create_augmented_data.ipynb

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  "nbformat_minor": 0,
  "metadata": {
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.5-final"
    },
    "orig_nbformat": 2,
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "colab": {
      "name": "create_augmented_data.ipynb",
      "provenance": [],
      "toc_visible": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LlUqvd-M65bO"
      },
      "source": [
        "# Check if we in colab or local machine"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X9yPDE3X5fcK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a918c006-3ac7-49d9-ee0f-aef80aa5ae66"
      },
      "source": [
        "if 'google.colab' in str(get_ipython()):\n",
        "  !pip install split-folders\n",
        "  print('Running on CoLab')\n",
        "\n",
        "  from google.colab import drive\n",
        "  drive.mount('/content/drive')\n",
        "\n",
        "else:\n",
        "  print('Not running on CoLab')\n",
        "\n",
        "RunningInCOLAB = 'google.colab' in str(get_ipython())"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting split-folders\n",
            "  Downloading https://files.pythonhosted.org/packages/b8/5f/3c2b2f7ea5e047c8cdc3bb00ae582c5438fcdbbedcc23b3cc1c2c7aae642/split_folders-0.4.3-py3-none-any.whl\n",
            "Installing collected packages: split-folders\n",
            "Successfully installed split-folders-0.4.3\n",
            "Running on CoLab\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Tpe8opWw5fcJ"
      },
      "source": [
        "# Import"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1N7UL3NL5fcJ"
      },
      "source": [
        "import os\n",
        "import pathlib\n",
        "import tensorflow as tf\n",
        "import IPython.display as display\n",
        "from PIL import Image\n",
        "import IPython.display as display\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import splitfolders\n",
        "import shutil\n",
        "import random"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hQHkqRbE5fcL"
      },
      "source": [
        "# Functions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2giHdD_m5fcL"
      },
      "source": [
        "def visualize(original, augmented):\n",
        "  fig = plt.figure()\n",
        "  plt.subplot(1,2,1)\n",
        "  plt.title('Original image')\n",
        "  plt.imshow(original)\n",
        "\n",
        "  plt.subplot(1,2,2)\n",
        "  plt.title('Augmented image')\n",
        "  plt.imshow(augmented)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E1j2CBN95fcL"
      },
      "source": [
        "# Gets the bounding box for only the breast, centered on the y axis\n",
        "def get_boundary(img):\n",
        "    idx = 0\n",
        "    right = 0\n",
        "    left = 224\n",
        "    for x in img.numpy():\n",
        "        for y in x:\n",
        "            idx += 1\n",
        "            if y[0] >= 50 and idx > right:\n",
        "                right = idx        \n",
        "        idx = 224\n",
        "        for y in reversed(x):\n",
        "            idx -= 1\n",
        "            if y[0] >= 50 and idx < left:\n",
        "                left = idx\n",
        "        idx = 0\n",
        "\n",
        "    # bounding box\n",
        "    y_min = (img.shape[0]-(right-left))//2\n",
        "    x_min = left\n",
        "    y_max = img.shape[0]-y_min\n",
        "    x_max = right\n",
        "    # print(right, left)\n",
        "    return x_min,y_min,x_max,y_max"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a-6mJRKt5fcL"
      },
      "source": [
        "IMG_WIDTH, IMG_HEIGHT = 224, 224\n",
        "IMG_AUGMENTED = 10\n",
        "def generate_images(data_dir, aug_directory, aug_type, aug_func, aug_params, add_plain_dataset=True, exclude_original=False):\n",
        "    data_dir = pathlib.Path(data_dir)\n",
        "    sample_shown = False\n",
        "    # Generates new augmented images\n",
        "    if aug_type != 'plain':\n",
        "        for class_name in CLASS_NAMES:\n",
        "            # List all the images in the given directory (It should be Splitted_Data/Train/plain)\n",
        "            images_path = list(data_dir.glob(class_name+'/*.png'))\n",
        "            \n",
        "            for image in images_path:\n",
        "                try:\n",
        "                    # Copy the images in the directory of the augmented img\n",
        "                    img_name = str(image).split('/')[-1]\n",
        "                    img = tf.io.read_file(str(image))\n",
        "\n",
        "                    if add_plain_dataset == True:\n",
        "                        # Copy image to augmented directory\n",
        "                        fname = tf.constant(aug_directory+'/'+class_name+'/'+img_name)\n",
        "                        fwrite = tf.io.write_file(fname, img)\n",
        "\n",
        "                    # Check if the image is original or not (the image name doesn't start with one of the augmentation type)\n",
        "                    output = np.prod([(IMG_AUGMENTED if img_name.startswith(aug_type) else 1) for aug_type in augmentation_type])\n",
        "                    # Check if the augmentation type we did is the same that we want to apply: if an image is vertical flipped, we don't want to apply the vflip to that image, bcs it will produce the original image\n",
        "                    already_augmented = aug_type in img_name\n",
        "                    # If I don't want to apply the augmentation to the original\n",
        "                    if not exclude_original or (exclude_original and output == IMG_AUGMENTED and not already_augmented):\n",
        "                        img = tf.image.decode_png(img, channels=3)\n",
