata":{"id":"eaCQ-CjduNRF"},"source":["# Data Augmentation\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"WihqGA5k4rYE","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421643288,"user_tz":-600,"elapsed":458,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"b0edf416-483b-4099-df7b-1b9fcca2ae33"},"outputs":[{"output_type":"stream","name":"stdout","text":["created dir variables for data augmentation\n"]}],"source":["# create varibles for datasplit folders\n","train_images_dir = '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/train'\n","validation_images_dir = '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/validation'\n","test_images_dir = '/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/test'\n","print('created dir variables for data augmentation')"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":15990,"status":"ok","timestamp":1652226656728,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"iDwhNGpntXSn","outputId":"5c656d5e-ce5c-468f-dba8-28ff28a6ddd9"},"outputs":[{"output_type":"stream","name":"stdout","text":["Found 680 images belonging to 17 classes.\n","Found 340 images belonging to 17 classes.\n","Found 340 images belonging to 17 classes.\n"]}],"source":["# create Data augmentation and image generator for flowers17 dataset\n","# normalize as well as create a larger dataset\n","train_datagen = ImageDataGenerator(rescale=1./255,\n","      rotation_range=180,\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","      vertical_flip=True,\n","      fill_mode='nearest') \n","\n","# normalize the data\n","validation_datagen = ImageDataGenerator(rescale=1./255)\n","test_datagen = ImageDataGenerator(rescale=1./255)\n","\n","train_generator = train_datagen.flow_from_directory(\n","    train_images_dir,\n","    target_size=(224, 224),\n","    batch_size=20,\n","    class_mode='categorical')\n","\n","validation_generator = train_datagen.flow_from_directory(\n","    validation_images_dir, # same directory as training data\n","    target_size=(224, 224),\n","    batch_size=10,\n","    class_mode='categorical',\n","    shuffle=False)\n","\n","test_generator = test_datagen.flow_from_directory(\n","    test_images_dir, \n","    target_size=(224, 224),\n","    batch_size=1,\n","    class_mode='categorical',\n","    shuffle=False)"]},{"cell_type":"markdown","metadata":{"id":"4eWYg-KBtsd9"},"source":["# Baseline VGG16 Model"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1073,"status":"ok","timestamp":1652317546659,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"zM9wjgO5tr2F","outputId":"3ac4ffeb-5e50-4b44-d41a-61a2a4d85277"},"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n","58892288/58889256 [==============================] - 0s 0us/step\n","58900480/58889256 [==============================] - 0s 0us/step\n","Model: \"vgg16\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," input_1 (InputLayer)        [(None, None, None, 3)]   0         \n","                                                                 \n"," block1_conv1 (Conv2D)       (None, None, None, 64)    1792      \n","                                                                 \n"," block1_conv2 (Conv2D)       (None, None, None, 64)    36928     \n","                                                                 \n"," block1_pool (MaxPooling2D)  (None, None, None, 64)    0         \n","                                                                 \n"," block2_conv1 (Conv2D)       (None, None, None, 128)   73856     \n","                                                                 \n"," block2_conv2 (Conv2D)       (None, None, None, 128)   147584    \n","                                                                 \n"," block2_pool (MaxPooling2D)  (None, None, None, 128)   0         \n","                                                                 \n"," block3_conv1 (Conv2D)       (None, None, None, 256)   295168    \n","                                                                 \n"," block3_conv2 (Conv2D)       (None, None, None, 256)   590080    \n","                                                                 \n"," block3_conv3 (Conv2D)       (None, None, None, 256)   590080    \n","                                                                 \n"," block3_pool (MaxPooling2D)  (None, None, None, 256)   0         \n","                                                                 \n"," block4_conv1 (Conv2D)       (None, None, None, 512)   1180160   \n","                                                                 \n"," block4_conv2 (Conv2D)       (None, None, None, 512)   2359808   \n","                                                                 \n"," block4_conv3 (Conv2D)       (None, None, None, 512)   2359808   \n","                                                                 \n"," block4_pool (MaxPooling2D)  (None, None, None, 512)   0         \n","                                                                 \n"," block5_conv1 (Conv2D)       (None, None, None, 512)   2359808   \n","                                                                 \n"," block5_conv2 (Conv2D)       (None, None, None, 512)   2359808   \n","                                                                 \n"," block5_conv3 (Conv2D)       (None, None, None, 512)   2359808   \n","                                                                 \n"," block5_pool (MaxPooling2D)  (None, None, None, 512)   0         \n","                                                                 \n"," global_average_pooling2d (G  (None, 512)              0         \n"," lobalAveragePooling2D)                                          \n","                                                                 \n","=================================================================\n","Total params: 14,714,688\n","Trainable params: 0\n","Non-trainable params: 14,714,688\n","_________________________________________________________________\n","Model: \"sequential\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," vgg16 (Functional)          (None, 512)               14714688  \n","                                                                 \n"," dense (Dense)               (None, 17)                8721      \n","                                                                 \n","=================================================================\n","Total params: 14,723,409\n","Trainable params: 8,721\n","Non-trainable params: 14,714,688\n","_________________________________________________________________\n"]}],"source":["# #baseline pretained VGG16 model\n","VGG16_base = VGG16(weights= \"imagenet\" , include_top=False, pooling='avg')\n","VGG16_base.trainable = False\n","VGG16_base.summary()\n","\n","# add VGG16 base and output layer\n","baseline_VGG16_model = Sequential()\n","baseline_VGG16_model.add(VGG16_base)\n","baseline_VGG16_model.add(Dense(17, activation='softmax'))\n","\n","# model summary\n","baseline_VGG16_model.summary()"]},{"cell_type":"code","source":["tf.keras.utils.plot_model(\n","    baseline_VGG16_model,\n","    to_file='model.png',\n","    show_shapes=True,\n","    show_dtype=True,\n","    show_layer_names=True,\n","    rankdir='TB',\n","    expand_nested=False,\n","    dpi=96,\n","    layer_range=None,\n","    show_layer_activations=True\n",")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":404},"id":"LvweIkwD5jl4","executionInfo":{"status":"ok","timestamp":1652319255262,"user_tz":-600,"elapsed":3,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"7fa30ebe-8192-4c3d-b5ea-9b5d582ca9e2"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<IPython.core.display.Image object>"],"image/png":"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\n"},"metadata":{},"execution_count":5}]},{"cell_type":"code","source":["# if we need to load model from dir\n","baseline_load_model_dir ='/content/drive/My Drive/42028/Assignment2/Image_Detection/flowers17_baseline_VGG16_model_checkpoints'\n","baseline_VGG16_model = tf.keras.models.load_model(baseline_load_model_dir + '/VGG16_baseline_model.hdf5')\n","baseline_VGG16_model.summary()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-Fh5IbWNwIZS","executionInfo":{"status":"ok","timestamp":1652226664505,"user_tz":-600,"elapsed":7824,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"0c3f4660-9f11-4e73-9438-9beb59285e5e"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"sequential_1\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," vgg16 (Functional)          (None, 512)               14714688  \n","                                                                 \n"," dense_1 (Dense)             (None, 17)                8721      \n","                                                                 \n","=================================================================\n","Total params: 14,723,409\n","Trainable params: 8,721\n","Non-trainable params: 14,714,688\n","_________________________________________________________________\n"]}]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":11,"status":"ok","timestamp":1652226664505,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"pgWzhgJEubd0","outputId":"bdd7b93a-e162-4e77-c50c-31cd72994fc4"},"outputs":[{"output_type":"stream","name":"stdout","text":["WARNING:tensorflow:`period` argument is deprecated. Please use `save_freq` to specify the frequency in number of batches seen.