main.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "main.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "kExRelcl_d3w",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# some functions for image and plotting graph\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from torch import nn, optim\n",
        "from torch.autograd import Variable\n",
        "\n",
        "def imshow(image, ax=None, title=None, normalize=True):\n",
        "    \"\"\"Imshow for Tensor.\"\"\"\n",
        "    if ax is None:\n",
        "        fig, ax = plt.subplots()\n",
        "    image = image.numpy().transpose((1, 2, 0))\n",
        "\n",
        "    if normalize:\n",
        "        mean = np.array([0.485, 0.456, 0.406])\n",
        "        std = np.array([0.229, 0.224, 0.225])\n",
        "        image = std * image + mean\n",
        "        image = np.clip(image, 0, 1)\n",
        "\n",
        "    ax.imshow(image)\n",
        "    ax.spines['top'].set_visible(False)\n",
        "    ax.spines['right'].set_visible(False)\n",
        "    ax.spines['left'].set_visible(False)\n",
        "    ax.spines['bottom'].set_visible(False)\n",
        "    ax.tick_params(axis='both', length=0)\n",
        "    ax.set_xticklabels('')\n",
        "    ax.set_yticklabels('')\n",
        "\n",
        "    return ax\n",
        "\n",
        "def view_classify(img, ps):\n",
        "    ''' Function for viewing an image and it's predicted classes.\n",
        "    '''\n",
        "    ps = ps.data.numpy().squeeze()\n",
        "\n",
        "    fig, (ax1, ax2) = plt.subplots(figsize=(6,9), ncols=2)\n",
        "    ax1.imshow(img.resize_(1, 28, 28).numpy().squeeze())\n",
        "    ax1.axis('off')\n",
        "    ax2.barh(np.arange(26), ps)\n",
        "    ax2.set_aspect(0.1)\n",
        "    ax2.set_yticks(np.arange(26))\n",
        "    ax2.set_yticklabels(['A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','R','S','T','U','V','W','X','Y','Z'], size='small');\n",
        "    ax2.set_title('Class Probability')\n",
        "    ax2.set_xlim(0, 1.1)\n",
        "\n",
        "    plt.tight_layout()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UvE4OXRrEtE6",
        "colab_type": "code",
        "outputId": "545a9106-011f-4e3f-e100-6b60a063c0fe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1714
        }
      },
      "source": [
        "##   download the dataset and upload it to your drive: https://drive.google.com/open?id=1lUt0lKeoBgnvM0E-G-KGV7wwHKuJHMhz\n",
        "# necessary downloads\n",
        "!wget https://github.com/dishank-b/Character_Segmentation/archive/master.zip\n",
        "!unzip master.zip\n",
        "!mv Character_Segmentation-master/* /content/\n",
        "!rm -r segmented_img/img1/*\n",
        "!wget https://i.imgur.com/sNrjsXD.jpg\n",
        "!mv sNrjsXD.jpg /content/data/"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2019-05-03 11:06:58--  https://github.com/dishank-b/Character_Segmentation/archive/master.zip\n",
            "Resolving github.com (github.com)... 192.30.255.113\n",
            "Connecting to github.com (github.com)|192.30.255.113|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://codeload.github.com/dishank-b/Character_Segmentation/zip/master [following]\n",
            "--2019-05-03 11:06:58--  https://codeload.github.com/dishank-b/Character_Segmentation/zip/master\n",
            "Resolving codeload.github.com (codeload.github.com)... 192.30.253.121\n",
            "Connecting to codeload.github.com (codeload.github.com)|192.30.253.121|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: unspecified [application/zip]\n",
            "Saving to: ‘master.zip’\n",
            "\n",
            "master.zip              [    <=>             ]  10.38M  14.9MB/s    in 0.7s    \n",
            "\n",
            "2019-05-03 11:06:59 (14.9 MB/s) - ‘master.zip’ saved [10887675]\n",
            "\n",
            "Archive:  master.zip\n",