        "                        if aug_type == 'crop':\n",
        "                            x_min,y_min,x_max,y_max = get_boundary(img)\n",
        "                            im = Image.open(str(image))\n",
        "                            im = im.crop((x_min,y_min,x_max,y_max))\n",
        "                            im = im.resize((224,224))\n",
        "                            im.save(aug_directory+'/'+class_name+'/'+aug_type+'_'+img_name, \"PNG\")\n",
        "                            \n",
        "                            # Show sample\n",
        "                            if sample_shown == False:\n",
        "                                sample_shown = True\n",
        "                                display.display(im)\n",
        "                        else:\n",
        "                            aug_img = aug_func(img, *aug_params)\n",
        "                            enc = tf.image.encode_png(aug_img)\n",
        "                            fname = tf.constant(aug_directory+'/'+class_name+'/'+aug_type+'_'+img_name)\n",
        "                            fwrite = tf.io.write_file(fname, enc)\n",
        "\n",
        "                            # Show sample\n",
        "                            if sample_shown == False:\n",
        "                                visualize(img, aug_img)\n",
        "                                sample_shown = True\n",
        "\n",
        "                except Exception as error:\n",
        "                    print(error)\n",
        "                    continue"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "adfP5tCQ5fcL"
      },
      "source": [
        "# Path"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zwC2pFZD5fcL"
      },
      "source": [
        "if RunningInCOLAB:\n",
        "    parent_directory = '/content/drive/MyDrive/Colab Notebooks/'\n",
        "else:\n",
        "    parent_directory = '.'"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RlDpynrq5fcL"
      },
      "source": [
        "# Create Directories"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8rJJdLUp5fcL"
      },
      "source": [
        "CLASS_NAMES = ['Density4Benign', 'Density1Benign', 'Density3Malignant', 'Density3Benign', 'Density4Malignant', 'Density2Benign', 'Density1Malignant', 'Density2Malignant']\n",
        "\n",
        "augmentation_type = ['plain', 'crop', 'vertical_flip', 'horizontal_flip', 'brightness', 'crop_vflip', 'crop_vflip_hflip', 'crop_vflip_hflip_brightness']\n",
        "\n",
        "test_set_aug_type = ['plain', 'vflip_hflip_brightness']"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ekn_1YHz5fcL"
      },
      "source": [
        "def create_class_dir(directory, aug_type):\n",
        "    for class_name in CLASS_NAMES:\n",
        "        try:\n",
        "            os.mkdir(os.path.join(parent_directory,directory+'/'+aug_type+'/'+class_name))\n",
        "            print(class_name,\" directory created\")\n",
        "        except FileExistsError as error:\n",
        "            print(error)\n",
        "            continue"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wq0R5gHa5fcL"
      },
      "source": [
        "def get_files_from_folder(path):\n",
        "    files = os.listdir(path)\n",
        "    return np.asarray(files)\n",
        "\n",
        "def train_val_split(path_to_data, path_to_train_data, path_to_test_data, train_ratio):\n",
        "    # get dirs\n",
        "    _, dirs, _ = next(os.walk(path_to_data))\n",
        "\n",
        "    # calculates how many train data per class\n",
        "    data_counter_per_class = np.zeros((len(dirs)))\n",
        "    for i in range(len(dirs)):\n",
        "        path = os.path.join(path_to_data, dirs[i])\n",
        "        files = get_files_from_folder(path)\n",
        "        data_counter_per_class[i] = len(files)\n",
        "    test_counter = np.round(data_counter_per_class * (1 - train_ratio))\n",
        "\n",
        "    # transfers files\n",
        "    for i in range(len(dirs)):\n",
        "        path_to_original = os.path.join(path_to_data, dirs[i])\n",
        "        path_to_save_test = os.path.join(path_to_test_data, dirs[i])\n",
        "        path_to_save_train = os.path.join(path_to_train_data, dirs[i])\n",
        "\n",
        "        #creates dir\n",
        "        if not os.path.exists(path_to_save_test):\n",
        "            os.makedirs(path_to_save_test)\n",
        "\n",
        "        if not os.path.exists(path_to_save_train):\n",
        "            os.makedirs(path_to_save_train)\n",
        "\n",
        "        files = get_files_from_folder(path_to_original)\n",
        "        # moves data into test folder\n",
        "        for j in random.sample(range(0, int(data_counter_per_class[i])), int(test_counter[i])): # take random n (test_counter) unique numbers within the range [0,number_of_img]\n",
        "        # for j in range(int(test_counter[i])):\n",
        "            src = os.path.join(path_to_original, files[j])\n",
        "            dst = os.path.join(path_to_save_test, files[j])\n",
        "            shutil.copy(src, dst)\n",
        "        \n",
        "        # moves data into train folder\n",
        "        for j in random.sample(range(0, int(data_counter_per_class[i])), int(data_counter_per_class[i]) - int(test_counter[i])):\n",
        "        # for j in range(int(data_counter_per_class[i]) - int(test_counter[i])):\n",
        "            src = os.path.join(path_to_original, files[j])\n",
        "            dst = os.path.join(path_to_save_train, files[j])\n",
        "            shutil.copy(src, dst)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vV_VvKCF5fcL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "556d2230-49cb-4f88-d88b-ab32a56ed14c"
      },
      "source": [