\n"]}],"source":["# configure model to create checkpoint every epoch\n","filepath_of_weights= baseline_load_model_dir + '/weights.{epoch:02d}-{val_loss:.2f}.hdf5'\n","checkpoint = keras.callbacks.ModelCheckpoint(filepath_of_weights, monitor='val_loss', verbose=0, save_best_only=False, save_weights_only=False, mode='auto', period=1)"]},{"cell_type":"code","source":["# configure model to append to csv file every epoch for history\n","baseline_model_history_dir = '/content/drive/My Drive/42028/Assignment2/Image_Detection/flowers17_baseline_VGG16_CSVLogger_checkpoints'\n","csv_logger = CSVLogger(baseline_model_history_dir + \"/baseline_model_history.csv\", append=True)"],"metadata":{"id":"0E7jg_AK0SH_"},"execution_count":null,"outputs":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"382VaVTJvblo"},"outputs":[],"source":["# complie the model\n","baseline_VGG16_model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1874440,"status":"ok","timestamp":1652228550599,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"0CJXlK0RvmMM","outputId":"32c2fbd1-878f-453e-ebc1-31ff05ba2fc3"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n","  if __name__ == '__main__':\n"]},{"output_type":"stream","name":"stdout","text":["Epoch 1/60\n","34/34 [==============================] - 717s 21s/step - loss: 1.2333 - accuracy: 0.6779 - val_loss: 1.3456 - val_accuracy: 0.6294\n","Epoch 2/60\n","34/34 [==============================] - 19s 560ms/step - loss: 1.1982 - accuracy: 0.6897 - val_loss: 1.3140 - val_accuracy: 0.6647\n","Epoch 3/60\n","34/34 [==============================] - 19s 555ms/step - loss: 1.1778 - accuracy: 0.7029 - val_loss: 1.3410 - val_accuracy: 0.6235\n","Epoch 4/60\n","34/34 [==============================] - 19s 556ms/step - loss: 1.1619 - accuracy: 0.6985 - val_loss: 1.3291 - val_accuracy: 0.6353\n","Epoch 5/60\n","34/34 [==============================] - 19s 558ms/step - loss: 1.1608 - accuracy: 0.6956 - val_loss: 1.2966 - val_accuracy: 0.6441\n","Epoch 6/60\n","34/34 [==============================] - 19s 568ms/step - loss: 1.1587 - accuracy: 0.7132 - val_loss: 1.2989 - val_accuracy: 0.6324\n","Epoch 7/60\n","34/34 [==============================] - 19s 566ms/step - loss: 1.1367 - accuracy: 0.6868 - val_loss: 1.2709 - val_accuracy: 0.6382\n","Epoch 8/60\n","34/34 [==============================] - 19s 559ms/step - loss: 1.1213 - accuracy: 0.7000 - val_loss: 1.2661 - val_accuracy: 0.6265\n","Epoch 9/60\n","34/34 [==============================] - 19s 559ms/step - loss: 1.0826 - accuracy: 0.7265 - val_loss: 1.2620 - val_accuracy: 0.6500\n","Epoch 10/60\n","34/34 [==============================] - 19s 561ms/step - loss: 1.1018 - accuracy: 0.6897 - val_loss: 1.2793 - val_accuracy: 0.6294\n","Epoch 11/60\n","34/34 [==============================] - 19s 566ms/step - loss: 1.1027 - accuracy: 0.6941 - val_loss: 1.2525 - val_accuracy: 0.6353\n","Epoch 12/60\n","34/34 [==============================] - 19s 567ms/step - loss: 1.0861 - accuracy: 0.7074 - val_loss: 1.2108 - val_accuracy: 0.6706\n","Epoch 13/60\n","34/34 [==============================] - 19s 572ms/step - loss: 1.0719 - accuracy: 0.7044 - val_loss: 1.2461 - val_accuracy: 0.6382\n","Epoch 14/60\n","34/34 [==============================] - 19s 572ms/step - loss: 1.0419 - accuracy: 0.7353 - val_loss: 1.2269 - val_accuracy: 0.6324\n","Epoch 15/60\n","34/34 [==============================] - 19s 564ms/step - loss: 1.0496 - accuracy: 0.7191 - val_loss: 1.2111 - val_accuracy: 0.6735\n","Epoch 16/60\n","34/34 [==============================] - 19s 572ms/step - loss: 1.0399 - accuracy: 0.7103 - val_loss: 1.2212 - val_accuracy: 0.6559\n","Epoch 17/60\n","34/34 [==============================] - 19s 562ms/step - loss: 1.0216 - accuracy: 0.7279 - val_loss: 1.2226 - val_accuracy: 0.6735\n","Epoch 18/60\n","34/34 [==============================] - 19s 575ms/step - loss: 1.0349 - accuracy: 0.7250 - val_loss: 1.2129 - val_accuracy: 0.6559\n","Epoch 19/60\n","34/34 [==============================] - 19s 571ms/step - loss: 1.0168 - accuracy: 0.7191 - val_loss: 1.2015 - val_accuracy: 0.6500\n","Epoch 20/60\n","34/34 [==============================] - 19s 570ms/step - loss: 1.0170 - accuracy: 0.7221 - val_loss: 1.1788 - val_accuracy: 0.6559\n","Epoch 21/60\n","34/34 [==============================] - 19s 569ms/step - loss: 1.0044 - accuracy: 0.7456 - val_loss: 1.1968 - val_accuracy: 0.6529\n","Epoch 22/60\n","34/34 [==============================] - 19s 576ms/step - loss: 0.9847 - accuracy: 0.7412 - val_loss: 1.1961 - val_accuracy: 0.6559\n","Epoch 23/60\n","34/34 [==============================] - 20s 579ms/step - loss: 0.9769 - accuracy: 0.7294 - val_loss: 1.1852 - val_accuracy: 0.6765\n","Epoch 24/60\n","34/34 [==============================] - 20s 578ms/step - loss: 0.9834 - accuracy: 0.7338 - val_loss: 1.1352 - val_accuracy: 0.6676\n","Epoch 25/60\n","34/34 [==============================] - 20s 576ms/step - loss: 0.9815 - accuracy: 0.7103 - val_loss: 1.1926 - val_accuracy: 0.6735\n","Epoch 26/60\n","34/34 [==============================] - 19s 577ms/step - loss: 0.9715 - accuracy: 0.7456 - val_loss: 1.1487 - val_accuracy: 0.6618\n","Epoch 27/60\n","34/34 [==============================] - 20s 579ms/step - loss: 0.9604 - accuracy: 0.7368 - val_loss: 1.1522 - val_accuracy: 0.6529\n","Epoch 28/60\n","34/34 [==============================] - 20s 605ms/step - loss: 0.9673 - accuracy: 0.7235 - val_loss: 1.1298 - val_accuracy: 0.6676\n","Epoch 29/60\n","34/34 [==============================] - 19s 574ms/step - loss: 0.9127 - accuracy: 0.7515 - val_loss: 1.1402 - val_accuracy: 0.6676\n","Epoch 30/60\n","34/34 [==============================] - 20s 579ms/step - loss: 0.9531 - accuracy: 0.7456 - val_loss: 1.1385 - val_accuracy: 0.6706\n","Epoch 31/60\n","34/34 [==============================] - 19s 566ms/step - loss: 0.9386 - accuracy: 0.7456 - val_loss: 1.1320 - val_accuracy: 0.6706\n","Epoch 32/60\n","34/34 [==============================] - 19s 567ms/step - loss: 0.9178 - accuracy: 0.7500 - val_loss: 1.1624 - val_accuracy: 0.6500\n","Epoch 33/60\n","34/34 [==============================] - 19s 565ms/step - loss: 0.9122 - accuracy: 0.7515 - val_loss: 1.1211 - val_accuracy: 0.7029\n","Epoch 34/60\n","34/34 [==============================] - 19s 557ms/step - loss: 0.9128 - accuracy: 0.7471 - val_loss: 1.0861 - val_accuracy: 0.6941\n","Epoch 35/60\n","34/34 [==============================] - 19s 568ms/step - loss: 0.9279 - accuracy: 0.7397 - val_loss: 1.1585 - val_accuracy: 0.6529\n","Epoch 36/60\n","34/34 [==============================] - 19s 561ms/step - loss: 0.9169 - accuracy: 0.7426 - val_loss: 1.1414 - val_accuracy: 0.6647\n","Epoch 37/60\n","34/34 [==============================] - 19s 559ms/step - loss: 0.9146 - accuracy: 0.7544 - val_loss: 1.1297 - val_accuracy: 0.6794\n","Epoch 38/60\n","34/34 [==============================] - 19s 559ms/step - loss: 0.9042 - accuracy: 0.7588 - val_loss: 1.1340 - val_accuracy: 0.6618\n","Epoch 39/60\n","34/34 [==============================] - 23s 688ms/step - loss: 0.8995 - accuracy: 0.7721 - val_loss: 1.1032 - val_accuracy: 0.6971\n","Epoch 40/60\n","34/34 [==============================] - 19s 564ms/step - loss: 0.8826 - accuracy: 0.7515 - val_loss: 1.1091 - val_accuracy: 0.6529\n","Epoch 41/60\n","34/34 [==============================] - 19s 558ms/step - loss: 0.8685 - accuracy: 0.7588 - val_loss: 1.0944 - val_accuracy: 0.6882\n","Epoch 42/60\n","34/34 [==============================] - 19s 565ms/step - loss: 0.8674 - accuracy: 0.7412 - val_loss: 1.0945 - val_accuracy: 0.6794\n","Epoch 43/60\n","34/34 [==============================] - 19s 566ms/step - loss: 0.8568 - accuracy: 0.7632 - val_loss: 1.0524 - val_accuracy: 0.6676\n","Epoch 44/60\n","34/34 [==============================] - 19s 564ms/step - loss: 0.8687 - accuracy: 0.7485 - val_loss: 1.0953 - val_accuracy: 0.6794\n","Epoch 45/60\n","34/34 [==============================] - 19s 566ms/step - loss: 0.8507 - accuracy: 0.7574 - val_loss: 1.0650 - val_accuracy: 0.6824\n","Epoch 46/60\n","34/34 [==============================] - 19s 559ms/step - loss: 0.8613 - accuracy: 0.7824 - val_loss: 1.0762 - val_accuracy: 0.6618\n","Epoch 47/60\n","34/34 [==============================] - 19s 563ms/step - loss: 0.8382 - accuracy: 0.7721 - val_loss: 1.0850 - val_accuracy: 0.6765\n","Epoch 48/60\n","34/34 [==============================] - 19s 565ms/step - loss: 0.8431 - accuracy: 0.7721 - val_loss: 1.1017 - val_accuracy: 0.6559\n","Epoch 49/60\n","34/34 [==============================] - 19s 557ms/step - loss: 0.8396 - accuracy: 0.7824 - val_loss: 1.0559 - val_accuracy: 0.7000\n","Epoch 