            "1290d0b5d03978e562a576b8d5e728b4257a6250\n",
            "   creating: Character_Segmentation-master/\n",
            "  inflating: Character_Segmentation-master/README.md  \n",
            "   creating: Character_Segmentation-master/data/\n",
            "  inflating: Character_Segmentation-master/data/img_1.jpg  \n",
            "  inflating: Character_Segmentation-master/data/img_2.jpg  \n",
            "  inflating: Character_Segmentation-master/data/img_3.jpg  \n",
            "   creating: Character_Segmentation-master/data/test_result/\n",
            "  inflating: Character_Segmentation-master/data/test_result/Nomral_with_some_noise.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/better contours,less noise_contr.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/better contours,less noise_src.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/better contours,less noise_thres.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/final images_contr.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/final images_src.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/final images_thres.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/perfect line segmentation_adpthres.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/perfect line segmentation_contr.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/perfect line segmentation_thres.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/with contors and lines segmentation_contr.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/with contors and lines segmentation_src.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/with contors and lines segmentation_thres.jpg  \n",
            "  inflating: Character_Segmentation-master/data/test_result/y_projection_img2.png  \n",
            "  inflating: Character_Segmentation-master/main.py  \n",
            "   creating: Character_Segmentation-master/segmented_img/\n",
            "   creating: Character_Segmentation-master/segmented_img/img1/\n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_1_1.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_1_2.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_1_3.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_1_4.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_1_5.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_2_1.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_2_2.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_2_3.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_3_1.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_3_2.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_3_3.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_4_1.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_4_2.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_4_3.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_4_4.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_4_5.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_4_6.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_4_7.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_5_1.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_5_2.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_5_3.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_5_4.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_5_5.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_5_6.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_5_7.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/1_5_8.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/1_5_9.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_1_1.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/2_1_2.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_1_3.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/2_1_4.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_1_5.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_1_6.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_1_7.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_1_8.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_2_1.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_2_2.jpg  \n",