        "try:\n",
        "    # Create Splitted Dataset directory\n",
        "    path = os.path.join(parent_directory, 'Splitted_Dataset/')\n",
        "    os.mkdir(path)\n",
        "    print(\"Splitted_Dataset directory created\")\n",
        "except FileExistsError as error:\n",
        "    print(error)\n",
        "    \n",
        "try:\n",
        "    path = os.path.join(parent_directory, 'Splitted_Dataset/Train/')\n",
        "    os.mkdir(path)\n",
        "except FileExistsError as error:\n",
        "    print(error)\n",
        "\n",
        "try:\n",
        "    path = os.path.join(parent_directory, 'Splitted_Dataset/Test/')\n",
        "    os.mkdir(path)\n",
        "except FileExistsError as error:\n",
        "    print(error)\n",
        "\n",
        "# Create Test subdirectories\n",
        "for test_aug_type in test_set_aug_type:\n",
        "    try:\n",
        "        os.mkdir(os.path.join(parent_directory,'Splitted_Dataset/Test/'+test_aug_type))\n",
        "        print(test_aug_type,\"Test directory created\")\n",
        "        create_class_dir('Splitted_Dataset/Test/', test_aug_type)\n",
        "    except FileExistsError as error:\n",
        "        print(error)\n",
        "        create_class_dir('Splitted_Dataset/Test/', test_aug_type)\n",
        "        continue\n",
        "\n",
        "# Create subdirectories\n",
        "for aug_type in augmentation_type:\n",
        "    try:\n",
        "        os.mkdir(os.path.join(parent_directory,'Splitted_Dataset/Train/'+aug_type))\n",
        "        print(aug_type,\" directory created\")\n",
        "        create_class_dir('Splitted_Dataset/Train/', aug_type)\n",
        "    except FileExistsError as error:\n",
        "        print(error)\n",
        "        create_class_dir('Splitted_Dataset/Train/', aug_type)\n",
        "        continue\n"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Test/'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Test/plain'\n",
            "Density4Benign  directory created\n",
            "Density1Benign  directory created\n",
            "Density3Malignant  directory created\n",
            "Density3Benign  directory created\n",
            "Density4Malignant  directory created\n",
            "Density2Benign  directory created\n",
            "Density1Malignant  directory created\n",
            "Density2Malignant  directory created\n",
            "vflip_hflip_brightness Test directory created\n",
            "Density4Benign  directory created\n",
            "Density1Benign  directory created\n",
            "Density3Malignant  directory created\n",
            "Density3Benign  directory created\n",
            "Density4Malignant  directory created\n",
            "Density2Benign  directory created\n",
            "Density1Malignant  directory created\n",
            "Density2Malignant  directory created\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/plain'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//plain/Density2Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/crop'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop/Density2Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/vertical_flip'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//vertical_flip/Density2Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/horizontal_flip'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//horizontal_flip/Density2Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/brightness'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//brightness/Density2Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/crop_vflip'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip/Density2Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/crop_vflip_hflip'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip/Density2Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train/crop_vflip_hflip_brightness'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density4Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density1Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density3Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density3Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density4Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density2Benign'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density1Malignant'\n",
            "[Errno 17] File exists: '/content/drive/MyDrive/Colab Notebooks/Splitted_Dataset/Train//crop_vflip_hflip_brightness/Density2Malignant'\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w7gFNIjY5fcM"
      },
      "source": [
        "original_data_dir = parent_directory+'/Dataset'\n",
        "train_dir = parent_directory+'/Splitted_Dataset/Train1/'\n",
        "plain_train_dir = parent_directory+'/Splitted_Dataset/Train1/plain/'\n",
        "test_dir = parent_directory+'/Splitted_Dataset/Test/'\n",
        "plain_test_dir = parent_directory+'/Splitted_Dataset/Test/plain'\n",
        "data_dir = plain_train_dir"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uqk-RazD5fcM"
      },
      "source": [
        "# Split the DataSet in 80% train 20% test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HizrtHqA5fcM"
      },
      "source": [
        "train_val_split(original_data_dir, plain_train_dir, plain_test_dir, 0.8)"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ovk6gY0I5fcM"
      },
      "source": [
        "# input_folder = \"./Dataset\"\n",
        "# output = \"./Splitted_Dataset\" #where you want the split datasets saved. one will be created if none is set\n",
        "\n",
        "# splitfolders.ratio(input_folder, output=output, seed=42, ratio=(.8, .2)) # ratio of split are in order of train/val/test. You can change to whatever you want. For train/val sets only, you could do .75, .25 for example."