50/60\n","34/34 [==============================] - 19s 559ms/step - loss: 0.8570 - accuracy: 0.7529 - val_loss: 1.1095 - val_accuracy: 0.6559\n","Epoch 51/60\n","34/34 [==============================] - 19s 556ms/step - loss: 0.8259 - accuracy: 0.7662 - val_loss: 1.0527 - val_accuracy: 0.7000\n","Epoch 52/60\n","34/34 [==============================] - 19s 562ms/step - loss: 0.8226 - accuracy: 0.7750 - val_loss: 1.0852 - val_accuracy: 0.6647\n","Epoch 53/60\n","34/34 [==============================] - 19s 561ms/step - loss: 0.8125 - accuracy: 0.7765 - val_loss: 1.0924 - val_accuracy: 0.6735\n","Epoch 54/60\n","34/34 [==============================] - 19s 561ms/step - loss: 0.8360 - accuracy: 0.7750 - val_loss: 1.0568 - val_accuracy: 0.6824\n","Epoch 55/60\n","34/34 [==============================] - 19s 569ms/step - loss: 0.8096 - accuracy: 0.7926 - val_loss: 1.0694 - val_accuracy: 0.6735\n","Epoch 56/60\n","34/34 [==============================] - 19s 557ms/step - loss: 0.7997 - accuracy: 0.7956 - val_loss: 1.0552 - val_accuracy: 0.7088\n","Epoch 57/60\n","34/34 [==============================] - 19s 560ms/step - loss: 0.8101 - accuracy: 0.7985 - val_loss: 1.0907 - val_accuracy: 0.6529\n","Epoch 58/60\n","34/34 [==============================] - 19s 555ms/step - loss: 0.8209 - accuracy: 0.7750 - val_loss: 1.0686 - val_accuracy: 0.6824\n","Epoch 59/60\n","34/34 [==============================] - 19s 561ms/step - loss: 0.7965 - accuracy: 0.7750 - val_loss: 1.0273 - val_accuracy: 0.6794\n","Epoch 60/60\n","34/34 [==============================] - 19s 558ms/step - loss: 0.8018 - accuracy: 0.7765 - val_loss: 1.0473 - val_accuracy: 0.6618\n"]}],"source":["# Train the baseline model\n","baseline_VGG16_model_history = baseline_VGG16_model.fit_generator(\n","        train_generator,\n","        steps_per_epoch= train_generator.samples/train_generator.batch_size, # as 680 images = 34 steps  * 20 batches\n","        epochs= 60,\n","        validation_data=validation_generator,\n","        validation_steps= validation_generator.samples/validation_generator.batch_size, # as 340 images = 34 steps  * 10 batches\n","        callbacks = [checkpoint, csv_logger],\n","        verbose=1)"]},{"cell_type":"markdown","source":["### Evaluating the Model"],"metadata":{"id":"AWGZRI37f4my"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"Acy5SL6FglNV","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421727066,"user_tz":-600,"elapsed":727,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"04f28789-041e-4f05-e8fa-5771d291adc0"},"outputs":[{"output_type":"stream","name":"stdout","text":["successfuly ammened the epochs\n"]}],"source":["# as the model had to be trained over serval runs the epochs would increment from the previous run, this function fixes the csv to reflect the correct epochs\n","df = pd.read_csv(baseline_model_history_dir + \"/baseline_model_history.csv\", index_col=False)\n","df['epoch'] = np.arange(len(df)) + 1\n","df.to_csv(baseline_model_history_dir + \"/baseline_model_history.csv\", index=False)\n","print('successfuly ammened the epochs')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"00CUAOwvkuHe"},"outputs":[],"source":["# read the csv to show the data\n","baseline_model_history = pd.read_csv(baseline_model_history_dir + \"/baseline_model_history.csv\", sep=',', engine='python')"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":545},"executionInfo":{"elapsed":1032,"status":"ok","timestamp":1652228731131,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"0El3h7XtvuWr","outputId":"4ccb394d-f3f9-4df5-8bbf-57baceb38a81"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{"needs_background":"light"}}],"source":["#plot graphs of training and validation\n","\n","acc = baseline_model_history['accuracy']\n","val_acc = baseline_model_history['val_accuracy']\n","loss = baseline_model_history['loss']\n","val_loss = baseline_model_history['val_loss']\n","\n","epochs = range(len(acc))\n","\n","plt.plot(epochs, acc, 'bo', label='Training accuracy')\n","plt.plot(epochs, val_acc, 'b', label='Validation accuracy')\n","plt.title('Training and validation accuracy')\n","plt.legend()\n","\n","plt.figure()\n","\n","plt.plot(epochs, loss, 'bo', label='Training Loss')\n","plt.plot(epochs, val_loss, 'b', label='Validation Loss')\n","plt.title('Training and validation loss')\n","plt.legend()\n","\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"_WDp3g_5E7uo","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652228968396,"user_tz":-600,"elapsed":216994,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"c1d3aae7-dbc2-433c-e272-610eb6e6a73c"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n","  \n"]}],"source":["# get test accuracy and predictions\n","\n","filenames = test_generator.filenames\n","nb_samples = len(filenames)\n","\n","baseline_VGG16_model_predict = baseline_VGG16_model.predict_generator(test_generator,steps = nb_samples)"]},{"cell_type":"code","source":["scores = baseline_VGG16_model.evaluate_generator(test_generator)\n","print(\"\\n%s%s: %.2f%%\" % (\"Testing \",baseline_VGG16_model.metrics_names[1], scores[1]*100))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"PIwMZz9AgesZ","executionInfo":{"status":"ok","timestamp":1652228995328,"user_tz":-600,"elapsed":4609,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"d9847128-e77b-4a5c-b129-125d7ad44e83"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: UserWarning: `Model.evaluate_generator` is deprecated and will be removed in a future version. Please use `Model.evaluate`, which supports generators.\n","  \"\"\"Entry point for launching an IPython kernel.\n"]},{"output_type":"stream","name":"stdout","text":["\n","Testing accuracy: 69.71%\n"]}]},{"cell_type":"code","source":["# get classification report\n","test_labels = test_generator.classes\n","y_pred = np.argmax(baseline_VGG16_model_predict, axis = 1)\n","\n","print(classification_report(test_labels, y_pred))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"HNobp5qc3I3L","executionInfo":{"status":"ok","timestamp":1652228999360,"user_tz":-600,"elapsed":497,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"42318824-c936-4693-d5d3-cfd1725cff56"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.94      0.80      0.86        20\n","           1       0.60      0.45      0.51        20\n","           2       0.68      0.65      0.67        20\n","           3       0.55      0.60      0.57        20\n","           4       0.63      0.60      0.62        20\n","           5       0.84      0.80      0.82        20\n","           6       0.80      0.80      0.80        20\n","           7       0.35      0.40      0.37        20\n","           8       0.88      0.78      0.83        37\n","           9       0.81      0.85      0.83        20\n","          10       1.00      0.65      0.79        20\n","          11       0.00      0.00      0.00         3\n","          12       0.82      0.70      0.76        20\n","          13       0.77      0.85      0.81        20\n","          14       0.85      0.85      0.85        20\n","          15       0.55      0.60      0.57        20\n","          16       0.48      0.80      0.60        20\n","\n","    accuracy                           0.70       340\n","   macro avg       0.68      0.66      0.66       340\n","weighted avg       0.72      0.70      0.70       340\n","\n"]}]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":258268,"status":"ok","timestamp":1652229277349,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"},"user_tz":-600},"id":"Gi5YAe2EE4B1","outputId":"918aeb4d-3c53-4dd8-c885-d82b5e87c836"},"outputs":[],"source":["#Show the Testset images with predictions and accuracy\n","num_class_dict=test_generator.class_indices \n","reverse_dict={}\n","for key, value in num_class_dict.items():\n","    reverse_dict[value]=key   \n","\n","for i , p in enumerate(baseline_VGG16_model_predict):\n","  image_name = str(filenames[i].split('/')[1])\n","  index=np.argmax(p)\n","  flowers_class=reverse_dict[index]    \n","  prob=p[index]\n","  print('for file', image_name, ' predicted class is ', flowers_class,' with a probability of ',prob)\n","  img = image.load_img('/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/jpg/' + image_name, target_size=(224, 224))\n","  plt.imshow(img)\n","  plt.show()"]},{"cell_type":"markdown","metadata":{"id":"IYY3xdXxmtWn"},"source":["# Finetuned VGG16 Models"]},{"cell_type":"markdown","source":["## Adding Conv Layers Model"],"metadata":{"id":"qwitkqst8WOT"}},{"cell_type":"code","source":["# Adding 2 Conv Layers and TC Layers\n","\n","VGG16_base = VGG16(weights= \"imagenet\" , include_top=False, input_shape=(224, 224, 3))\n","VGG16_base.summary()\n","\n","# making it so the VGG16 base cannot be trained\n","for i, layer in enumerate(VGG16_base.layers):\n","    layer.trainable = False\n","    print(i, layer.name, layer.trainable)\n","\n","# add extra con layers\n","add_conv_finetuned_VGG16_model = Sequential()\n","add_conv_finetuned_VGG16_model.add(VGG16_base)\n","add_conv_finetuned_VGG16_model.add(Conv2D(filters=32,kernel_size=(2,2),padding=\"same\", activation=\"relu\"))\n","add_conv_finetuned_VGG16_model.add(Conv2D(filters=32,kernel_size=(2,2),padding=\"same\", activation=\"relu\"))\n","add_conv_finetuned_VGG16_model.add(MaxPooling2D(pool_size=(2,2),strides=(2,2)))\n","\n","add_conv_finetuned_VGG16_model.add(Flatten())\n","add_conv_finetuned_VGG16_model.add(Dropout(0.8))\n","# dropping at 0.8 randomly to prevent overfitting\n","add_conv_finetuned_VGG16_model.add(Dense(512, activation='relu'))\n","add_conv_finetuned_VGG16_model.add(Dense(17, activation='softmax')) # output layer\n","\n","add_conv_finetuned_VGG16_model.summary()"],"metadata":{"id":"9DCZw_5XBiF0","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652229434255,"user_tz":-600,"elapsed":2554,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"e652defd-0888-4d1e-977f-e7672dd558b6"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n","58892288/58889256 [==============================] - 1s 0us/step\n","58900480/58889256 [==============================] - 1s 0us/step\n","Model: \"vgg16\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," input_1 (InputLayer)        [(None, 224, 224, 3)]     0         \n","                                                                 \n"," block1_conv1 (Conv2D)       (None, 224, 224, 64)      1792      \n","                                                                 \n"," block1_conv2 (Conv2D)       (None, 224, 224, 64)      36928     \n","                                                                 \n"," block1_pool (MaxPooling2D)  (None, 112, 112, 64)      0         \n","                                                                 \n"," block2_conv1 (Conv2D)       (None, 112, 112, 128)     73856     \n","                                                                 \n"," block2_conv2 (Conv2D)       (None, 112, 112, 128)     147584    \n","                                                                 \n"," block2_pool (MaxPooling2D)  (None, 56, 56, 128)       0         \n","                                                                 \n"," block3_conv1 (Conv2D)       (None, 56, 56, 256)       295168    \n","                                                                 \n"," block3_conv2 (Conv2D)       (None, 56, 56, 256)       590080    \n","                                                                 \n"," block3_conv3 (Conv2D)       (None, 56, 56, 256)       590080    \n","                                                                 \n"," block3_pool (MaxPooling2D)  (None, 28, 28, 256)       0         \n","                                                                 \n"," block4_conv1 (Conv2D)       (None, 28, 28, 512)       1180160   \n","                                                                 \n"," block4_conv2 (Conv2D)       (None, 28, 28, 512)       2359808   \n","                                                                 \n"," block4_conv3 (Conv2D)       (None, 28, 28, 512)       2359808   \n","                                                                 \n"," block4_pool (MaxPooling2D)  (None, 14, 14, 512)       0         \n","                                                                 \n"," block5_conv1 (Conv2D)       (None, 14, 14, 512)       2359808   \n","                                                                 \n"," block5_conv2 (Conv2D)       (None, 14, 14, 512)       2359808   \n","                                                                 \n"," block5_conv3 (Conv2D)       (None, 14, 14, 512)       2359808   \n","                                                                 \n"," block5_pool (MaxPooling2D)  (None, 7, 7, 512)         0         \n","                                                                 \n","=================================================================\n","Total params: 14,714,688\n","Trainable params: 14,714,688\n","Non-trainable params: 0\n","_________________________________________________________________\n","0 input_1 False\n","1 block1_conv1 False\n","2 block1_conv2 False\n","3 block1_pool False\n","4 block2_conv1 False\n","5 block2_conv2 False\n","6 block2_pool False\n","7 block3_conv1 False\n","8 block3_conv2 False\n","9 block3_conv3 False\n","10 block3_pool False\n","11 block4_conv1 False\n","12 block4_conv2 False\n","13 block4_conv3 False\n","14 block4_pool False\n","15 block5_conv1 False\n","16 block5_conv2 False\n","17 block5_conv3 False\n","18 block5_pool False\n","Model: \"sequential\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," vgg16 (Functional)          (None, 7, 7, 512)         14714688  \n","                                                                 \n"," conv2d (Conv2D)             (None, 7, 7, 32)          65568     \n","                                                                 \n"," conv2d_1 (Conv2D)           (None, 7, 7, 32)          4128      \n","                                                                 \n"," max_pooling2d (MaxPooling2D  (None, 3, 3, 32)         0         \n"," )                                                               \n","                                                                 \n"," flatten (Flatten)           (None, 288)               0         \n","                                                                 \n"," dropout (Dropout)           (None, 288)               0         \n","                                                                 \n"," dense (Dense)               (None, 512)               147968    \n","                                                                 \n"," dense_1 (Dense)             (None, 17)                8721      \n","                                                                 \n","=================================================================\n","Total params: 14,941,073\n","Trainable params: 226,385\n","Non-trainable params: 14,714,688\n","_________________________________________________________________\n"]}]},{"cell_type":"code","source":["finetuned_load_model_dir ='/content/drive/My Drive/42028/Assignment2/Image_Detection/flowers17_finetuned_VGG16_model_checkpoints'\n","add_conv_finetuned_VGG16_model = tf.keras.models.load_model(finetuned_load_model_dir + '/add_2_conv_layers.hdf5')\n","\n","# model summary\n","add_conv_finetuned_VGG16_model.summary()"],"metadata":{"id":"3_OQ2zH49nGA","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652319497520,"user_tz":-600,"elapsed":3612,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"638cc4a6-d4ad-4ad8-fe76-24d4d3ce696f"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"sequential\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," vgg16 (Functional)          (None, 7, 7, 512)         14714688  \n","                                                                 \n"," conv2d (Conv2D)             (None, 7, 7, 32)          65568     \n","                                                                 \n"," conv2d_1 (Conv2D)           (None, 7, 7, 32)          4128      \n","                                                                 \n"," max_pooling2d (MaxPooling2D  (None, 3, 3, 32)         0         \n"," )                                                               \n","                                                                 \n"," flatten (Flatten)           (None, 288)               0         \n","                                                                 \n"," dropout (Dropout)           (None, 288)               0         \n","                                                                 \n"," dense (Dense)               (None, 512)               147968    \n","                                                                 \n"," dense_1 (Dense)             (None, 17)                8721      \n","                                                                 \n","=================================================================\n","Total params: 14,941,073\n","Trainable params: 226,385\n","Non-trainable params: 14,714,688\n","_________________________________________________________________\n"]}]},{"cell_type":"code","source":["tf.keras.utils.plot_model(\n","    add_conv_finetuned_VGG16_model,\n","    to_file=finetuned_load_model_dir + '/addlayers_model.png',\n","    show_shapes=True,\n","    show_dtype=True,\n","    show_layer_names=True,\n","    rankdir='TB',\n","    expand_nested=False,\n","    dpi=96,\n","    layer_range=None,\n","    show_layer_activations=True\n",")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"P0i0yvZH6VFH","executionInfo":{"status":"ok","timestamp":1652320683160,"user_tz":-600,"elapsed":1006,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"9770ec75-6778-47a9-e11a-b0bab03cb536"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<IPython.core.display.Image object>"],"image/png":"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\n"},"metadata":{},"execution_count":13}]},{"cell_type":"code","source":["filepath_of_weights= finetuned_load_model_dir + '/weights.