            "  inflating: Character_Segmentation-master/segmented_img/img1/2_2_3.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_2_4.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_3_1.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_3_2.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_4_1.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_4_2.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_4_3.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_4_4.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_4_5.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_4_6.jpg  \n",
            " extracting: Character_Segmentation-master/segmented_img/img1/2_4_7.jpg  \n",
            "--2019-05-03 11:07:07--  https://i.imgur.com/sNrjsXD.jpg\n",
            "Resolving i.imgur.com (i.imgur.com)... 151.101.52.193\n",
            "Connecting to i.imgur.com (i.imgur.com)|151.101.52.193|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 756628 (739K) [image/jpeg]\n",
            "Saving to: ‘sNrjsXD.jpg’\n",
            "\n",
            "sNrjsXD.jpg         100%[===================>] 738.89K  --.-KB/s    in 0.04s   \n",
            "\n",
            "2019-05-03 11:07:07 (20.2 MB/s) - ‘sNrjsXD.jpg’ saved [756628/756628]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M_UlzJUy-3kA",
        "colab_type": "code",
        "outputId": "043bb3e1-82f5-4b1a-8479-cb40ce6beb52",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        }
      },
      "source": [
        "# mount google drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qTXnggVC-4nH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!cp \"drive/My Drive/Colab Notebooks/DL with Pytorch/A_Z Handwritten Data.csv\" \"/content\""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xwBS-8Ci-6uJ",
        "colab_type": "code",
        "outputId": "d543c1a2-5fd9-4421-9065-16e666f9c08f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 6955
        }
      },
      "source": [
        "#convert .csv file to images\n",
        "\n",
        "import csv\n",
        "from PIL import Image\n",
        "import numpy as np\n",
        "import string\n",
        "import os\n",
        "\n",
        "csv_File_Path =\"A_Z Handwritten Data.csv\" #Your downloded csv file path\n",
        "\n",
        "count = 1\n",
        "last_digit_Name =  None\n",
        "\n",
        "image_Folder_Path =\"A_Z\" #your path to target folder to save images. Note: Path should have 26 empty folder with name as alphabets\n",
        "\n",
        "Alphabet_Mapping_List = list(string.ascii_uppercase)\n",
        "\n",
        "for alphabet in Alphabet_Mapping_List:\n",
        "    path = image_Folder_Path + '/test/' + alphabet\n",
        "    if not os.path.exists(path):\n",
        "        os.makedirs(path)\n",
        "\n",
        "for alphabet in Alphabet_Mapping_List:\n",
        "    path = image_Folder_Path + '/train/' + alphabet\n",
        "    if not os.path.exists(path):\n",
        "        os.makedirs(path)\n",
        "        \n",
        "        \n",
        "with open(csv_File_Path, newline='') as csvfile:\n",
        "    reader = csv.reader(csvfile, delimiter=',', quotechar='|')\n",
        "    count = 0\n",
        "    for row in reader:\n",
        "        digit_Name = row.pop(0)\n",
        "        image_array = np.asarray(row)\n",
        "        image_array = image_array.reshape(28, 28)\n",
        "        new_image = Image.fromarray(image_array.astype('uint8'))\n",
        "\n",
        "        if last_digit_Name != str(Alphabet_Mapping_List[(int)(digit_Name)]):\n",
        "            last_digit_Name = str(Alphabet_Mapping_List[(int)(digit_Name)])\n",
        "            count = 0\n",
        "            print (\"\")\n",
        "            print (\"Prcessing Alphabet - \" + str (last_digit_Name))\n",