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fphtp8_RcQw-"
      },
      "source": [
        "# Augment Train Set"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pDKjN5X55fcM"
      },
      "source": [
        "## Generate and save vertical flip images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8NOxHi6Z5fcM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 216
        },
        "outputId": "482d6fc1-74ea-44c8-ff69-26c9d4946b58"
      },
      "source": [
        "vflip_train_dir =  train_dir+'vertical_flip/'\n",
        "generate_images(data_dir, vflip_train_dir, 'vertical_flip', tf.image.flip_up_down, [])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WNRH2Cic5fcM"
      },
      "source": [
        "## Generate and save horizontal flip images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RAhvrY0l5fcM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 216
        },
        "outputId": "0aefe5fb-c873-483c-f8a0-4033a6b4b356"
      },
      "source": [
        "hflip_train_dir =  train_dir+'horizontal_flip/'\n",
        "generate_images(data_dir, hflip_train_dir, 'horizontal_flip', tf.image.flip_left_right, [])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YjXh-WJS5fcM"
      },
      "source": [
        "## Brightness"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t_rcVv3d5fcM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 216
        },
        "outputId": "e2b8501a-0e16-40f7-e7ac-1a7c18ea8cd2"
      },
      "source": [
        "brightness_train_dir =  train_dir+'brightness/'\n",
        "generate_images(data_dir, brightness_train_dir, 'brightness', tf.image.adjust_brightness, [+0.3])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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z2qGkrqsKulwuU6lUKBQKyQLBhUKBSqXSYfHYVDOI/oEMDQ0xNDSU1a06VyGubScLctG424mS1Jqxa0najiaNO5bL5Y7BIZo2Zl3edEXQ4du7du2ir68v47t2rhZc204W5KJxV2x8Ub9r/NEOzdaKotOlFovFJH2s1WrR19fHwMBAR+eTtZq2bNni8Umnq7i2nW6TiwCdWjPpbcVisSN1rFKpJHnANttAj9XKoC/dXy6Xk7zhEAKVSoVXvepVnD592lewcVYc17aTBblo3KEzFTI9LDudaaCrxtuYpIpff1etVjvmyrYdWq1Wi82bN7NlyxZGR0czuV/n6sG17WTBFTXuInIEmARmgGYI4Q4R2QT8GbAbOALcF0I4N895ks9W/DaLoNVqJZkAxWIxmRJVLR/tmNJVaTQjIX0NjVMWi0V2797N2bNnk+wEx1GWS9sW17bTTZYj5v6PQwi3hRDuiL8/CDwZQrgFeDL+Pi9pa8bGKDWLwFoq9lg7AjBtGdkOKztoxFo4jjMHrm1n1bISHap7gEfjz48C9y70h+nh12qdVCqVxF0VEZrNZiJyK25oT69aKpWSTie1itLH9vX1sXv3bs8ucBaKa9tZNVxpzD0AnxeRAPy3EMLDwNYQggb7TgJbZ/uhiDwAPACwdu3ajrk3gA5LxLqmat3YTiU9PoRAX19f4poCHdZMvV5PFhjW81x77bVs3bqV4eHhK3wUTo+xLNoeGhpybTuZcKWN++tCCCMici3wBRF50e4MIYS4clxCXFkeBhgaGgrWVbVWjg67hnZMUY/R+TfU2mk2mx2DQICkcyqEQLlcpq+vj6mpqSRuWSqV2L17N2fOnKFarV7h43B6iGXR9s033+zadjLhihr3EMJI/H5KRB4HXguMici2EMKoiGwDTi3kXHb+DKBjGLWKWFO+dJ+IJPFKu8iB/l7zhbUy6ECQQqFAtVpNBods2rSJbdu2cfjw4Y5Rf87Vi2vbWe0sOeYuImtFZL1+Bn4ceA54AtgbH7YX+Ox851LLJO1WxufucF3TQ7A1Jay/v5++vr5kux3hl+6s0uHc5XI5qSQ7d+6kUqks9XE4PYRr2+kFrsRy3wo8HouqBHwyhPC/ReRrwGMi8g7gKHDfggsTWy2a8qVWC0C5XE5ijSKSVJZGo0GlUkncVbsGpT1HetEDtYyAxMLZvn07hw4duoJH4vQIy6ZtbXRd2063WXLjHkJ4GXj1LNvPAm9Y7Pk0LUxjjCpW3W4rh+2AssO39V1Fnx4ZqAM97HuhUEjOt3PnTkZGRpienl5s8Z0ewrXt9AK5mltGB27YCZKAjg4o7TjSY3R1GiCZeElTynQ1eeicnMxWHBuz3LBhA9dff33HoCrHWQ5c2063yU3jrqlfOpmSboP2XO8qYDtdqqaZQdv1tWlkQHJOayVp5bFLlxUKBbZv3+7xSWfZsAORXNtON8lN464WhQraClQtlnSHlMYjNf/XTqmqMUfdphVIrZr0serCbt68mW3btmX2HJzewurVte10k9w07raTyLqVmiWg1ocKuVwuJyvUaKWp1WpJh5VWEu1wsulkuk8rhl5T3eYbbrjBR/Y5y4Zr28mCXDXu1vpQsWu+rs0FhnYKmFYQG0tUV1hdVT2vDvWuVCpJepnGN7UDamZmhsHBQbdwnGVBwy2ubafb5KJxT0+SZK0YtVq0gjQajWTAhp0TWy0hO+e1xhxtp5SNT6Y/Ax25wf39/Vk+FqcHcG07WZGLxh3ocFPtjHd2cQJop4RB2ypS60RR8QMdHVN2Zj2tZFoJyuUy5XI5ufbmzZt9PUpnWXBtO1mQi8ZdXVAVbnqqUzuST2OJmg6mc3DoSECtFNCOO9rfapzSpqDZWKi1sHbt2uWryTtXhGvbyYpcNO5Ah0hDCB3upF1XMj0gxA7X1pijnRrVDs9WwWsqme5Xy8m6zK1Wi40bN/qc2M4V49p2siAXjbsKGdqxQ/3c19d3yWrwmlEgIlSrVaanp5MKAu1BHXZItuYQWwtHK4Ber1Qq0dfXl1hVpVKJ7du3u4XjXBGubScLctG42wmRbCeQblfh2ziiWilpV1RjjzZLAOgQuq1IQJJzrPFJW4GGhoZYv359Bk/F6RVc204W5KZx17mqNcZo91nLBtqj9GyHU9oFtRUlPTWq7XRSd1krh5YDog6rgYEBtm6ddU0Gx5kX17aTFblo3K0ggWS6Ut3XbDY7coNbrVYSl7Sxy0ajQa1Wo1arUa/XE4vHdmJB20rSeKVaVFpxdJCHWknXXXddMirQcRaLa9vJglw07kCSzlWr1ZKpTe3AD5sHrPFFtWbK5XISU1ShTk1NUavVEjcU6HCJ9TzNZjOpEGrV2Bn1Wq0Wg4OD3vnkLBnXtpMFuWjcRYTp6enEIlH3UvdpJdBZ89QN1XiijV3qb0qlUlKpNA3NZhfokG27XSuIPa9Wwq1bt3bkITvOQnFtO1mQi8Yd6Jh72s6HoZVBxWlH5+l8Gmr56PGNRiMRerPZTOblUJHbzqx0DrC6umvWrKGvry85/9DQEOvWrcv4KTmrEde2kwW5aNxDCJekhelADpsGBu1Z9nQdyampKer1ehK/tCvTaCxfLSPtiNKcYJsXbDMPdODJwMAAEHU+rV27lsHBwe4/HGfV49p2siA3jfv09HTS+aMZBunFCqxlUyhEa0tqLFEtmHTamH0BSQ6wvqA9a59eVyuiVhp1X7dt29ZRGR1nPlqtlmvbyYTcjGDQld9VcCrAtGWjAzBsvLHVanUscqAVSb9DW+TQnsMjPXJQrRq9jrrMaj1t3LiR/v5+pqamuvtwnFWLiLi2nUzIzb/qQqGQZAqoe6nWih15p8dq3BJIXFO1WPr6+jqsII1batqZzSO2nUvpji57nRACAwMDbNq0KbNn5KxOXNtOFuSmcVex1+v1JLNAhT/bqu/pEXoqfrWO1DqxCxzYOGTandVz29n6rKusFXPTpk0d2QuOczlUg65tp9vkJiwD7aHT+q6VwIoWSCyPNDYrQQWtFUsnXbJDuLVyaEVRt1WPs3Nra+XZsGEDlUrFV5F3FoVr2+k2uWncbSxQhaxxQbtPV63RGGK5XO6IOarbCZH4dT4N/W6nVrUvtXDsUG+1bsrlMrVajWKxyLp161izZo1XAGfBuLadLMhFWEYFZ+eqtu6qzdNVN7JWq1GtVqnX60Dn+pT6/XLTn2pFgPbEZdPT00xPTycVRY/VOUFCCFQqFZ9syVk0rm2n28zbuIvIx0TklIg8Z7ZtEpEviMhL8fvGeLuIyO+JyEEReVZEbl9oQaybqj34QEdnk34HEqunXq8zPT2dDN+2FcYOBrFxTbuwcDo+qfN7qAWUnk1PY5OeNrb6cW27tnuZhfwVHwHelNr2IPBkCOEW4Mn4O8DdwC3x6wHgwwsqhBmMkRaWitkO3NDj026nTRnTfXb9SBvjVAtG3WJ1hXWgh8Y+7VStEFlCGzZs8OHavcEjrLC2VUuubafbzNu4hxC+BLyS2rwHeDT+/Chwr9n+JyHiaWBQROZdal1EkkEb9qVxR7uggArbfi8Wi4kFo6LWyZLswsI2DqkdS61WK0kvUxfXDvfWY1XwIQTWr1/PmjVr5rstJ+e4tl3bvcxS/a+tIYTR+PNJQCeF3g4Mm+OOx9vmL4ixKlT06UEe6k6qmFXwOpWpnkPjiLoOpeb8ple90Zn66vV6hxurbq4d/q0Wjs6J7TnBPYtr27XdE1xxtkwIIYhImP/ITkTkASL3lrVr114SK7STKakwbX5wCO35rjXtC9rDvfWzjupTq8YuQxaXg2az2TGyTy0aHQlo7jWxeK699lqGh4c7ru30Fsuh7aGhIde2kwlLtdzH1CWN30/F20eAnea4HfG2SwghPBxCuCOEcEd/fz+NRiPJItDZ7nT+a7VYtKNJrRO1fnSb7WxKD+JoNBqJFaPHqLWiI/X02mpF9ff3JxVFxa8dVxs2bGDt2rVLfHxOjllWbV9zzTWubScTltq4PwHsjT/vBT5rtt8fZxbcCUwYF/eyqGjtYgU2PqiDLjTOCHR0LtlKAu3FC5IbjdPFdBX5SqWSCF8rg7rCdvY9zQ+2KWYhRNOm+jSpPYlr27XdE8wblhGRTwF3AVtE5DjwG8D7gMdE5B3AUeC++PDPAfcAB4Ep4O0LLYhaDRo71FigFbg9TuONuk0zC2wsUyuAWkh2SLe+rDuqrqpWABvDtGXRirR+/foOS8pZXXRD26ovcG073WXexj2E8LY5dr1hlmMD8M6lFETFaadCtb3+dpIj+0rHF3WotbqfOnmSrRwqeJtnbHOC1dLRCmIrqM0RXrt2bVJGZ/Xh2nZt9zK5mX7ADsmGdqzRCl+Fp5aGCl6xrq12OOk221llJ2my59aKYbMXdLuudmOtJM1i8ArgXA7XtpMFuWjcVVQaf7QiU0vHZhWkLZL0cGx1Y2u1WkfqWblcTuKedtV5O6zbit+OBNTr6HVtGR1nLlzbTlbkonEHZrVk7MRKKnJbQfRdxRlCoF6vJ+6qdT3VCrIubKvVShYm1k4ta/lAp0trLR87n4fjXA7XtpMFuWjcrdViRWUFZy2K9MRIuk0tEq0wuqqNWj5pAUNUCRqNRmL9aMeTtWqsG6vutd3mOHPh2nayIheNO7R7+VVY+q77oL0OpE3lsr+12QYqXmsRad6vWjr6Gxvr1G16jJ2Nz2YeTE9PIxLN2aGz9zlOGhtLd2073SRXjbtaJyG0R+hZq0KP0/kwdABHuiJoR5OuMm8ri1YEdXOhHcvUCpOueNZttutaWivJcebCte1kQW4a92az2TE3tRWhzfvVSpIe5GHjmPZYtWh0eTMVru63+b42D9iuiKMVQy0dO4z8mmuuYd26dRQKBWq1GhMTE27tOB24tp0syE3jDnTE+qz41L2EdoaBClUnQrLTmKYzD9TlLBaLNBoNarXaJfN76HF6Ha2Q+lnRYwYGBigUCtx4440dq+aMj4+zf/9+zp8/352H5uQa1ZZr2+k2uWncbeqXrQjWkrHHqduqQrVur41tWre1XC7T39+fHGfze2ezXkKIholDlPer6EjDZrPJ4OBgx9Dw9evXUyqV2LdvH9VqtctP0ckjrm0nC3LTuFv3Mb1dXVcVZqFQoFKpUCqVktVloB3b1Filur06Kq/RaFAul5Nj0xVErSI72k/PowsMq8uqFk+lUunINw4hsGPHDk6cOMHRo0e78uycfOPadrIgFz0m6ZxaFbLtcLKz2llXVytEuVxO5qNWV1KzA2wsUgWtMUt1d7VjyU7uZGfZs5kJmkqmlcW+SqUSa9euZffu3Z5K5lyCa9vpFrmx3K1VYd1UaPfsW9dUXUprVah4NdaYnkPDrkijFo3GNm0aWjpLwF5XB6NoJ9Zc9+LDth241GJ2bTvdIjeNu7U60j3+0HZp1YW1loP9nbq3ut1aQNCubDbmqaLW82rlUvdUB3bYBYl1+Lf1OvSYixcvMjw8fIlH4lyduLadLMhN467uoK4ckx74AZe6tLYzSrGCtyPyoD1iz8Y59bxpl1ivZeOaOqfH9PQ09Xq9YyEEvUa9XufAgQOMjMy6joNzFeLadrIgV417eu4LO2GSdSdtRZgrd1ePU3FrfFK3q+DVpVX0fOrmqtWk7u7k5CRnz55NUs80Dioi1Go1jhw5wqFDh9x1dQA6dAqubad75KJxVzHbvFyNAabdWY1f2n1aEezIPxW8CtcOr7ar1IhEw6zT7qrNKlArqdlscubMGfbv3w/QEedsNptUq9VkjUvHUVzbThbkonG38TsrbmuxAB3xyHSOsG7T84UQqNVqHa6uzRwIIdDX15e4o5pXDDAwMHDJBE56/vHxcS5evLiyD8TpSVzbTjfJReMObZGpSFX8IUTzZKiVonFKa/WoUO0kSHbAhx2Zp9fQ77VarSOuqLPtadzRVphms8m5c+e6+lyc1Y9r28mC3DTuQIeg1VJRC0bFrCK3sUebbWDn0FB31mYUqOurriiQuKb2uPQowkajwfj4OJOTk119Jk5v4Np2uk1uGvd09oDNv4VOtzVdUdLurB5jF0RIL4pg45vWCtJ5NCDKDqhUKoQQqFarnDlzxjuTnEWhjapr2+k2uRihCu2efGgL2fb6q4Nih24AAA1hSURBVEurFo51bTWVK90hZSuIil+vYd1ciP65VCoVCoUC9Xo96WzSCqEVwPN7ncVgs17Ate10j1xY7ipQFay1dqAdR9QcXh1ebS0cfdfBGDYeqedKp5TZEX2aFaADOWzmQbPZZGxszGOSzqJxbTtZkYvGHTpH4tlsAfvSCqGdROn4pf2tHSyils1s8c30wBFoj8bTz1NTUxw7dqxjelTHWQh20JBr2+kmuWjc0+6pWhxAMtcFkLiROhDDZhbo8WqR6Ci+crmciNvOzwF0VCKdVc/GLCFybY8ePeqWjbNkXNtOFuSicYd2Hm86ngjtRQ3UqlEBq9WiQrdZAlb0trPKurN6Xd2u4tdKIyJMTEz4XBrOFeHadrJg3g5VEfmYiJwSkefMtodEZERE9sWve8y+94rIQRHZLyJvXHBBTBzSDrCwOb26zx6nIrfzXNvOqOnpaaanp2k0GolLaxdAAJIKlB7a3Ww2efnll5mYmFjobTirCNe2a7uXWUi2zCPAm2bZ/qEQwm3x63MAInIr8Fbge+Lf/KGIFBdTILtsWHzOS+KUetxs2QLpjih1VbWjSsUPdHQsTU9PJ+6vvk9MTHDs2LGkojg9xyOssLatVezadrrJvGGZEMKXRGT3As+3B/h0CKEGHBaRg8BrgS8v4DpJXq7GD21+rs3bVRfVdkTZOTase6puaLFY7Ig76ktdYjvIQxcdfuGFF5iamlrgrTurjW5oWzXq2na6zZXE3N8lIvcDzwDvCSGcA7YDT5tjjsfbLovN51VUsNqppNt0HUgVcLVaTUQM7cqU7nDSuKO6uPpZLR+Nfar1c+TIEUZHR6/g8TirGNe2s+pZ6iCmDwM3AbcBo8AHFnsCEXlARJ4RkWdqtVoiRLVirDD1pWtF6qAMXWvSZg+kV37XeGSj0UjmqlZrRo/VCqbnOXv2LC+++GIym55zVbGs2j5//rxr28mEJVnuIYQx/SwiHwH+Kv46Auw0h+6It812joeBhwE2b94c+vr6OlaaUWtDO5DUyrGdRTZtzI7GU0Erdlh2XOaOGGfyMEolpqameO6557hw4cJSHo2zyllubd90002ubScTlmS5i8g28/UtgGYbPAG8VUQqInIjcAvw1YWc0/bmqzBVuPE1k5fNGbaLHagLW6/XqdfriZtqhZ+uSHp+nSL1wIEDnDx5cimPxekBXNtOrzCv5S4inwLuAraIyHHgN4C7ROQ2IABHgJ8BCCF8R0QeA54HmsA7QwgLmo3IDq5IZw9o5bCDO2xGgT0mvbyYMlsKmm5T9/XIkSMcOHDAJ1C6SuiGtrWT1LXtdJuFZMu8bZbNH73M8b8F/NZiCmFTvFT4NqPATqpkh2UrNg6pv7OC10WArbDTlWpsbIznn38+GTHo9D7d0Hb8O9e203VyM0I1Pcgj/dm6mmoF2biinVhJO67sPlsx7Ox5xWKR06dP8/Wvf53z58+v6D06VyeubScLctO423UioXNBAcVmGdh5N3SNRzsvdnqlGcVaTaVSicnJSb71rW/5/BrOiqBWtWvb6Ta5adyBDrHbFC773Vo5IZ7VTt1Nm3JmXV79jcY+9XXu3Dm++c1vcvLkSZ9fw1lRXNtOt8lN456ON2ocUt3Qvr6+xJpRN1Xn3bBzbugAETvFqcY7bfbB5OQk+/btY3R01MXvrBjpcIluc207K00uGvd0h5K6l9Aeeq1DsjUFTEft2Vn0bAqZitrmDWsleeWVV9i3bx8nTpxw8TsrjmvbyYJcNO7QmaerFogduq0WUL1e73BPoe3eKtr5pOhovZmZmSQO6eJ3uoVr28mC3DTumgmg82IAHbFFtXpKpajIs1k1QIeFpPu14pw6dYr9+/e7+J2u4tp2siAXjbtaMTaHFzpH8dmYInR2StlRfzYHWM938eJFRkZGePHFF33+aqfruLadLMhF425j7mqNpAU+W/7vbPm91sqZnp5mfHycQ4cOceLECR/E4XQd17aTFblp3NetW9exKIFuh/YI1tlG8CnWxa3Vapw9e5bh4WHGxsaYnJzs2r04jsW17WRFLhp3aC/WofHGtOjtBEmKij7E059Wq1XGx8cZHh5mdHSUarXq8Ucnc1zbThbkqnHXjie1cGxWgJ2TQ4/XXOBqtcqZM2cYHR1lbGyMWq2W1W04ziW4tp0syEXjHkKgVqslAk93Ptm8XrvSzPT0dCL8c+fOedzRyR0aSnFtO90mF427LikGdFgw+t2uCTkzM8PU1BSnTp1ibGyM8+fPu3vq5BbXtpMVuWnc1bqBduzRdkLNzMxQrVYZGxvj9OnTXLx40Vdud3KP9UrBte10j1w07hpj1MmRdOIkrQBTU1OMjY1x8uTJxApynNWAa9vJilw07poLbFeSUWv+9OnTnDhxgsnJSXdRnVWJa9vJglw17hp7bDabTExMcOTIEc6dO+fCd1Ytrm0nK3LRuANJmlir1WJ4eJiRkRF3U51Vj45AdW073SYXjbumiDWbTYaHhzl8+LAv5Ov0DK5tJwsK8x/SPU6fPu3id3oKzY5xbTvdJheNu4hQrVY5fPhwMiWq4/QKrm0nC3LRuIcQOHbsmK/Q7vQkrm0nC3LRuLdaLV/I1+lJXNtOVuSiQ1VH6DlOr9FsNn1aXicT5rXcRWSniHxRRJ4Xke+IyC/E2zeJyBdE5KX4fWO8XUTk90TkoIg8KyK3z3eNer3uw62drtMNbTcaDde2kwkLCcs0gfeEEG4F7gTeKSK3Ag8CT4YQbgGejL8D3A3cEr8eAD483wW8o8nJiBXXts/m6GTFvI17CGE0hPCN+PMk8AKwHdgDPBof9ihwb/x5D/AnIeJpYFBEti17yR3nCnFtO73MojpURWQ38BrgK8DWEMJovOsksDX+vB0YNj87Hm9znNzi2nZ6jQU37iKyDvhz4N0hhI68rhClAiwqHUBEHhCRZ0TkmcX8znGWm5XUtodlnKxYUOMuImUi8X8ihPAX8eYxdUnj91Px9hFgp/n5jnhbByGEh0MId4QQ7lhq4R3nSllpbff19a1c4R3nMiwkW0aAjwIvhBA+aHY9AeyNP+8FPmu23x9nFtwJTBgX13Fyg2vb6WUWkuf+j4B/DXxbRPbF234FeB/wmIi8AzgK3Bfv+xxwD3AQmALevqwldpzlw7Xt9CySh5FzIpJ9IZyeJoQg8x+1/AwODobXv/71WVzauQp46qmnGB8fn1XbuZh+wHEcx1levHF3HMfpQbxxdxzH6UG8cXccx+lBvHF3HMfpQbxxdxzH6UG8cXccx+lBvHF3HMfpQbxxdxzH6UG8cXccx+lBvHF3HMfpQfIyt8xp4CJwJuuyAFvIvhx5KAP0Tjl2hRCGlqswi0FEJoH9WVw7Ra/8LZeLXinHnNrOReMOICLP5GFu9zyUIw9l8HIsD3kpu5fj6iuHh2Ucx3F6EG/cHcdxepA8Ne4PZ12AmDyUIw9lAC/HcpCXsns5Oun5cuQm5u44juMsH3my3B3HcZxlIvPGXUTeJCL7ReSgiDzY5WsfEZFvi8g+EXkm3rZJRL4gIi/F7xtX4LofE5FTIvKc2TbrdePFmH8vfj7PisjtK1yOh0RkJH4m+0TkHrPvvXE59ovIG5exHDtF5Isi8ryIfEdEfiHe3vVnspy4tpNtV6W2M9d1CCGzF1AEDgGvAvqAbwG3dvH6R4AtqW3vBx6MPz8I/PYKXPdHgNuB5+a7LtGCzH8NCHAn8JUVLsdDwC/Ncuyt8d+nAtwY/92Ky1SObcDt8ef1wIH4el1/Jsv4bF3b81y317Wdta6zttxfCxwMIbwcQqgDnwb2ZFymPcCj8edHgXuX+wIhhC8BryzwunuAPwkRTwODIrJtBcsxF3uAT4cQaiGEw8BBor/fcpRjNITwjfjzJPACsJ0Mnsky4tqe/7o9re2sdZ11474dGDbfj8fbukUAPi8iXxeRB+JtW0MIo/Hnk8DWLpVlrutm8YzeFbuFHzOue1fKISK7gdcAXyFfz2SxZF1G1/bsZKLtLHSddeOeNa8LIdwO3A28U0R+xO4Mka/U9XSirK4b82HgJuA2YBT4QLcuLCLrgD8H3h1COG/3ZfxMViOu7UvJRNtZ6Trrxn0E2Gm+74i3dYUQwkj8fgp4nMgVG1NXKH4/1aXizHXdrj6jEMJYCGEmhNACPkLbPV3RcohImagCfCKE8Bfx5lw8kyXi2m6Ti79jFtrOUtdZN+5fA24RkRtFpA94K/BENy4sImtFZL1+Bn4ceC6+/t74sL3AZ7tRnstc9wng/rgn/U5gwrh0y04qxvcWomei5XiriFRE5EbgFuCry3RNAT4KvBBC+KDZlYtnskRc221y8XfstrYz1/WV9ggvQ4/yPUS9yIeAX+3idV9F1EP+LeA7em1gM/Ak8BLwN8CmFbj2p4jcwgZRXO0dc12XqOf8D+Ln823gjhUux5/G13k2Fts2c/yvxuXYD9y9jOV4HZFr+iywL37dk8UzcW27tpdL21nr2keoOo7j9CBZh2Ucx3GcFcAbd8dxnB7EG3fHcZwexBt3x3GcHsQbd8dxnB7EG3fHcZwexBt3x3GcHsQbd8dxnB7k/wNfcCj4/92pugAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DlSEvm1E5fcM"