{epoch:02d}-{val_loss:.2f}.hdf5'\n","checkpoint = keras.callbacks.ModelCheckpoint(filepath_of_weights, monitor='val_loss', verbose=0, save_best_only=False, save_weights_only=False, mode='auto', period=1)"],"metadata":{"id":"yAP-Y3dK-ohM","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652229465862,"user_tz":-600,"elapsed":4,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"93b414e2-c7c7-492e-b42a-f230e829d977"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["WARNING:tensorflow:`period` argument is deprecated. Please use `save_freq` to specify the frequency in number of batches seen.\n"]}]},{"cell_type":"code","source":["# configure model to append to csv file every epoch for history\n","finetuned_model_history_dir = '/content/drive/My Drive/42028/Assignment2/Image_Detection/flowers17_finetuned_VGG16_CSVLogger_checkpoints'\n","csv_logger = CSVLogger(finetuned_model_history_dir + \"/add_2_conv_layers.csv\", append=True)\n"],"metadata":{"id":"hJOVXnWa-C9g"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["add_conv_finetuned_VGG16_model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])"],"metadata":{"id":"BiB4mcgfB_Ih"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["add_conv_finetuned_model_history = add_conv_finetuned_VGG16_model.fit_generator(\n","        train_generator,\n","        steps_per_epoch= train_generator.samples//train_generator.batch_size, # as 680 images = 34 steps  * 20 batches\n","        epochs= 100,\n","        validation_data=validation_generator,\n","        validation_steps= validation_generator.samples//validation_generator.batch_size, # as 340 images = 34 steps  * 10 batches\n","        callbacks = [checkpoint, csv_logger],\n","        verbose=1)"],"metadata":{"id":"QN3LT7oACByg","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652231421605,"user_tz":-600,"elapsed":1906499,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"a0fb72a7-6645-44f3-918c-4aebccfcd679"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:8: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n","  \n"]},{"output_type":"stream","name":"stdout","text":["Epoch 1/100\n","34/34 [==============================] - 23s 613ms/step - loss: 2.8596 - accuracy: 0.0882 - val_loss: 2.7264 - val_accuracy: 0.1176\n","Epoch 2/100\n","34/34 [==============================] - 19s 554ms/step - loss: 2.6970 - accuracy: 0.1103 - val_loss: 2.5426 - val_accuracy: 0.1647\n","Epoch 3/100\n","34/34 [==============================] - 19s 559ms/step - loss: 2.5475 - accuracy: 0.1441 - val_loss: 2.3848 - val_accuracy: 0.2294\n","Epoch 4/100\n","34/34 [==============================] - 19s 559ms/step - loss: 2.4293 - accuracy: 0.1941 - val_loss: 2.2803 - val_accuracy: 0.2324\n","Epoch 5/100\n","34/34 [==============================] - 19s 562ms/step - loss: 2.3868 - accuracy: 0.2044 - val_loss: 2.0786 - val_accuracy: 0.3118\n","Epoch 6/100\n","34/34 [==============================] - 20s 578ms/step - loss: 2.2015 - accuracy: 0.2471 - val_loss: 1.9230 - val_accuracy: 0.3647\n","Epoch 7/100\n","34/34 [==============================] - 20s 586ms/step - loss: 2.0571 - accuracy: 0.3103 - val_loss: 1.9032 - val_accuracy: 0.3706\n","Epoch 8/100\n","34/34 [==============================] - 19s 564ms/step - loss: 2.0838 - accuracy: 0.2824 - val_loss: 1.8753 - val_accuracy: 0.4088\n","Epoch 9/100\n","34/34 [==============================] - 19s 569ms/step - loss: 2.0321 - accuracy: 0.3000 - val_loss: 1.7874 - val_accuracy: 0.4471\n","Epoch 10/100\n","34/34 [==============================] - 19s 557ms/step - loss: 2.0187 - accuracy: 0.3338 - val_loss: 1.7510 - val_accuracy: 0.4265\n","Epoch 11/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.8730 - accuracy: 0.3765 - val_loss: 1.6739 - val_accuracy: 0.4500\n","Epoch 12/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.8494 - accuracy: 0.3471 - val_loss: 1.6183 - val_accuracy: 0.4265\n","Epoch 13/100\n","34/34 [==============================] - 19s 564ms/step - loss: 1.7565 - accuracy: 0.4176 - val_loss: 1.5958 - val_accuracy: 0.4912\n","Epoch 14/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.8089 - accuracy: 0.3765 - val_loss: 1.6676 - val_accuracy: 0.4765\n","Epoch 15/100\n","34/34 [==============================] - 19s 573ms/step - loss: 1.8013 - accuracy: 0.3794 - val_loss: 1.6025 - val_accuracy: 0.4794\n","Epoch 16/100\n","34/34 [==============================] - 20s 602ms/step - loss: 1.6508 - accuracy: 0.4279 - val_loss: 1.5045 - val_accuracy: 0.5294\n","Epoch 17/100\n","34/34 [==============================] - 20s 584ms/step - loss: 1.6562 - accuracy: 0.4206 - val_loss: 1.5708 - val_accuracy: 0.4735\n","Epoch 18/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.6539 - accuracy: 0.4265 - val_loss: 1.4806 - val_accuracy: 0.5265\n","Epoch 19/100\n","34/34 [==============================] - 19s 556ms/step - loss: 1.6147 - accuracy: 0.4500 - val_loss: 1.4371 - val_accuracy: 0.5235\n","Epoch 20/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.5581 - accuracy: 0.4529 - val_loss: 1.4081 - val_accuracy: 0.5471\n","Epoch 21/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.4936 - accuracy: 0.4853 - val_loss: 1.3811 - val_accuracy: 0.5382\n","Epoch 22/100\n","34/34 [==============================] - 19s 557ms/step - loss: 1.5418 - accuracy: 0.4574 - val_loss: 1.3781 - val_accuracy: 0.5500\n","Epoch 23/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.4303 - accuracy: 0.5029 - val_loss: 1.3677 - val_accuracy: 0.5324\n","Epoch 24/100\n","34/34 [==============================] - 19s 557ms/step - loss: 1.4609 - accuracy: 0.4956 - val_loss: 1.4445 - val_accuracy: 0.5176\n","Epoch 25/100\n","34/34 [==============================] - 20s 580ms/step - loss: 1.4931 - accuracy: 0.4882 - val_loss: 1.2685 - val_accuracy: 0.5618\n","Epoch 26/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.4782 - accuracy: 0.4882 - val_loss: 1.2467 - val_accuracy: 0.5941\n","Epoch 27/100\n","34/34 [==============================] - 19s 568ms/step - loss: 1.4366 - accuracy: 0.5132 - val_loss: 1.2530 - val_accuracy: 0.6118\n","Epoch 28/100\n","34/34 [==============================] - 19s 560ms/step - loss: 1.4313 - accuracy: 0.5015 - val_loss: 1.3179 - val_accuracy: 0.5824\n","Epoch 29/100\n","34/34 [==============================] - 19s 563ms/step - loss: 1.4198 - accuracy: 0.5000 - val_loss: 1.3412 - val_accuracy: 0.5618\n","Epoch 30/100\n","34/34 [==============================] - 19s 559ms/step - loss: 1.3704 - accuracy: 0.5147 - val_loss: 1.3104 - val_accuracy: 0.6000\n","Epoch 31/100\n","34/34 [==============================] - 19s 564ms/step - loss: 1.4075 - accuracy: 0.5162 - val_loss: 1.2797 - val_accuracy: 0.6000\n","Epoch 32/100\n","34/34 [==============================] - 19s 554ms/step - loss: 1.3364 - accuracy: 0.5074 - val_loss: 1.1855 - val_accuracy: 0.6147\n","Epoch 33/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.3370 - accuracy: 0.5676 - val_loss: 1.1997 - val_accuracy: 0.6353\n","Epoch 34/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.2570 - accuracy: 0.5559 - val_loss: 1.2257 - val_accuracy: 0.5618\n","Epoch 35/100\n","34/34 [==============================] - 19s 556ms/step - loss: 1.2145 - accuracy: 0.5809 - val_loss: 1.2026 - val_accuracy: 0.5588\n","Epoch 36/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.3472 - accuracy: 0.5338 - val_loss: 1.2620 - val_accuracy: 0.6059\n","Epoch 37/100\n","34/34 [==============================] - 19s 556ms/step - loss: 1.2848 - accuracy: 0.5500 - val_loss: 1.2349 - val_accuracy: 0.6088\n","Epoch 38/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.3001 - accuracy: 0.5382 - val_loss: 1.2565 - val_accuracy: 0.5971\n","Epoch 39/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.2680 - accuracy: 0.5574 - val_loss: 1.1947 - val_accuracy: 0.6176\n","Epoch 40/100\n","34/34 [==============================] - 19s 560ms/step - loss: 1.1578 - accuracy: 0.6000 - val_loss: 1.1660 - val_accuracy: 0.6000\n","Epoch 41/100\n","34/34 [==============================] - 19s 575ms/step - loss: 1.2397 - accuracy: 0.5809 - val_loss: 1.3314 - val_accuracy: 0.5647\n","Epoch 42/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.2164 - accuracy: 0.5662 - val_loss: 1.1401 - val_accuracy: 0.6353\n","Epoch 43/100\n","34/34 [==============================] - 19s 565ms/step - loss: 1.1772 - accuracy: 0.5868 - val_loss: 1.2658 - val_accuracy: 0.5647\n","Epoch 44/100\n","34/34 [==============================] - 19s 567ms/step - loss: 1.2031 - accuracy: 0.5765 - val_loss: 1.2862 - val_accuracy: 0.5735\n","Epoch 45/100\n","34/34 [==============================] - 19s 552ms/step - loss: 1.1487 - accuracy: 0.6000 - val_loss: 1.0863 - val_accuracy: 0.6353\n","Epoch 46/100\n","34/34 [==============================] - 19s 567ms/step - loss: 1.1643 - accuracy: 0.6000 - val_loss: 1.1445 - val_accuracy: 0.6147\n","Epoch 47/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.1593 - accuracy: 0.6059 - val_loss: 1.1537 - val_accuracy: 0.6235\n","Epoch 