        "        if np.random.randint(6) == 0:\n",
        "          image_Path = image_Folder_Path + '/test/' + last_digit_Name + '/' + str(last_digit_Name) + '-' + str(count) + '.png'\n",
        "        else :\n",
        "          image_Path = image_Folder_Path + '/train/' + last_digit_Name + '/' + str(last_digit_Name) + '-' + str(count) + '.png'\n",
        "        \n",
        "        new_image.save(image_Path)\n",
        "        count = count + 1\n",
        "\n",
        "        if count % 1000 == 0:\n",
        "            print (\"Images processed: \" + str(count))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Prcessing Alphabet - A\n",
            "Images processed: 1000\n",
            "Images processed: 2000\n",
            "Images processed: 3000\n",
            "Images processed: 4000\n",
            "Images processed: 5000\n",
            "Images processed: 6000\n",
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            "Images processed: 8000\n",
            "Images processed: 9000\n",
            "Images processed: 10000\n",
            "Images processed: 11000\n",
            "Images processed: 12000\n",
            "Images processed: 13000\n",
            "\n",
            "Prcessing Alphabet - B\n",
            "Images processed: 1000\n",
            "Images processed: 2000\n",
            "Images processed: 3000\n",
            "Images processed: 4000\n",
            "Images processed: 5000\n",
            "Images processed: 6000\n",
            "Images processed: 7000\n",
            "Images processed: 8000\n",
            "\n",
            "Prcessing Alphabet - C\n",
            "Images processed: 1000\n",
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            "\n",
            "Prcessing Alphabet - D\n",
            "Images processed: 1000\n",
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            "\n",
            "Prcessing Alphabet - E\n",
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            "\n",
            "Prcessing Alphabet - F\n",
            "Images processed: 1000\n",
            "\n",
            "Prcessing Alphabet - G\n",
            "Images processed: 1000\n",
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            "\n",
            "Prcessing Alphabet - H\n",
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            "\n",
            "Prcessing Alphabet - I\n",
            "Images processed: 1000\n",
            "\n",
            "Prcessing Alphabet - J\n",
            "Images processed: 1000\n",
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            "\n",
            "Prcessing Alphabet - K\n",
            "Images processed: 1000\n",
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            "Images processed: 3000\n",
            "Images processed: 4000\n",
            "Images processed: 5000\n",
            "\n",
            "Prcessing Alphabet - L\n",
            "Images processed: 1000\n",
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            "\n",
            "Prcessing Alphabet - M\n",
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            "\n",
            "Prcessing Alphabet - N\n",
            "Images processed: 1000\n",
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            "\n",
            "Prcessing Alphabet - O\n",
            "Images processed: 1000\n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0KFuUi39-_Po",
        "colab_type": "code",
        "outputId": "6fa5ae75-e130-497c-a9c4-ff8f4fd35475",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "# testdata to traindata ratio \n",
        "data_dir = 'A_Z'\n",
        "ratio=!ls -l A_Z/test/A|wc -l && ls -l A_Z/train/A|wc -l \n",
        "print(\"Test(A): \",ratio[0],\"\\nTrain(A): \",ratio[1])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Test(A):  2344 \n",
            "Train(A):  11528\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DvR2Dpwd4dl0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# necessay includes\n",