      },
      "source": [
        "## Breast centered crop"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "tags": [],
        "id": "Fr1Y5-sf5fcM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "outputId": "14687301-3528-49eb-9a11-2c9ec81814a5"
      },
      "source": [
        "crop_train_dir =  train_dir+'crop/'\n",
        "generate_images(data_dir, crop_train_dir, 'crop', tf.image.crop_to_bounding_box, [])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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FlQDIHGSER9O4mOC2i3YRGR3NEXTash4O6+1TAk7RL5TbySIYky2sFHpmtVLAdPYtOiUGNVE+oWHLQHDO9bQQSg9ChA16nUH6mIUtIJGF+GxubvZptrZWZTSKPillmvR1ZlMNhGnk4WnR0oxPutgc8+7edhIwfzNNTwzIGjjKGcVsOR4/V8O9gq1WbSPaq898PNpM1KgSrWxy0km4kqwwSKyaRYcERSYtw3b5zvZAIVReq1fegKQTnQ2oZpHL4XT+lK1fu4AxHSFALuWzAjFZ8lXOuf5RbU9PvKwmGqPKDA7CjTZ56Ox3fi6MwsRyUTLo1mNYzaYdjodPxS3WRahCo3zAXQhlWGCg1GqIVxHHGt2kfaiwYZGYaaLH6Kt6sQXH6LHo7yaPLWE3ibZ+VsBV3Bh0JjOQTEINoNqg/DSscA8RcBe80FBj5pdWjr1kWcmRtCDYAJE8mrAs/YnMvRUkc2TxW+e/NoLd1dlCaz48qcXs39alWU+HmPlFhVEqYKQOKrO6cZ6lI2pSiGNealqO4KBUthzXTwVmVpMWtnENNWsBM6oclWpjZHZXQG7XfQOCDACNMletb84o4pDGlJyWjBBaRE1jushpdU/CyvAgBZLr4bh+hq2t4UEIQKlIJ8TjPySmWpw7Cll1nsOLQgQeYjyclcRpz6ceQS7yIIRBCJIFx1pQFbdObtPyRdGwCXY4rMtnBARIWLgyU4REQ0BgOOhvXQ2Dw2ol34LBs2IdtD2SlBXKKH96f41E/potTpNDxLKu6/qJ0sO1LK7VE6ZUSBCZAvKiWhUbqdcaVXl7AITBbCn2n34OkSND5OInz4Ck032e18hqxRhCj6SB8kUAw7kksR6Ox08UV65VhDfwfxrEnNsjzbtLTEfvhoATwDHlCxF2HkpgR3I1FbXcYIzVusFxXADMwZS1yYcxUnMgYMt6OF4/Zms7b6JHa5c6i2+0A809UelaEADB/GNUE1+aGtwTNAARSAChafVhzkG5NkH9BAC5swhF2Xo8nj9mayOFjQHsRU7jr54esIQCPUW5aKJsfFYFfOHhpqrZFDVF+oNR9ZNPJASZKu3EqMqTIJq0bRsWGdU4mtOEgK3Hh/P5MwIO8zDRla5CiukXBYjIoE3oWAmYHM/k3nlEUXL38Dja7rNpdppxAYD3uIqZi3OEGfRt2wVLpuABbTmePmHr18H9exp1tLDHdn9p715oBt4g0k643KeZ2ZwtZx56PICoSkwLMnPXCBb2SqKpBQKxHE+fKI9dlVk918jIlabGar7SvPgj4zGKKmwSiL011E2Uez1RWf8JxBqL6snKGBlGPRibdbLWUtiSiyf2XYqMux9Ox4/JzNovHd1NcoAfMy7RGcnKV1Q1XZT+a9DWyopIKMcquy0/DtaShSYDh4YVRBBU2DoZ/J18AmGH4+FjMlMCqpsfZZGc9D5GUSOmlGxpzj8ITXWaeA/vAUVolJFtRnm6l4BFwboHAIi0Zalkz5DOi3uvx9PhsKOzbwnoaRjy8emoGbJSqXixHJFRmeZ7MoLKW9YeFqrVrkKWnSM2wYnVF1EIDVUtQEy0kZiS+5asjaZ1U74qw+sjuWXL4Xg6+QeRmRUC4N0PFTFvvh/OvQS/U3fOnigqB2OTR5BP7NapYFSCWznVRsqL7pVFKs/Nlh7Y1ouEK2JZD6fTRxvNrIkHXQEAQBmrR5QdBuaYpvxrErnd/C+uz9LZ/GFmRNOSh3lMZzPGP9iq18LLvQuVa7xaPmX3EaAth+Pp/IGEa1ZHDqc9obAbyMxjmtrotFtBaFTOW9fTVERqCnFU7yMpRRo9Jf1KtjdoQXIAcvHkaWquF98T5Ho6HT9YCrPOeRCfBjGDXNll3W4M1RsPaS7Wfy1fNz9iuxz9JNYPqx+jm+4oIqbszuuLy/E4UtTvCFjPwVhtw85FZ5wi686YIUxPtYxf1IqPcElaBgsXPqeQEYAHsV/KmGeVcDMwwWtxbdMH5dLoXFiRkwCBNrYcDh+VzKzVww7PZZo1hdRzqSJ36THSa9UySFuYNQnVLzU2XvjfIyYBtYQhfYcJUADINwGLJd02wF1bPKLyhtmHEshlPXyUZXqVm3jz9zWgnNSwL85/neCT09/nyyYBc4exWhBiWy+kmHBFyWRfUTbauq72ZzKzRqud5oaqQciJk9eAG0yRIjLACdPGCJn3Qm1bAmQpagJoWp8UkPCqrUL1nmVhxtRL3YsMJ6SogwDaevioJihCFuF1xcqIYmnNejMkVTxg+PMW2ztWt6ZHgmpydJTJlYS0g6sjxMK0I0npbGEtEdYQO1/HqCYp1BMFWw7rBwuXe+O4YiUJWylUNSgHY/53ur8D5KrbR0VMwyec04Omq/sjp/pYL6SdPXzn4rKsy5+LntbYjaAjYQFupUgJEe08zR650M0pQ68t6j5Uc5Who17aMXpPY5DjYR5b1aQqt2ootXOyzA1ZKeH6xwLntVzXaEBAPocyIcGzhcJk55O9dFdLQFURsCKJ8Zsi5tnmsgH9kVxUxkKDG0bpWtLhounYKwFtWdZ1+dNYr3tDnjOjRk3lImTzmzW1nayBAqpWIfb3GAlqdsAwDZCYqQyNWBzGS5Q4kFVtb2nqaBNpy5+3H12R2740bCabBJEVss3DPQUMtdxGPiNnUvoc7AhSki30bnnM7SkkxELeKW7FmalG5MybnQVKlPGvVQcEaeufs/Wriih1fRXSorMW0g/TNPBkgCkLLwNhSoemlHxuEhM/q0JgYextWQBX8qC2ZPEc0uQ0w1PsXv14BO/J33xNdr1bmx/obpPGwYBi0USqYbTEwFrwn46Vs9bpN4aWFRqkO/zGRlX3iHNl08rbWpY/krV1jxEhTDe9tgJr+ZjACKjeNiZjmukgbxxsNT1KumJLJTiwZdVyp0OqJ2OK9kxH/UXuW+1zU8QGAKbVz28LGH9Mu1Tdj8vO+nFoJBnVQgo7l1Vb6sAiBhsBlhya6ko0xu70YI8ouyZNGoruNgBc/sxG10VylwNi5SrjRg5r339tUwTEKnef9iapTrVg5GMa1r3u5dMDUcA8mcswJu2CCKo9CfsBqqU4E3nnfU3+KwFNTnjkOwof5q5jSzSAJOd4ROfj1R66wqlfprmbXeIJLf2WfkMFfvJDl48OR4TY0u1l2voyVVnq/L6A8evisLsted+8pIl9V8avW8su4UPb/OZBuQVbXb5bUjg6lLP047XZ7a8g8Y8zMMm2WZrcWHEdf0u9yVkyGQh4Fnt4DkY4Fvme8HmVII/e9YkJUbHgQi1j51bKsIWNKDKUNGaPoGgb9fG1CqAtuQSxM9GYKQzUoZWI3eRXublVUsyyheMBLoBuVhONRsBkXgw2QTm+Tupe/yq9igF1d++12FCWs/8hmjEEZJngUS9x3zMVKkIb4vzfiOhlBU+gA/tvd908ULXte0ql4k4zsxnN10x6vnZF2BDMXR2SBpEjHJZcCZnlTBo5eHcZ3nQVVZwriWkD1DRRpx6DyCjrRmU1Ur4WPjNzZaQnYjCna/8kYD1Rcyvi7SXgPfHNgAx60FNsuHqBzmQ58lczmWv5BjJ1iKPmKwpzdtenpt4QcP5HNqBXDgAAPP3tnQ9aS7Vmstpo5LnMxTp6LOTGlv3rCpmG4liqu7FM4E7AMn2tNV8RkOpAUWlBRMtsjrXO/mHvNZEDMYhdhb0YGz9LnbEZPLm6x1LpUkLlsRTozQA5CZi7P0Q3krvDBSYf4E0BU/92AkbNp2F8NfVbTaQmZPlhtaDRx2pJaGYnkhKEhGTt0zpfgbiOodvTcOXrAhA/tH8tYHhlewGRKU7sm1DtL4knqjJLiuHMo7yDNvZTb40xyNxBqOISEVVauf0TiGrMndCwjwVdN8wCTpKoV40DxUzTRci51SxyshxNiLKqJsPX0VqDsysvkmpHFX+OpldFg0hjbW4WrnRGcSKeSua2n2M/t/cEfCMqYMCesbH/5NjUSMNmzhar/8i9RUtmFDuBDdUoEN4qWBnFhzXF5yTc6P3QdlvgFUn6k4Rr34ZhWqrp6o+YyAbmwR9U7RmdkmeYSZGHCHhpC1F7SqvgRQ2U8TnZab/garknHnJvGWzOTI5Eva6ZiZD7fUH+KwFTgsr9JYOQSvXiw5xVhIfPwUjBTEstglF1xNCn6aKqhHOIRqt0ClibVMROF8kJVMnUBCUDJCOlmJcuLbTsJ4n2R5d+7RFIFekBf3vc29FMjam9V19fqumYuMTc8+fNn9eX8/2jxInjJZqWH0LuDpotf1hCsRKwru2rhg2RmbqqzjAUetrsoudv1FplvetiBeLIpRpeutKFfcZliXxbLvaMm51j9Vt5gL2uO12MiI2+v6djULXYfTejCmFshoDTkMyfMPKEk4GYQmR0U8XOgjCWg9DQVE65AJrZwvKHGrdyj6USMGo9qpoM7p6LLZd1fX93406Appui8a80DC3PrLpJKkLEictkuxlBmN7QMida1Sz1f5QhitkrnzF9lJC0D1/IrSov++BaQ6eyUysaUX7mbsAmRI5crztzonfpA2KjQxgyvxDGki6Im8ilQAtgZTeZBW0NkjHLbF5kW7xWiJgjtAWpE+D6Q1XliiL+0/BMOLP7YtAkSzoqV2081t5rhCwNFgseq4AA