48/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.1462 - accuracy: 0.5912 - val_loss: 1.1924 - val_accuracy: 0.6029\n","Epoch 49/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.1540 - accuracy: 0.6088 - val_loss: 1.1274 - val_accuracy: 0.6324\n","Epoch 50/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.2107 - accuracy: 0.5926 - val_loss: 1.1444 - val_accuracy: 0.5647\n","Epoch 51/100\n","34/34 [==============================] - 19s 560ms/step - loss: 1.1749 - accuracy: 0.5985 - val_loss: 1.0603 - val_accuracy: 0.6500\n","Epoch 52/100\n","34/34 [==============================] - 19s 554ms/step - loss: 1.1085 - accuracy: 0.6176 - val_loss: 1.0554 - val_accuracy: 0.6588\n","Epoch 53/100\n","34/34 [==============================] - 19s 562ms/step - loss: 1.1328 - accuracy: 0.5912 - val_loss: 1.2534 - val_accuracy: 0.6059\n","Epoch 54/100\n","34/34 [==============================] - 19s 560ms/step - loss: 1.0578 - accuracy: 0.6588 - val_loss: 1.1657 - val_accuracy: 0.6294\n","Epoch 55/100\n","34/34 [==============================] - 19s 553ms/step - loss: 1.1099 - accuracy: 0.6338 - val_loss: 1.1336 - val_accuracy: 0.6000\n","Epoch 56/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.1100 - accuracy: 0.6265 - val_loss: 1.1047 - val_accuracy: 0.6353\n","Epoch 57/100\n","34/34 [==============================] - 19s 563ms/step - loss: 1.1115 - accuracy: 0.6176 - val_loss: 1.1157 - val_accuracy: 0.6265\n","Epoch 58/100\n","34/34 [==============================] - 19s 572ms/step - loss: 1.0152 - accuracy: 0.6324 - val_loss: 1.1703 - val_accuracy: 0.6324\n","Epoch 59/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.0759 - accuracy: 0.6338 - val_loss: 1.3248 - val_accuracy: 0.5706\n","Epoch 60/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.1097 - accuracy: 0.6088 - val_loss: 1.1010 - val_accuracy: 0.6176\n","Epoch 61/100\n","34/34 [==============================] - 19s 563ms/step - loss: 1.1085 - accuracy: 0.6118 - val_loss: 1.0925 - val_accuracy: 0.6471\n","Epoch 62/100\n","34/34 [==============================] - 19s 559ms/step - loss: 1.0445 - accuracy: 0.6691 - val_loss: 1.0713 - val_accuracy: 0.6441\n","Epoch 63/100\n","34/34 [==============================] - 19s 570ms/step - loss: 1.0278 - accuracy: 0.6691 - val_loss: 1.3582 - val_accuracy: 0.5912\n","Epoch 64/100\n","34/34 [==============================] - 19s 558ms/step - loss: 1.1920 - accuracy: 0.5985 - val_loss: 1.1228 - val_accuracy: 0.6235\n","Epoch 65/100\n","34/34 [==============================] - 19s 555ms/step - loss: 1.0463 - accuracy: 0.6338 - val_loss: 1.2964 - val_accuracy: 0.5941\n","Epoch 66/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.0577 - accuracy: 0.6456 - val_loss: 1.0352 - val_accuracy: 0.6529\n","Epoch 67/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.0264 - accuracy: 0.6294 - val_loss: 1.1503 - val_accuracy: 0.5882\n","Epoch 68/100\n","34/34 [==============================] - 19s 559ms/step - loss: 0.9674 - accuracy: 0.6662 - val_loss: 1.0929 - val_accuracy: 0.6324\n","Epoch 69/100\n","34/34 [==============================] - 19s 564ms/step - loss: 0.9506 - accuracy: 0.6794 - val_loss: 1.1933 - val_accuracy: 0.6235\n","Epoch 70/100\n","34/34 [==============================] - 19s 553ms/step - loss: 0.9496 - accuracy: 0.6676 - val_loss: 1.0992 - val_accuracy: 0.6618\n","Epoch 71/100\n","34/34 [==============================] - 19s 558ms/step - loss: 0.9676 - accuracy: 0.6529 - val_loss: 1.1120 - val_accuracy: 0.6324\n","Epoch 72/100\n","34/34 [==============================] - 19s 558ms/step - loss: 0.9957 - accuracy: 0.6485 - val_loss: 1.1873 - val_accuracy: 0.6353\n","Epoch 73/100\n","34/34 [==============================] - 19s 558ms/step - loss: 0.9717 - accuracy: 0.6721 - val_loss: 1.0369 - val_accuracy: 0.6618\n","Epoch 74/100\n","34/34 [==============================] - 20s 581ms/step - loss: 0.9941 - accuracy: 0.6618 - val_loss: 1.0672 - val_accuracy: 0.6382\n","Epoch 75/100\n","34/34 [==============================] - 19s 560ms/step - loss: 0.9749 - accuracy: 0.6574 - val_loss: 1.1769 - val_accuracy: 0.6000\n","Epoch 76/100\n","34/34 [==============================] - 19s 555ms/step - loss: 0.9527 - accuracy: 0.6750 - val_loss: 1.1033 - val_accuracy: 0.6176\n","Epoch 77/100\n","34/34 [==============================] - 19s 559ms/step - loss: 0.9182 - accuracy: 0.6897 - val_loss: 1.1892 - val_accuracy: 0.6206\n","Epoch 78/100\n","34/34 [==============================] - 19s 563ms/step - loss: 1.0248 - accuracy: 0.6368 - val_loss: 1.1388 - val_accuracy: 0.6206\n","Epoch 79/100\n","34/34 [==============================] - 19s 557ms/step - loss: 0.9823 - accuracy: 0.6838 - val_loss: 1.0021 - val_accuracy: 0.6588\n","Epoch 80/100\n","34/34 [==============================] - 19s 555ms/step - loss: 0.9885 - accuracy: 0.6765 - val_loss: 1.2038 - val_accuracy: 0.6059\n","Epoch 81/100\n","34/34 [==============================] - 19s 561ms/step - loss: 1.0048 - accuracy: 0.6574 - val_loss: 1.0546 - val_accuracy: 0.6500\n","Epoch 82/100\n","34/34 [==============================] - 19s 571ms/step - loss: 0.9111 - accuracy: 0.7103 - val_loss: 1.0719 - val_accuracy: 0.6529\n","Epoch 83/100\n","34/34 [==============================] - 19s 550ms/step - loss: 0.9113 - accuracy: 0.6824 - val_loss: 1.0623 - val_accuracy: 0.6765\n","Epoch 84/100\n","34/34 [==============================] - 19s 554ms/step - loss: 0.8933 - accuracy: 0.6691 - val_loss: 1.0654 - val_accuracy: 0.6471\n","Epoch 85/100\n","34/34 [==============================] - 19s 554ms/step - loss: 0.8751 - accuracy: 0.6765 - val_loss: 1.0153 - val_accuracy: 0.6500\n","Epoch 86/100\n","34/34 [==============================] - 19s 564ms/step - loss: 0.8984 - accuracy: 0.6897 - val_loss: 0.9913 - val_accuracy: 0.6441\n","Epoch 87/100\n","34/34 [==============================] - 19s 558ms/step - loss: 0.9609 - accuracy: 0.6676 - val_loss: 1.1078 - val_accuracy: 0.6000\n","Epoch 88/100\n","34/34 [==============================] - 19s 559ms/step - loss: 0.9495 - accuracy: 0.6662 - val_loss: 1.0225 - val_accuracy: 0.6765\n","Epoch 89/100\n","34/34 [==============================] - 19s 563ms/step - loss: 0.8729 - accuracy: 0.7118 - val_loss: 0.9873 - val_accuracy: 0.6735\n","Epoch 90/100\n","34/34 [==============================] - 19s 565ms/step - loss: 0.8938 - accuracy: 0.6956 - val_loss: 1.0257 - val_accuracy: 0.6676\n","Epoch 91/100\n","34/34 [==============================] - 19s 567ms/step - loss: 0.8814 - accuracy: 0.7059 - val_loss: 1.0490 - val_accuracy: 0.6324\n","Epoch 92/100\n","34/34 [==============================] - 19s 559ms/step - loss: 0.9190 - accuracy: 0.7029 - val_loss: 1.0244 - val_accuracy: 0.6735\n","Epoch 93/100\n","34/34 [==============================] - 19s 564ms/step - loss: 0.8889 - accuracy: 0.6779 - val_loss: 1.0826 - val_accuracy: 0.6618\n","Epoch 94/100\n","34/34 [==============================] - 19s 561ms/step - loss: 0.9499 - accuracy: 0.6735 - val_loss: 0.9657 - val_accuracy: 0.6500\n","Epoch 95/100\n","34/34 [==============================] - 19s 567ms/step - loss: 0.8660 - accuracy: 0.7088 - val_loss: 1.0701 - val_accuracy: 0.6794\n","Epoch 96/100\n","34/34 [==============================] - 19s 550ms/step - loss: 0.9474 - accuracy: 0.6779 - val_loss: 1.1468 - val_accuracy: 0.6294\n","Epoch 97/100\n","34/34 [==============================] - 19s 562ms/step - loss: 0.9346 - accuracy: 0.6809 - val_loss: 1.1308 - val_accuracy: 0.6147\n","Epoch 98/100\n","34/34 [==============================] - 19s 558ms/step - loss: 0.9046 - accuracy: 0.7206 - val_loss: 1.0824 - val_accuracy: 0.6618\n","Epoch 99/100\n","34/34 [==============================] - 19s 560ms/step - loss: 0.8698 - accuracy: 0.7074 - val_loss: 0.9865 - val_accuracy: 0.6765\n","Epoch 100/100\n","34/34 [==============================] - 19s 554ms/step - loss: 0.8067 - accuracy: 0.7132 - val_loss: 1.0523 - val_accuracy: 0.6471\n"]}]},{"cell_type":"markdown","source":["### Evaluating the Model"],"metadata":{"id":"pihn8N98f07K"}},{"cell_type":"code","source":["# as the model had to be trained over serval runs the epochs would increment from the previous run, this function fixes the csv to reflect the correct epochs\n","df = pd.read_csv(finetuned_model_history_dir + \"/add_2_conv_layers.csv\", index_col=False)\n","df['epoch'] = np.arange(len(df)) + 1\n","df.to_csv(finetuned_model_history_dir + \"/add_2_conv_layers.csv\", index=False)\n","print('successfuly ammened the epochs')"],"metadata":{"id":"L3N3xFn0_OwE","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421812164,"user_tz":-600,"elapsed":1164,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"44986974-40f4-40a8-a9dd-95c81ec38555"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["successfuly ammened the epochs\n"]}]},{"cell_type":"code","source":["# read the csv to show the data\n","add_conv_finetuned_model_history = pd.read_csv(finetuned_model_history_dir + \"/add_2_conv_layers.csv\", sep=',', engine='python')"],"metadata":{"id":"5sE15Kzn_gIK"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#plot