        "%matplotlib inline\n",
        "%config InlineBackend.figure_format = 'retina'\n",
        "\n",
        "import cv2\n",
        "import matplotlib.pyplot as plt\n",
        "import torch\n",
        "from torch import nn\n",
        "from torchvision import datasets, transforms"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7Lr-2_He_LLM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# define transforms and data loaders\n",
        "transform = transforms.Compose([ transforms.CenterCrop(21),transforms.Resize(28), transforms.ToTensor(),\n",
        "  transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5))\n",
        "])\n",
        "test_data = datasets.ImageFolder(data_dir+\"/test\" , transform=transform)\n",
        "train_data = datasets.ImageFolder(data_dir+\"/train\" , transform=transform)\n",
        "\n",
        "trainloader = torch.utils.data.DataLoader(train_data, batch_size=32,shuffle=True)\n",
        "testloader = torch.utils.data.DataLoader(test_data, batch_size=32,shuffle=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XfTk8qCW_QHU",
        "colab_type": "code",
        "outputId": "3559d241-87ee-4fb5-aff9-13609e79d077",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        }
      },
      "source": [
        "# check one of the images in any of the dataloaders\n",
        "data_iter = iter(trainloader)\n",
        "images, labels = next(data_iter)\n",
        "imshow(images[0], normalize=False)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fee05341eb8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdMAAAHTCAYAAAB8/vKtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/png": {
              "width": 233,
              "height": 233
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7uEwmpX0_SvL",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# network architecture (fully connected deep NN)\n",
        "from torch import nn, optim\n",
        "class Classify(nn.Module):\n",
        "  def __init__(self):\n",
        "    super().__init__()\n",
        "    self.fc0=nn.Linear(2352,784)\n",
        "    self.fc1=nn.Linear(784,256)\n",
        "    self.fc2=nn.Linear(256,256)\n",
        "    self.fc3=nn.Linear(256,128)\n",
        "    self.fc4=nn.Linear(128,64)\n",
        "    self.fc5=nn.Linear(64,26)\n",
        "    self.relu=nn.ReLU()\n",
        "    self.ls=nn.LogSoftmax( dim=1)\n",
        "  def forward(self,x):\n",
        "        x = x.view(x.shape[0], -1) \n",
        "        x = self.relu(self.fc0(x))\n",
        "        x = self.relu(self.fc1(x))\n",
        "        x = self.relu(self.fc2(x))\n",
        "        x = self.relu(self.fc3(x))\n",
        "        x = self.relu(self.fc4(x))\n",
        "        x = self.ls(self.fc5(x))\n",
        "        \n",
        "        return x"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PSNlOVcy_VuJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# criterion and optimizer\n",
        "from torch import optim\n",
        "model=Classify()\n",
        "criterion=nn.NLLLoss()\n",
        "optimizer=optim.SGD(model.parameters(),lr=0.005)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mFViVwOK_XdZ",
        "colab_type": "code",
        "outputId": "2c2f8748-3c00-4c91-a39c-ace50c4cebb8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 67
        }
      },
      "source": [
        "# train the network/model\n",
        "epochs = 3\n",
        "train_losses, test_losses = [], []\n",
        "for e in range(epochs):\n",
        "    running_loss = 0\n",
        "    for images, labels in trainloader:\n",
        "        log_ps = model(images)\n",
        "        loss = criterion(log_ps, labels)\n",
        "        \n",
        "        optimizer.zero_grad()\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "        \n",
        "        running_loss += loss.item()\n",
        "    \n",
        "    else:\n",
        "        test_loss = 0\n",