0EYz1WJdINbzsnW3uI+rDU/tfkHYFOYP0xIbFE4k4D0B68YZ3UZVE+cvBscfDKe7gGEsa5zTWpOxsqk4UPGf+EdR+aYKykgA6u57EKhZkKJ57cP4roCUJM9FC/Oi2oKrlqkI9bx/qGpFFRmbZ8F2tdegEQtFd4eDcFmGUPt4p3iJK5d9qt4MLjLGStMo/s2VYVWPGhqQMzGn2CtR1+g2Ae9YSxLzKCXwqG/rAe75OXsZYeEy4BMb3da25UpbvhumJOf9sgzLqZ3RGsCBRaQtax/j4bpDnthfdKb81eShm1M4WIV+YG3EVvmn2eFL+FMRdjBX4caEKVeLRimHnoRloWKwaCv9H6mX7pCa9rbC4D+uBmMB3227XW+j+mmtySON3f/Y4kVnsZpfA6cqMhBGsHbiKKr/CVnekGzEHfJY9FH0lUuoNklgA6MAqjyhKhGcPG8LIAXBZVk2o+vBFrMlrP/lcn56Ofsk4HztMxGvFLql7NEacYwRMpzsWHZ+jSIYq8mVGUA2K+HongyEtLKU2ZuIRnxHA3GDNj8u62JLoPPl/LKsy/WWUzwzvETfhqGiCmd8zKr2EENJCgg7y7Q3KsVAkAjPiqKn5UhpiCZkvqXVUNn0JN7jWINSTpAmM8CX9bStaywIB7QeH36cn5+e8sC7TJ9xvLK7kB0s5PRlfJMuTwuIamXdP4hyFaEN5608qYSoBuTNPeaJQULALum5zqJ2NIiZKFILzODG5bAsq8WCA2CVb9vLP+tjnNP0iQ0FcvuMV59qAMxHDyjXItteiCthuONhuStynzw9Ng6uFQt7U03CDKStgi0tICj4QYDfXMDaAQ8NZCnmNaZU5S2rMbHJNtpq97Lp+G37sgmccRNjjwPmDkTl9MW90QwbRWzJvanKtXb2K0DZYIjwjR1gVicFARR4+I+ZrpdNVQgEVOKtHtFmoonYBC5R4pQ7HRcbmFBJabrAOO42H1lufOOHo3ZKTvthVlt4q6YtPLimedZZB4BmVbsUZWE28x5h+XGw6xnn7U5FiXeuNmgJnXt+NX6WD1EhbBuYeEhA33636laS+3eyuiH1M5KfUVKE3EAinC3uBZRoWLf/OWtzrUjSORM/NjQUh2STyNJm0jYPLwEDZYcsOzaDROTcgLVW505H3kwRvLzHlOQbORNiozOLJcepyr35Tq4UyK3rKOH4n5suV42C2LLqXdq0Q9WhfeqP6H5/XmiP9xChXJWEpJH0YtPDKZWj7uN67WDkUIRlgNxRPryRUFAjq6eDl61/6fb44itm657qN9kzNRtVfZ8sBDHqu/5vUebIybAUGbNuGnrXayjdDpxTP6tVNAXMgFabYKvTDyvWgVj6/nJat0hht6kuvezGhvIaYqVOvp21cR5pTeaTF6M8NAFmbkCstQ51joBNpVc0urRZRk3jGc+UmayIHHqWciR/KweUySOQtSm24sfpsN1ll9roDgxlUeP8fvD/gLFp9UR6U239q4dLKwXfU7JXtay6w5t60vBEW3dQ+M87AeMXovDw8IB1WhPCqdBz7sZYeOC5ZTqhLmQdcG49DyrL3yy+axfL70WGA3Jdbzy0+7YYWeZsxtFhMd7ehAgd0ukWzzPFoNNf/+dYR6IEzBV6FIsHkHtpTssfa6Dlm7vLRUWxSsSYbUvZ034jT1FV0Qw0iajTd9m/7Fmg4qCSw+JUnJztWR6ROnKXZZilXQ7/2a5zKVdrwN0tzarrmzseitwVqDSXS+4JXtbivt53skeTtmS3vbKH1Yr4xifG1lPgHRHXh9utBByWsMDl/sahYEAexKC0szYvz4p0ZVo3RxaKBGVnMB/rHY7zJbWj+kDaaaKaJkd/ui1KL143tDtOWA62jpt20YOeFPVvyRxytnUOKCwBAcl7l/rK6Dqz4iC3KCQjO2HNG5qzsUK8oXRhEwQrlywz4M3PFRLm3rklUeJGgJ0Dptx+8/1x3o1gX44qPecovpN2SjD10HSr5Sbj49I+VfPW9ZbPEgP4Bw0NFVtHzEGo3TBnP2I8YI5I5HxnrXbq5czWAxwQiN7SqCZo7yyB5oLuHoe5NfAnTOU0GIF5tYUIAScntJ3WNPYu6Xq5rYBcvTPzfJJuWr1mFQXCg2ZmMT0KMxMyY2G1wkutsigmNO9mAepnmkgCbAQB4iSwnvnVT0Fs7w4vnIYg5rK268vtLYdXuz92T5g+5+4XHONevT897+5REioE200bvDNFqXhOEoXR9vyv/N1z0JIYaru8XKeNxGuulj0YfK1bVfCCIvpt1SLuV91dpI9WUYYatWaEHOQQuZ5ImureVULWzcyQM2tEfcvNiVssllYADqdul+dzHceA0f0YBo/dYWNylKOAfl/Rg4rhYPyEPWBD86clFDOCF4R2Hw9sYQZONblhrvcgJt0Jx+3y8nxe59HJaVePHSrUAtYHk64meMza0S5HCJxwW58MJpGEIflFm7loIsfWQEVA5tJOhRF8T0DAr8+/n54vawyqR1g4VvVM8C6WRt+Z2VcMMPspe1jMIkoXch/P1B9NT2htmCwEUeccG2yw9WKrLMR2v20+NkeputNK6hi2p5///H4ubyKJQjHIWX9KwHnspqHcmS9NiBKzKlo35kd55dMI3ulZKtKuB3MTeY1zW7Rt2+QnTNCevGA7P/7z6+miNdx8jaQRR33LrlvH4FUFBufRm+RO7g4icvW19HzmmZ1wGDe9gsRydI21sSHN0wf0623bmgzPZEUCuV1ffv73v78vyj2dJBadyg1eyuhUq0OTydIYoMJw09zs0pjEGwayjrX1Au5UrtQqXqf5aWkzaJYVyUoO6BC223UTY0t9QnDmIkxE7enLz//+9+/L1psYV3fOhmFSk3sKPrgw7343/hxhJM7P/PRVLtdEkNM4yYHb9epZCHBvt+Xwl19///PrSZgi25p8j/bPtAMUAlWB1gYgNtGxRsbdwrB8TEVKPGPX4rQvNWK3ldpvu2EU8zY5hbVClW/frrcMPNV6xeoJYbu8/P77798vAirDm4+eOBSAWH1NTh8UBgVodJFghioHxxGahMcxtclMIzmY3d0IIS4go1KhiEIyiBGSjDd7AMi2Xa8bDr0GY6rkl7bz4z8///55CbT9c27iDXdyxr0ZHt+wuVPZSyyme71cMB+TMaR+haTEJpZtqYnp7n67Xi/Xjdtq5LIECFlGpXy7vfz++/ev53zcagKaAVXMp9YNoNBlTPzckiSabgkNYdnZW5YJAQBTcChbzZpWQ1ajLQum4Q+SXmyuW8F+znZ+Pl83HBaSy7oYl/K4fduul5eXp/O5nr5WI2DFDIuhpJJMc6u8UdRu9FFQkzzHxlBWKWeVd3bqPGONrHqwEHBZLM9TZ43SSOfMURuP63Z+fL5uWFaAy7qaWajAdtuu18vL9TZVdr3KTUyIVdOg5sDo5b0VzpHZX2FcrczdMHlWxxT2i8zMhj+Xu3XdO8ANatJ2e3l8vnn4nrYuscKO0rZtt9v1vDufMKss8iGyeX51MKDLKpBx/Yg9zOSGCbFK3h30SXWwq1dQJtf7CaO/mIGPpBuZK7NpYaeqCDVJzO3l8bkOAWYn/AOm/e5UrT4qeiaFGbYe2wtXHzRwz90CsA7smVmbMBz9iXPmajjVFCse0FGEzQHaYmbTMOegh3u/Xc/P57l35+tek16haBVbsyn+rI+vrPaO1N09XAl/bYv79na+MgAbDXdPIkZblqzJvlP9pKG3sc/RR9Rhbfs+OTaJL6jNo5EnWUaTolHlCU2tqDVcFABzwWN8arRCNiKEodXpKhl38S0ynzBblhXBjnOFbZEtAPDtK+dhv2EHubftTVyaCuV/R1xi0I/6QCjaiCqSmb9T4nGc+hvLyWPyKarCFqv4zGsT67frNwXskN+gWwLqiJnadgv130ECNaZQsCqNlMFkbaSMbrVpCuO1+bTinAZLHre5BqMdAL5dLp/aIz0FLN+nJl0Z2GpZFHOA6FJyALV+uhZkqzunfd4YDEOejByrk+SxCpcVnIHLt22LnYBiL4ugNVsEldpODbOp2/n8FQGnv08hw+nSFoiqoZKj4CKwde8NC/P41XyOH2Zbe0IG+dh8IvqJmKWy47n16tvl8oWTeOeNAoIyIGNAwxqIjCNWByev6ic135yZVjzT66fxdRI5L/4csQn3zbesgOWEmU0NKjtcXeR+vV6/cBz2TsC00qkpE4vck8eQhETTr5kyQl4DCyqzjjUQkqwdHGBL56eQu7o5RAmfJM4MLGjy7Xa7fhdkXl07rUy5sKdlb+h06Wz4Vv6G4ifwS3OCen5orenZLZFP+a6Xy1fNhKQehSAkykWngdQRGMvdpkodw01NUiKgKpZKgoBSZl0M54oZxvOGVYBlrWw0wHIFQS1izHvDkbicz5ftVb9/JCAwNxXImaIoKQdmypTMROqzGAPhdltKFMfOyVyQgukpnkXKpGPhFHpglopklXRFleBy+fXycvloO8NXAjZ+7vpFqALcBv77K7P6zbaDLs6/YEkbAuYsC5TcagIvb40HS6k04Ytvt8tHmxneCxgwbvni4GcxSxyN3aE8u8mULl9Iwf5RM2sijoFtGUP5C3uVRUq5xiAqHKgK+kQ4rsMpjELabfuijUBtYtzBsbL1KJOd8pU7sB/KErrhrwVMOM6Oa/PC/lcveESS7TQJzAWPWZLqiUCsEbxevmIjsN9PZr5mA9vuzns/q7+PAWZzoxw63A1lOWmSmusx9o21Oo1YXmtgYttud/ftcvmigF4721SkNhrLLrLTPH4li2o0K8FEgLWgvOZzLutkBclS09UihxSo20nG0seoi3KP3WEXM4tsktxv169NwSiIvceQ+tcYwJ18w5XXNDzDBamheov3Capt5IrXIR2YELFOZ1cmfnPDGCWt+7qKRkhxchQ0GpfmevIggMkYsGWcIDi9ZKlWcvfiWQK120rBbvcr6+Exfu6+xWFuFssFopP9drl+WUVt2uCXE9D3+3vfniFWr4un7z16lrnIjZly5WW5D3M4KeB6YngAYp/8iOxuaenz4AMXIL9ezufr5w/6BoB18buzqDXGbOemlHyhXlItH36FMzURR19h90t2vQVeG1cSKPm6jrdgbrs8f9EKAisN0zB0o7Qz/aOMpcMZivwxXdOC6yQdXiHeFqi6iLExfhwu2MPYHRhLKm+3rQt5jcY6zVXXp9/PX7OCceZLUak5i9yZ5pqHdUZdNNNKquYZY9A90SH10nK3kTKPcSKGx4K3dDTZW/9sgm63Wt801pnJJb88/X7+As8OAaNju/PR/TlAg3OdDOrjNy6lzAl/ff+4i3XW2RjS6bjQRPQu0WxiIAC+Xc9Pz1/xlELAio9UyjUkqYL2YMqBNG37h3HQICixUzYmWpCELYJzQqybSHOSB+CWG6iaA9IoAh8EPcQ+Pz+/fCVYkQJKo4srEYDybVhx6Nk0A6qdRFTnoEcrtN/sMV3n8bThcOQGaUMQgDS4h+onv++QqgTcXh6fXq5flS8OtRmvKe3RPPUnFa5+aGLSzgz2mt03clCAwZOQRWBvNXdP7xEVopLfXh6fvi4f1q3wIVaVNEXMtzjqaOUaktxtK0IqFUTbvTgToJ23AbF0c9uyt9Go/8RlPeJbxoXCq9i+A6GIM0DLsDMEDPZZXOZVxWlvRjDNl3KZd3DSSZU0gjkxS8BS3HqZEO615amUodRLvnK7nZ8ez19FGPR5E9kqNJTNVCZiBoEHGYTqphLI0P2gJKzDb4ja7aXqI1WUvvCxuwddU9PsePSXtuvz8/PLlyE0BJwOKGVsYeOYTbdnNQAWSNr6WAmgS3oSWjt2lMrFXvKGjHPkmQS57ihUXUPPLbdqKToVNWoUtpfHx+fzF0lMCJhN6w8SZppsZ9dbLhJzn9bqtvaaejyLqIWCdgkPgLH/TeV95zHqaTF5n80t/Pb8+PjyjRnYAnZxVSFbszd1l7ow9syaAplB3II7ovprn/vO3sgDh9JpqviIMiKcCFDkP1OJJCC/PP16/OwB7a8EjLMsUpj6n6ohYd8oeW53JIwN49M+LLFKsDZEH0+XpoJAmqNSFBBguY1aBIY9kaZKQ8ITzN67XZ5+PX5rADOFPRrxmt+jbUGmmeqnTcaLCqk/Gbf2+Zup9zWzK8W0C4ZwKKhhKIHfLi9Pz5fvzMAKOo2YJNAeRbVrt8pRd+wym8WomZzsRaashkLk+d0taODPmG5ABdgwoDcs/fnx6eWb8uWGOVVoyhRWUh49MNu2hPhKlAFNrzHwvRIc8Qgx3KpJ6fPUqKqQzE7rBbblEyfJJqDt5ffvl2/KN7Z62F+agfWjK5d13HG7eExCdALmKMosT6FeHMdwNc+eQtru1+ffj5dvmEAAfXqd9ehMNggT8UCPAoE4czwpVcw8m32AQUs9E8QlXxtzFmkA+vsC4/qBJFLazo8/Hy9fZ6Et4GTz0C2rYHAN5YQfO47RWtq1BlNdNaT7tUiYwGOIkwqwi7+m6ut2fnl8fPquhk6n1yFtQDaiycoe+N+5VMA4ZmdJ6LUNZKFPpR535A4VeYmbJwt7fX58Pn/PRKSA+YriSyKsNunH3KnV5PYUxod7up3B6nzc0BDG9nBZqtaEnhUBd9/cWdkrRG/4+dev73gR9wJmG7yY2qS2e0M1r0Hp7k9FVZPUyU8snawwUvtRqteUfdh8k6aiQAZJ+/XrO15EC7j/Z5V/vgoH9ujUBypzN0FK//98Y2EXd6v5Y2Rt6IW7T3nNRAHpdn76FxCaAjZozkiI0YtBF4ubxd4kQq6u7ikcVHqLDW8wOF+shyRyK/UymFFvHiwC6lIEEhkQWkhqOz8//n78Wiz7TsCGmL3d66RTCT4FNxEDYPMC4SqGQMUg+4sRUR3nClS6rJBS27ZtnShDahKhy/Pj49Pl++L1NtShgkU2hs1LiLBuZnq/ruQqQ2Vzs/VYj1VDyACWULgRwBpxqdwddtu6yqhg3IzaXn7+800vYhJwYoN1kt0E6kiY60h7YKRSXC+b7QqPgLVfVTw0KxMs7YOp8RWQiNz9beut54uumpl0e/rn76d/MQFxV+kUI1EBkWIlBLgTcD7lLgljrtRMI9ZaSqu9JzhcxHq6A0gBKwg7mmJG+PXl6ffvfwOh6AxvOau+jWygjfnU6BcdwOL+FSkWPDek7ekDMPMQ5UKbdUdMPbnfq1l1vxl1ffr1+/H8bxAGEVWDoFx6sPWpv7XuAWWNmSfpSOHZJhp0PKXHvWoZ4pZ28qfIdepBJuqjszqEHe82w3b+9fPXy5dD2W8JOBYWNDl8JeCYhlIfqVDWfMabQVZbP8fVE0CS1zYOMzp352K7Pv/++fRvTGAIuJWpiz0oWFSfccBcCVibfqA37Y97mvGM0BVrUACUC8RezNO9EbtCgWMiVOaAJLndzk///Pw+yW4Ba5PeZH8s8KTFdp8o57x7t2ZtNLYPfWlSkxNwUJYRRZZL8igwKm2xOtcKFUikEdrOT79//f7XAzjtEBt/dlyzf9ER9/bWi6mqTutpUB3srV2iqLpmhebGvuyoge4If7Yg5Hv59c/Pp/O/nIAl4JQf2U+IImmABKfn7Owgdx1JPm7vdhe50YYkX2NpTrgWGGfggu2OmNlCbbfnv//357e93FnASqBX26ZgRU6tHsEaml6JIZnfj2D82TYv51nR8HGc26hUn0eQUQi06fby+PPp33GYFPDzP91T8THdPrhrcggzsTMzWLwapNRZv16+k4p4df1/xL6Q7lpPXRcAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<PIL.Image.Image image mode=L size=224x224 at 0x7F9F8F646E48>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mb9_guCT5fcN"
      },
      "source": [
        "## Cropped and vertical flipped"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zBaGdQq_5fcN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 440
        },
        "outputId": "af8e2702-8268-47e1-d8ca-79cca61cdf08"
      },
      "source": [
        "cropvflip_train_dir =  train_dir+'crop_vflip/'\n",
        "generate_images(data_dir, cropvflip_train_dir, 'crop', tf.image.crop_to_bounding_box, [])\n",
        "generate_images(cropvflip_train_dir, cropvflip_train_dir, 'vertical_flip', tf.image.flip_up_down, [], add_plain_dataset=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=L size=224x224 at 0x7F9F96CF9278>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "avQhsJDQ5fcN"
      },
      "source": [
        "## Crop, vflip, hflip"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "tags": [],
        "id": "z-GyH1gz5fcN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 639
        },
        "outputId": "8a25a9e3-f9c8-4e8a-d2c0-670477aed1fb"
      },
      "source": [
        "crop_vflip_hflip_train_dir =  train_dir+'crop_vflip_hflip/'\n",
        "generate_images(data_dir, crop_vflip_hflip_train_dir, 'crop', tf.image.crop_to_bounding_box, [])\n",
        "generate_images(crop_vflip_hflip_train_dir, crop_vflip_hflip_train_dir, 'vertical_flip', tf.image.flip_up_down, [], add_plain_dataset=False)\n",
        "generate_images(crop_vflip_hflip_train_dir, crop_vflip_hflip_train_dir, 'horizontal_flip', tf.image.flip_left_right, [], add_plain_dataset=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=L size=224x224 at 0x7F9F8FC1FE48>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u9_THdqT5fcN"
      },
      "source": [
        "## Crop, vflip, hflip, brightness"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BsXtLK2m5fcN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 838
        },
        "outputId": "aa58b5e4-cadf-4e5c-f70e-fddb17b861e3"
      },
      "source": [
        "crop_vflip_hflip_brightness_train_dir =  train_dir+'crop_vflip_hflip_brightness/'\n",
        "generate_images(data_dir, crop_vflip_hflip_brightness_train_dir, 'crop', tf.image.crop_to_bounding_box, [])\n",
        "generate_images(crop_vflip_hflip_brightness_train_dir, crop_vflip_hflip_brightness_train_dir, 'vertical_flip', tf.image.flip_up_down, [], add_plain_dataset=False)\n",
        "generate_images(crop_vflip_hflip_brightness_train_dir, crop_vflip_hflip_brightness_train_dir, 'horizontal_flip', tf.image.flip_left_right, [], add_plain_dataset=False)\n",
        "generate_images(crop_vflip_hflip_brightness_train_dir, crop_vflip_hflip_brightness_train_dir, 'brightness', tf.image.adjust_brightness, [+0.3], add_plain_dataset=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=L size=224x224 at 0x7F9F8F76CF60>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YaRYPm4acbp3"
      },
      "source": [
        "# Augment Test Set"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_lX3dJ1KceD9"
      },
      "source": [
        "## Vflip, hflip, brightness"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2TKtsZiv9WKF",
        "outputId": "641ba796-25be-4abc-e980-e974ae4c21dd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        }
      },
      "source": [
        "vflip_hflip_brightness_test_dir =  test_dir+'vflip_hflip_brightness/'\n",
        "generate_images(plain_test_dir, vflip_hflip_brightness_test_dir, 'vertical_flip', tf.image.flip_up_down, [])\n",
        "generate_images(vflip_hflip_brightness_test_dir, vflip_hflip_brightness_test_dir, 'horizontal_flip', tf.image.flip_left_right, [], add_plain_dataset=False)\n",
        "generate_images(vflip_hflip_brightness_test_dir, vflip_hflip_brightness_test_dir, 'brightness', tf.image.adjust_brightness, [+0.3], add_plain_dataset=False)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}