graphs of training and validation\n","\n","acc = add_conv_finetuned_model_history['accuracy']\n","val_acc = add_conv_finetuned_model_history['val_accuracy']\n","loss = add_conv_finetuned_model_history['loss']\n","val_loss = add_conv_finetuned_model_history['val_loss']\n","\n","epochs = range(len(acc))\n","\n","plt.plot(epochs, acc, 'bo', label='Training accuracy')\n","plt.plot(epochs, val_acc, 'b', label='Validation accuracy')\n","plt.title('Training and validation accuracy')\n","plt.legend()\n","\n","plt.figure()\n","\n","plt.plot(epochs, loss, 'bo', label='Training Loss')\n","plt.plot(epochs, val_loss, 'b', label='Validation Loss')\n","plt.title('Training and validation loss')\n","plt.legend()\n","\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":545},"id":"ZypzryRY_nPo","executionInfo":{"status":"ok","timestamp":1652231438078,"user_tz":-600,"elapsed":2045,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"6853d437-c0c1-48b7-c554-e4937c973f4a"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["# get test accuracy and predictions\n","\n","filenames = test_generator.filenames\n","nb_samples = len(filenames)\n","\n","add_conv_finetuned_VGG16_model_predictions = add_conv_finetuned_VGG16_model.predict_generator(test_generator,steps = nb_samples)\n","\n","scores = add_conv_finetuned_VGG16_model.evaluate_generator(test_generator)\n","print(\"\\n%s%s: %.2f%%\" % (\"Testing \",add_conv_finetuned_VGG16_model.metrics_names[1], scores[1]*100))"],"metadata":{"id":"eIGN-CJg_19c","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652231496122,"user_tz":-600,"elapsed":10017,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"8538ac11-a9da-4c2f-8d7c-db752f46171d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n","  \n","/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:8: UserWarning: `Model.evaluate_generator` is deprecated and will be removed in a future version. Please use `Model.evaluate`, which supports generators.\n","  \n"]},{"output_type":"stream","name":"stdout","text":["\n","Testing accuracy: 70.59%\n"]}]},{"cell_type":"code","source":["# get classification report\n","test_labels = test_generator.classes\n","y_pred = np.argmax(add_conv_finetuned_VGG16_model_predictions, axis = 1)\n","\n","print(classification_report(test_labels, y_pred))"],"metadata":{"id":"xkDT-fu6AHmI","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652231503451,"user_tz":-600,"elapsed":5,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"47d41b1e-75d0-4470-c8c7-7e6cfd0ea9ff"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       1.00      0.75      0.86        20\n","           1       0.67      0.30      0.41        20\n","           2       0.81      0.65      0.72        20\n","           3       0.46      0.85      0.60        20\n","           4       0.76      0.65      0.70        20\n","           5       0.79      0.55      0.65        20\n","           6       0.80      0.80      0.80        20\n","           7       0.38      0.25      0.30        20\n","           8       0.89      0.92      0.91        37\n","           9       1.00      0.75      0.86        20\n","          10       0.88      0.70      0.78        20\n","          11       0.00      0.00      0.00         3\n","          12       0.62      0.80      0.70        20\n","          13       0.94      0.85      0.89        20\n","          14       0.75      0.60      0.67        20\n","          15       0.51      0.90      0.65        20\n","          16       0.51      0.90      0.65        20\n","\n","    accuracy                           0.71       340\n","   macro avg       0.69      0.66      0.66       340\n","weighted avg       0.74      0.71      0.70       340\n","\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, msg_start, len(result))\n","/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, msg_start, len(result))\n","/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, msg_start, len(result))\n"]}]},{"cell_type":"code","source":["#Show the Testset images with predictions and accuracy\n","num_class_dict=test_generator.class_indices \n","reverse_dict={}\n","for key, value in num_class_dict.items():\n","    reverse_dict[value]=key   \n","\n","for i , p in enumerate(add_conv_finetuned_VGG16_model_predictions):\n","  image_name = str(filenames[i].split('/')[1])\n","  index=np.argmax(p)\n","  flowers_class=reverse_dict[index]    \n","  prob=p[index]\n","  print('for file', image_name, ' predicted class is ', flowers_class,'with a probability of',prob)\n","  img = image.load_img('/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/jpg/' + image_name, target_size=(224, 224))\n","  plt.imshow(img)\n","  plt.show()"],"metadata":{"id":"HahKWq1PCeDV","colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1652231714725,"user_tz":-600,"elapsed":206328,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"7d4207cb-5ecf-4fac-b59d-a646406105bb"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Remove 2 Conv Layers Model"],"metadata":{"id":"58zpG5fJ_EDc"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"XtujZzGKBOu4"},"outputs":[],"source":["#Fine tune pretained VGG16 model\n","VGG16_base = VGG16(weights= \"imagenet\" , include_top=False, input_shape=(224, 224, 3))\n","\n","# removed 2 conv layers and global_average_pooling2d_2\n","VGG16_base = Model(VGG16_base.input, VGG16_base.layers[-3].output)\n","\n","# Check the trainable status of the individual layers\n","\n","for i, layer in enumerate(VGG16_base.layers):\n","    layer.trainable = False\n","    print(i, layer.name, layer.trainable)\n","\n","VGG16_base.summary()\n","\n","# add FC layers and pooling\n","rmv_layers_finetuned_VGG16_model = Sequential()\n","rmv_layers_finetuned_VGG16_model.add(VGG16_base)\n","rmv_layers_finetuned_VGG16_model.add(MaxPooling2D(pool_size=(2,2),strides=(2,2)))\n","\n","rmv_layers_finetuned_VGG16_model.add(Flatten())\n","rmv_layers_finetuned_VGG16_model.add(Dropout(0.8))\n","# drop 0.8 with dropout layer to avoid overfitting\n","rmv_layers_finetuned_VGG16_model.add(Dense(512, activation='relu'))\n","rmv_layers_finetuned_VGG16_model.add(Dense(17, activation='softmax')) # output layer\n","\n","for i, layer in enumerate(rmv_layers_finetuned_VGG16_model.layers):\n","    print(i, layer.name, layer.trainable)\n","\n","# model summary\n","rmv_layers_finetuned_VGG16_model.summary()"]},{"cell_type":"code","source":["# if we need to load model from dir\n","finetuned_load_model_dir ='/content/drive/My Drive/42028/Assignment2/Image_Detection/flowers17_finetuned_VGG16_model_checkpoints/'\n","rmv_layers_finetuned_VGG16_model = tf.keras.models.load_model(finetuned_load_model_dir + 'rmv_2_layers_model.hdf5')\n","\n","# model summary\n","rmv_layers_finetuned_VGG16_model.summary()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"SX5tI5qjcvTx","executionInfo":{"status":"ok","timestamp":1652321595673,"user_tz":-600,"elapsed":2859,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"b4c01fd0-7de0-452f-ab6b-b54db0e61329"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"sequential_3\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," model_3 (Functional)        (None, 14, 14, 512)       12354880  \n","                                                                 \n"," max_pooling2d_2 (MaxPooling  (None, 7, 7, 512)        0         \n"," 2D)                                                             \n","                                                                 \n"," flatten_3 (Flatten)         (None, 25088)             0         \n","                                                                 \n"," dropout_5 (Dropout)         (None, 25088)             0         \n","                                                                 \n"," dense_6 (Dense)             (None, 512)               12845568  \n","                                                                 \n"," dense_7 (Dense)             (None, 17)                8721      \n","                                                                 \n","=================================================================\n","Total params: 25,209,169\n","Trainable params: 12,854,289\n","Non-trainable params: 12,354,880\n","_________________________________________________________________\n"]}]},{"cell_type":"code","source":["tf.keras.utils.plot_model(\n","    rmv_layers_finetuned_VGG16_model,\n","    to_file=finetuned_load_model_dir + '/rmvlayers_model.png',\n","    show_shapes=True,\n","    show_dtype=True,\n","    show_layer_names=True,\n","    rankdir='TB',\n","    expand_nested=False,\n","    dpi=96,\n","    layer_range=None,\n","    show_layer_activations=True\n",")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":969},"id":"1XfnZwWUCmmz","executionInfo":{"status":"ok","timestamp":1652321598329,"user_tz":-600,"elapsed":306,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"232da1f7-ed3e-4412-bcc9-10e9ad464891"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<IPython.core.display.Image object>"],"image/png":"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\n"},"metadata":{},"execution_count":15}]},{"cell_type":"code","source":["filepath_of_weights= finetuned_load_model_dir + '/weights.