        "        accuracy = 0\n",
        "        \n",
        "        with torch.no_grad():\n",
        "            for images, labels in testloader:\n",
        "                log_ps = model(images)\n",
        "                test_loss += criterion(log_ps, labels)\n",
        "                \n",
        "                ps = torch.exp(log_ps)\n",
        "                top_p, top_class = ps.topk(1, dim=1)\n",
        "                equals = top_class == labels.view(*top_class.shape)\n",
        "                accuracy += torch.mean(equals.type(torch.FloatTensor))\n",
        "                \n",
        "        train_losses.append(running_loss/len(trainloader))\n",
        "        test_losses.append(test_loss/len(testloader))\n",
        "\n",
        "        print(\"Epoch: {}/{}.. \".format(e+1, epochs),\n",
        "              \"Training Loss: {:.3f}.. \".format(running_loss/len(trainloader)),\n",
        "              \"Test Loss: {:.3f}.. \".format(test_loss/len(testloader)),\n",
        "              \"Test Accuracy: {:.3f}\".format(accuracy/len(testloader)))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch: 1/3..  Training Loss: 1.300..  Test Loss: 0.429..  Test Accuracy: 0.876\n",
            "Epoch: 2/3..  Training Loss: 0.262..  Test Loss: 0.188..  Test Accuracy: 0.949\n",
            "Epoch: 3/3..  Training Loss: 0.160..  Test Loss: 0.146..  Test Accuracy: 0.960\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9cvROvTeBf73",
        "colab_type": "code",
        "outputId": "caf6b9e9-c5f5-4fd7-acd8-e4cf4ed56c2c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        }
      },
      "source": [
        "# plot trainloss vs testloss graph\n",
        "plt.plot(train_losses, label='Training loss')\n",
        "plt.plot(test_losses, label='Validation loss')\n",
        "plt.legend(frameon=False)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fedb8aa00b8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ePVojR45U/vz59cUXX2jatGl64IEH9Ouvv6bYTPPCCy9owoQJKlasmMLDwzV1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\ngg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/png": {
              "width": 373,
              "height": 250
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ENwM8GtbGZPd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "################### TESTING ON REAL NON-PROCESSED DATA "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i0k20p-rLA7z",
        "colab_type": "code",
        "outputId": "18822863-3900-4b9d-cdc6-e88b82f97c1f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        }
      },
      "source": [
        "#### example image \n",
        "image_path = './data/sNrjsXD.jpg'\n",
        "img = cv2.imread(image_path)\n",
        "\n",
        "print(type(img))\n",
        "\n",
        "plt.imshow(img)\n",
        "img.size"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'numpy.ndarray'>\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "47775744"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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3QBQ6eLbADbXLKg73PG9b1TjyBo3cccOZc9SSZ7ouqbX2PTi9bMhRJEm74NPT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\nuyT9W5LOk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A0w4qkBjI+DunlhBK/3e8uXJHeSWo5jmjSmlenlmQ5KHXjSN5dfN5ToIN/M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3C+V4ScYc4n6Uy7os8w47RQLy3GXI234ntkLF3opkYLjjDceEMsNKZ76TBOkSuBGISGazaZoc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FdAE3JFKSW6v6IosFqtkDcNXn/xDHmeY3s2Q13XWFQVptMpzg+PsL29jcXVVQomKKpdrVZf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aWWqBv0EZrC3fYyxoF/ra0bfWweHZ1sfe9MWYmXW1rqQPgC1YfAgD5o53MTZfv36tTDz3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\nWIFdbu050s0+9/oS4fs3rxDCJOkf3//7Fpj8+/Yfv+cPSvrlt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XZnkJ3krm8Bl+gq/3+M\nUa/3l8aq1tBk3ACAOyiMAWAI3Q3gog1pio3tG9azg053Wnw8HSDT3ryuvbrAZA4lgLuzrVLPU0av\nllJ6+8lRxYGj