{epoch:02d}-{val_loss:.2f}.hdf5'\n","checkpoint = keras.callbacks.ModelCheckpoint(filepath_of_weights, monitor='val_loss', verbose=0, save_best_only=False, save_weights_only=False, mode='auto', period=1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"iWu4GJ9Lc-5V","executionInfo":{"status":"ok","timestamp":1652177968738,"user_tz":-600,"elapsed":340,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"964e7c4a-ec2c-4299-9758-bf75de4885fa"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["WARNING:tensorflow:`period` argument is deprecated. Please use `save_freq` to specify the frequency in number of batches seen.\n"]}]},{"cell_type":"code","source":["# configure model to append to csv file every epoch for history\n","finetuned_model_history_dir = '/content/drive/My Drive/42028/Assignment2/Image_Detection/flowers17_finetuned_VGG16_CSVLogger_checkpoints'\n","csv_logger = CSVLogger(finetuned_model_history_dir + \"/rmv_2_layers_history.csv\", append=True)"],"metadata":{"id":"RbeMhawfdF8Z"},"execution_count":null,"outputs":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"MVXEJDf-qqvR"},"outputs":[],"source":["rmv_layers_finetuned_VGG16_model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])"]},{"cell_type":"markdown","metadata":{"id":"3gAqmoFPmc0f"},"source":[""]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"DMTl3z0HwHGb","outputId":"2cadab51-93de-4543-8f6f-1533ddcd53b2","executionInfo":{"status":"ok","timestamp":1652145100483,"user_tz":-600,"elapsed":504786,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}}},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:24: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n"]},{"output_type":"stream","name":"stdout","text":["34/34 [==============================] - 468s 14s/step - loss: 0.8196 - accuracy: 0.7250 - val_loss: 0.8916 - val_accuracy: 0.7147\n"]}],"source":["rmv_layers_finetuned_VGG16_model_history = rmv_layers_finetuned_VGG16_model.fit_generator(\n","        train_generator,\n","        steps_per_epoch= train_generator.samples//train_generator.batch_size, # as 680 images = 34 steps  * 20 batches\n","        epochs= 1,\n","        validation_data=validation_generator,\n","        validation_steps= validation_generator.samples//validation_generator.batch_size, # as 340 images = 34 steps  * 10 batches\n","        callbacks = [checkpoint, csv_logger],\n","        verbose=1)"]},{"cell_type":"markdown","source":["### Evaluating the Model"],"metadata":{"id":"MlkbJghLfsbA"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"h3KzbrhJdGUb","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1652421854617,"user_tz":-600,"elapsed":258,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"088c5335-82ee-492b-998c-dcf1bf1ffe6d"},"outputs":[{"output_type":"stream","name":"stdout","text":["successfuly ammened the epochs\n"]}],"source":["# as the model had to be trained over serval runs the epochs would increment from the previous run, this function fixes the csv to reflect the correct epochs\n","df = pd.read_csv(finetuned_model_history_dir + \"/rmv_2_layers_history.csv\", index_col=False)\n","df['epoch'] = np.arange(len(df)) + 1\n","df.to_csv(finetuned_model_history_dir + \"/rmv_2_layers_history.csv\", index=False)\n","print('successfuly ammened the epochs')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"wn2GOg9RdRw8"},"outputs":[],"source":["# read the csv to show the data\n","rmv_conv_finetuned_model_history = pd.read_csv(finetuned_model_history_dir + \"/rmv_2_layers_history.csv\", sep=',', engine='python')"]},{"cell_type":"code","source":["#plot graphs of training and validation\n","\n","acc = rmv_conv_finetuned_model_history['accuracy']\n","val_acc = rmv_conv_finetuned_model_history['val_accuracy']\n","loss = rmv_conv_finetuned_model_history['loss']\n","val_loss = rmv_conv_finetuned_model_history['val_loss']\n","\n","epochs = range(len(acc))\n","\n","plt.plot(epochs, acc, 'bo', label='Training accuracy')\n","plt.plot(epochs, val_acc, 'b', label='Validation accuracy')\n","plt.title('Training and validation accuracy')\n","plt.legend()\n","\n","plt.figure()\n","\n","plt.plot(epochs, loss, 'bo', label='Training Loss')\n","plt.plot(epochs, val_loss, 'b', label='Validation Loss')\n","plt.title('Training and validation loss')\n","plt.legend()\n","\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":545},"id":"_E64yjKyeCxS","executionInfo":{"status":"ok","timestamp":1652231752777,"user_tz":-600,"elapsed":855,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"4225421a-968e-4acd-c8c8-28f4293edab5"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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size 432x288 with 1 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["# get test accuracy and predictions\n","\n","filenames = test_generator.filenames\n","nb_samples = len(filenames)\n","\n","rmv_conv_finetuned_VGG16_model_predictions = rmv_layers_finetuned_VGG16_model.predict_generator(test_generator,steps = nb_samples)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xmVPq_hVeOfe","executionInfo":{"status":"ok","timestamp":1652178275504,"user_tz":-600,"elapsed":209590,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"3b44b8da-3594-472f-ff3b-de57a59c61d8"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n","  \n"]}]},{"cell_type":"code","source":["#scores = rmv_layers_finetuned_VGG16_model.evaluate_generator(test_generator)\n","print(\"\\n%s%s: %.2f%%\" % (\"Testing\",rmv_layers_finetuned_VGG16_model.metrics_names[1], scores[1]*100))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"w5zCQPlDfH-e","executionInfo":{"status":"ok","timestamp":1652178778006,"user_tz":-600,"elapsed":5,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"b8b7c263-0101-410e-b9bb-72e5763b1a15"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","Testingaccuracy: 78.82%\n"]}]},{"cell_type":"code","source":["# get classification report\n","test_labels = test_generator.classes\n","y_pred = np.argmax(rmv_conv_finetuned_VGG16_model_predictions, axis = 1)\n","\n","print(classification_report(test_labels, y_pred))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"u1uaR5QVeOax","executionInfo":{"status":"ok","timestamp":1652178567951,"user_tz":-600,"elapsed":453,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"9719cee1-10bc-4716-9b24-91d2f8567589"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       1.00      0.85      0.92        20\n","           1       0.81      0.65      0.72        20\n","           2       0.86      0.60      0.71        20\n","           3       0.79      0.75      0.77        20\n","           4       0.85      0.85      0.85        20\n","           5       0.94      0.80      0.86        20\n","           6       0.76      0.80      0.78        20\n","           7       0.64      0.45      0.53        20\n","           8       0.97      0.81      0.88        37\n","           9       0.83      0.95      0.88        20\n","          10       0.94      0.75      0.83        20\n","          11       0.20      0.33      0.25         3\n","          12       0.71      1.00      0.83        20\n","          13       0.68      0.95      0.79        20\n","          14       0.90      0.90      0.90        20\n","          15       0.77      0.85      0.81        20\n","          16       0.48      0.70      0.57        20\n","\n","    accuracy                           0.79       340\n","   macro avg       0.77      0.76      0.76       340\n","weighted avg       0.81      0.79      0.79       340\n","\n"]}]},{"cell_type":"code","source":["#Show the Testset images with predictions and accuracy\n","num_class_dict=test_generator.class_indices \n","reverse_dict={}\n","for key, value in num_class_dict.items():\n","    reverse_dict[value]=key   \n","\n","for i , p in enumerate(add_conv_finetuned_VGG16_model_predictions):\n","  image_name = str(filenames[i].split('/')[1])\n","  index=np.argmax(p)\n","  flowers_class=reverse_dict[index]    \n","  prob=p[index]\n","  print('for file', image_name, ' predicted class is a', flowers_class,'with a probability of',prob)\n","  img = image.load_img('/content/drive/My Drive/42028/Assignment2/Image_Detection/Flowers17_Data/jpg/' + image_name, target_size=(224, 224))\n","  plt.imshow(img)\n","  plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"3nt7HVP_eWs2","executionInfo":{"status":"ok","timestamp":1652231993703,"user_tz":-600,"elapsed":193114,"user":{"displayName":"Callum Freeburn","userId":"02892497511592552319"}},"outputId":"6eb7576a-56e8-423d-f64b-b06b1125c8d1"},"execution_count":null,"outputs":[]}],"metadata":{"colab":{"collapsed_sections":[],"name":"Image_Detection_Flowers17.ipynb","provenance":[],"authorship_tag":"ABX9TyPOh1OBz5DRRdesDB8G2ZYQ"},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"},"accelerator":"GPU"},"nbformat":4,"nbformat_minor":0}