7e7U0wecCMANIHSaJs0x6fF66/OnXBXrcRz2dZpV1q3nxrvDfgp9B2mrxy5x9gHk\nrbTaspLKDv6kIw2D/gPkxjFz8sLXINUOGEtOUFyXTUFHOg4Rmct8VVDstgl9QOkob8OybX1DFevB\n9S9tWNe1b8aUjp34OLTYQuTi6emp603XGcjm7XbTsiy9PBORqs5m76f0hXDUZ2VMrtdrP5zEsYin\nKfWNy9umajnjMcaea5tSq66Qlza3P61ySkMIv05tY9MfUytU///+BN/9O8Jw9Oj++S+Q9Gv2//4H\nw5+pd/qvhBB+yO75mZL+BUl3Sf/ecM9v23//htBKRHHPD6ud6vSX9GlB/5/05cLnhp7Jxavguy5Y\n7tU5y+WeMJ9JR3gZrwoBfv/+/YkRQfGhtB4eHj5hvGDe2LHPwvcNTygv31C1LEsv0YFQs+h8cxd9\nh01y48i9hCa8dA+bvegDBfQZUwdavOstdu/x8bG/1z1ovutgnPl4fX09hZxcQfN/Zz4cSPs8u6cr\nHSe1lFJO9fEccHj4Keej/BAXMuAsDKDNDYwz4u7JwnSNrJozcLC4Lnsu1wB/f5/nhDng9fbwjpFl\nQKZ9YwzGa2xrB2H5yNNiDH3XLsCY8cPg+A/PQM7d00c5O7vM2sLg0H9f4w46aDOGC4PvzLl05PBh\noLyurzNQ42+e42wd7cY4OuAGeAIeMaoOijyKAnhzveXrz9sXFCFdAAAgAElEQVQ/gixPP2F+vE6s\ns8LO/Lju9HeyVmGQfCMdawznhLbzLAdhvNOdFXckPJLjOgY96OkKPHu8/wDWB/mAPDOfzpwBLkbC\nwts6Pof3QQi4nvEx9P7532mrf4fn8bnPCWPBvLrz4e1mzhy48wx/rufoTtPUwQ/3cJ/n4bucvTV3\nrnedOXYbS/s4pcznb7RZLkvSwfB6Hx4eHrrMsJbcGXLnms9ZB8jzWIHF5QwbQPv4N5eTD9gyGF0n\nSVx38vP8/KyPH4/NyJ5vjPwhX26nmaevvvqq9ymE0GvDfqnrs0tChRB+uaR/XS1c/ocl/Spncvbr\nz9Vaf/f+798s6WeFEH5U7chQSfrZkqgZ+utqrT/qN9dafzSE8Jsl/UuS/mQI4T9WO2b0l6odHfor\n6/k0J6kdMfqL1Ark/48hhN8r6Wfs9yRJ/3St9atv2m9r3cnIX67zbqibgXh5ff4ETJH7tq6rnp+a\np7MuW9sJq6qSq1YNp8KkoJfXg1VxQDgWLZYaKxGCdLlcmzHatn7WLW1B4KVzqFI6FIQbFaj9WquC\n2m7eGPfziWvQ68u9hXHrnXlTrbWXlsgqCio7Y9IUieeqeDjLPX4HGw5iADfLsmjdNs2p5UKh6Jr3\nG3vpF+/b5dLObq77nlzOspc+LaTtYE86DP2Sd0awnsOQUjtlpdQ2BynF/ffhYTcmRC1vKVVN6dLP\ni+YdbkxKKTtT2Y7h4zg5VzywsRR1fnl5OYGBJhdmVIxxekuZ+5z4M1BAeckqpSrNsdUh3ZCtPZVh\nv+/het03LVXFubXdAVFXpOHTklOSeuky2rCu657PtyqmvZi+sQkYHQDL5XLRBjCIUWFnRV0RK8Z+\n0o0ba64OPEI7dSYb8PKLyARh9mqsainHKTgqrfTXuq8v8u0IH/MMz0Mj9YcxSimp5mNDDbrAmdc0\nTx0IYETciaC/HnlwUNS1XAgKsclxjEGltLqEWyntABGiLNOkZUhxKWonkrU2x86YsV7OYPfM4ElH\nDjyOE/Li4fVW4kZ9NzV9QFd6WJj+UuLIdQxrGx3x8vJyvH8f11r2lJu8tjWupmdSPPKvXYa6bdjn\nE5kZI1wnq7I/43a76ZkNJzpSiMYNXn1Nmp5jXGtoZduyilJMWu9H5IofHxvaNu5PWJalRXpKVcmb\npt0p3nY9sZasqqoQW5mrKRyA9wQiLTUnpaRbsnHTnolf95JRavUyAWBcgCmvZDOmhXhamYfsXffE\nGHvNcLfRDrABfb6Oas6aU1JNQfN86+le2DvpiPRwmhM2owbpvm7Summ6SFtd+272VHanPgalqbGd\nubR3STqVmQJHvLy8qOz25XLZS0PlckqnS5d9Z30Muj7uZ9mH0EkgcMnrvR2LWnIjlNat1T1GL7y8\nvBx5+zm3fNWxEPJnXl+iTunfuP9Okn719/nOfyfpd+///vcl/cOSflgtjD5L+n8k/UeSfmut9a1i\n96q1/kgI4X9WY0b/GbWIxR+X9Btrrb/vje/XEMI/qhbG/ycl/UpJr5L+kKTfMALfb3pVHR7aSdDN\ne57nuYXC9wVKSBMqHAPKmbLXaytV4XlJ05zOIE06LVKUBv/mb16WqdaqZInLgBrpUJAsRs7spQ3O\nujnoc9DDAvHcU8IFhNj+8l/+y/ru+w/9XRgbZ+hYyIwXoShC2s4K8xxnFRxQAhzmeZZiO5EDBYFi\nr51RORQ1Hq1vsHr//r0+fvx42pjhxjOlI6QnScXydBpganN1bGA7M0ohnGsRosR5D4AHg8x7Hx4e\n+jz3s4iNTcJDfoslc2fG2Qja7Aw46RS11gN0DWCVv93vd6Xdix83/pEL6kxqm78z00b+F2CMNt3v\nd5Vce0mzbdsU3jDKjMmyLMo7C89mozkd56x3J2NZ9LAr6a50999+ooqzaZ6DSD+YsxBCO6IvnXN4\nMY7OzPCZpyc464GRdflY17VvXHOASfuRA0+nYMwZYzfk/N/vZcy7nNvBG22dnYGMg6S+MdAAYgjq\n8uC6B50khZMuQq/B0LuTxNh75Y2aS2eM+vqu9bRm+hgUdRnz7/Gdbds6m+WM3zztshDO6Txv5Xcy\np+g55MRlhPc64+esOW3je87UOsOdUtLT09Nps2op5XT4SYyx/93nm/bzHCIQPoaj/HhfGG+XPy6X\ne2SbvrdxPebb0wuwHzDeHjWjHS4j02T1OmvVlo8ya4wfkTsuZ63pkztw3lfWKBG1nHOv4TraGk9X\nwP45G8u7p3LVlJJKOHQv68ixBOPHumK+ICK22uqOk4+N7Pn6cn1Le9zxyDn30PyynSswMI/IztPT\n005OWcRDX+b6bFBa2/n1v/4n8f3fJel3fcN3/W4d4PYH+f6mluf6W77J+36wl7RfGFrVdnb4FvZC\n8qmdipDiObm7b3gJBzPB5L6+vur2cP3EO7xcLtruS1PsO5jlPgSRBdpLxARpy1k1RMV0bOzAYPNc\nB5keDkVQv/e973XD7EI9hmo/yVdSUalVZWvK78OHD33MUBLRxoYQwbt37/TVV43IxoCjVNnBigIE\nKMOkchpF2sdYpkh9nBi7GKQQpKyqZV102RW2l9HAsHih6imdi0/jWHju0DkR/VA4l8tFeW3zlLcs\nKanO0rJurZ6fJKV2Hvk0JamWk1JtLNxR7shBEQrs4bGFBpf72tkCQA9GhPvcm89lk4KU4tSVFePA\n/3mnpyaklBqLWLZ2EldIul0bYL5ebqeTvHj3KXQXDicEuUypnV0Oo0HOV0ko7rrngEnr/d7Zm+4w\n5VYYOrIRoB6RAZwc1hlrk98wMAB9lz08DGfCQgi97mdN+99rUN2K5t0ZzFHKW2PQq5on78CNzR0O\nQKRz6JW/87nrFXd82/fPYWsHMbSZ8XCw4N+LMWrddqfxclHeNtUYpBTbOISWq67BSeW5tdbOTLcT\n09Tf4/qtye9RDslTa1hDgA90Qa31tNlkSjuLvOdAu/PAOxmPGNPJGPdUlH1cQ62qBk615yKKnesO\n1nV2HBx8OMBKKWnJWXk7alRSuxTdSYSiOyymX1Rrz/H19Y4ufP/+/ckxk46NTHNMCqXVV0YPAkxY\nX9t21LR1Vr3WFvHAbrS+7mH5WlslkrCf1hfPrLM7Ni5fnk7l4Lj3p7S6vmHXow7qaq09V3aKsdX/\nZR6iWkQpVE3piHb1Q1TWPac/VNVGKx1yvjuvtKE7IvMsharnp6933Xw5VXJwR1XSyQ4ypm1cmzPt\n7Gt3TkNSqa1mLpUxctnBrxEekCWeXpdS0m0+DmlxJ4iUhVKKphBbPm890jOac1tValGtO6F02Umr\n7djf4Y4euuEytTV5fbjIlvJnXT+VxfP/f3O5EkBgUExeCN9DlQAHNr+4J+QL2HPxEAryz0amEkXl\nLMzz83NXeBhZjBHtwqNCsSPMKPKnpye9f//+tNmHC2aMUBfX6+trDzWgoDxf1kNxy7Lo/fv3kg4j\nS+4lYQr6yhiM4a6RAfKalL5T0MM8bpSd5ZOOHE4ULWHxg9E5b5phvgGsfI5swFg5iGAunZ2hjfz9\nBHhM8aEMJZ12StIX5tef31MaYtS7d++MoT0fT+jhOmfStm3rgBugCjvh44X8vLy8dBnAMEnHWfGS\nTpUXUKAYSgDD/X4/1fqj77ybfpBr6qCZ76LMR6Dna5GwlL8D40kfnEFl3BhTl0PGDRlgLXk1Dmc+\n3wq/4rC5U+Sy5eytO7AAN3eWkCVYZ57P93yHr/+4/Lm8wzC5XI3AeLyXsXsrRcXDuz4nHvXJOfdo\n0uiIucPka3LMCWfcR0cLEI88edTANzU5YKfftNOdPJcjLzPGmI36EJnyShoO7rEJrpcZX97L2DIP\nPs7039lsSf1EP2wMeoRn+pw4APM9CrybseIzlyFvD+0m99tJCeTT2UfmHr3sTi1j7CDQIzjUOh4d\nMXeGJfWooDPDfJe5LqX0kks4Sb4PwWXXU4ic2fSoicso/cQGjQSD60z0PFhjWY7z7F9eXrqN3Lat\n6zz0orc153xKNeIextDHm2gFOMRz12utnTn9Ete3oPQzrxCCrtNFeSvtTPooLWvzglJK+vDuXc8j\nA4QiBAjXsiytHuReWw+iDLCR0n6GcDhvhpIOI/j+/XtdLpfTxg7ujzGq1KxlvZ8MDULUmT/z1Ecv\n1k+poN+ABN9xTWj48fFRDw8PJ0Pgifptwbzqdrt2RcvzPnz4oGmautfvSfZ4fH56CuAWpcD3egj7\ncum7U2FVUb4ptfydEs5pGPzbPWeMcjdQpbbznffP1m3p3nOtVdvO0o6GLWqWygGqURQ1R+W1MbZx\nPpiMrsjmqe+oxMA4S96ZFQMEvlmHfiNbyIsDAHdoQpRKPcp4xXlSnM+ho+fn567wcm61Ubc1q+Qj\nhOtOmYeDPKQkqdeGROZQ6pQjSym1M8rT4ZKjPLfSdsYT+mTHci/vkxpz66DBNyzcX14U6vm89x7+\ntDAqudljlQ1nSZpAhDfrmI6hTd80OAIXcoI9NIqB6I5Xrr1GctirIEwh9d3rU4yaLVSHcWXs3Bg6\nO0Sb3QGhnXxvnmfF2k4E87qgPnbuaAMiHEAzLg7Kfbzc+XRWyMPkyK87CThGKU5SPYOW2/Whs6ge\n+u+F5+vB7MbY8o8f9pSqmA6d6GOBXDmD5eF4JxD8M2dwO3CvLcLG3122SymadxY3hVadYFuWVl0i\nflos3q+sqjAd1QE6WNnrs/p819oqrczTpa/jrKq15F77kiggJ+K1SFDVJc2K9ezEuNPrjobrxWna\nyyDmdvob88qF7Pq8511n3AeHjTY7+y/pxLZ3ZzJULetdW15VdS727zK5rVnr0qoEkIt5vdx6Gogf\nCtD10m7Xpjl11tOL9Dtg572essA75+tNikm5SkVBT68vqjF0sKgUdd/W0/zRdn5P06StFt23o64w\nzjprmzbxOfYnpdQBrsvZVovSZe6pN1/i+haUfu5lQsVCGBk7WA6ETTozcZfLpZe1cQYE4XDwh+Ji\nEcMOPD09nbzYZErNvfzvx6h6qMI9tLEEBu8DVNM2vFzCj3wOA4XAS8eu4Rjjaec9IN1roknnXZV4\n+r6pSDo2ETmTQZ+daeyKrJzrCY7sFQaUMaI9ziJ5+IM5893oTTyOjUM+HxhBNxxurJ3Nc8DJZ11R\nGgvM5Z4sbRg9/23bTnm77o3TX2dieG4xY4G8O1vk7MbINPr3uVC+eP2AMmcKOsg3x4e15fPs8uzt\n9nXD3Dtr61UMYGWZSwebI3uK3HtKA3NIO31M+JszWt4vLl/fnl4gHXU0XTf4GnHGjXHg8Ae+y/3I\nM+/h+ZI6A+RrwcHVyOSN4N0ZQWfIaCvj+paseQSD/niI1Jk17nFQyn2sbwfc3Osy4rLmupI+Mx5j\nm/g/fXVGfNRzfM/ZVpfVkSnm7z7mknp+okdD3KEspXTwQASOHF6fM9f/0hkcMp8OCE+geQC7/J3L\nx5p1iWyNtrKnd5BCEM9VLCARfP05I+f9chDMuDt54+w4DprLEePna5BoHe11vUP7sYV8hm7mWSml\nU3qUt8FJH9o+jqnbXOwltuPrr78+Mf/Yg3VdTydWvTVWY+RnlH9Yax9b5Bv55Dn7Gz6Ri29yfQtK\nP/OqartQ2+7455OnMU3tmMzL5aJpTrpc586+MZnLeldV6aHvEYyiDNeStdUz+HABr7X2UGmMzWua\nrpfjiM4adLs+fBKy8kWIcic529/BAuqe6s4EwYASQkBhdC9/Bz8oUmdM+U6MQcty74uJxeULgHAz\n4BRGYtu2XqMwpqB1a6zzui39ZBeUmwMFZ4XKnsc5hdhzozz05YaMxcv8uRG/Xm6NkduVIXU+lauS\nDnZgvkYVWRhklnJdtJW7is7HFLpyq3lTVD31i3HF+3ZnBABTasufwptn/KSDrXTAcL/f9fXXXyvG\nvR5eXrXVrHmeNE2pnwiTVaQUVGP7GQF+l5+aWxt05FAhgyGEzgyH0HJUQ2q72481dpxG1Y3lfhoN\nEQCvKwogP4XxllfFdDBpvs62rdUaXIxV9tQA/6khKNlGCZcLB24ppW6EzoY2K8bGcEWdT4By4ApL\nMV0u2v4/9s5kS25cSdoGkIwpU1JVd7//+/Wib9/KISI4APgX4AcaKfXmVy1qkTwnT0qRDBKDw93c\n3OHIW04kMn8M4UapRWSqA9VpnieVkmtOck469V0bMxxKaWPNeZ4zjc1oKWqe9iHbUopKDAp913Lm\nfjX/buBZN+ipUkpL1akOWFLXRZWSldKiOaWaL6haAcCNoctQiwAty091ZqWaaxoU1XfbqXMORKn5\nyBizrpzBdpDrzsFRb4t57erJWvWgpE2eYTkdMMOwdV1X86DjVgt16LpWp9Qdbt7TQGuu+ZVECZCn\naZyVlu04U04nc4eAtU873LFqYCfV/G0HaO4UHtMyYqybO3MukoLO15tKiOqGk+aUpbXqCXqhOYwh\ntM2npWxVDtBNOFFhrWyinHQ5VT1XlHf6zOWvHSqhml9KNI02+7wRJRpOtdj8siytFvnletY8LXrc\nq127Xq9Sqaw87/78/GzzDUAMoT53OO0dANczHjF05wM9zTyFLIW8lRvEPnuUzOtot9JPq60jLa4R\nPUuRSlQXB6lEZUXNab/hledIUolB9/HZHAp30n73+gKlv31tniULgcT7IzvlXq170e75e34Hx/Gh\nrACKCEFvRijn3E4l4V3uPQEGHYS6QvTC/SwM96zwxJ1h8XbjEWPUj0aDMXIG5ZhfywKgbxT4Z0E6\noCK3xZk1FpiffuXGm522Hgp1dseZAPrmgN/Ddc5wHdlh2kubPGdI2lgX+uwLGkDCXHgOIuPkzC9t\naakIpezmwctoMZ6+yYl3IkduqJBP3vurOXTm3gE8l4MQP7UEZsnb4ow4QMFlBLDoIV5nHduKDPu8\nT1gjT1VwcEw7j/UI3Znx+fT58lCtM1oennPHwp/n69RZIF/z3haPgHiY2vUPERWXE9rpawkn5jhn\n3ocjS+z1Hd35dtlw5pJnOHPlEYTj+Dj4ow3+HJ8zZIc+ekToyN67s4sO9XxddAqMHvLjsuqAgLYx\nb/TH/8a93Mfc8Jv58XV3ZKrcwfd15uw470CmfU37/KD3eGcy0Ocgn3cRSqe9yA/Okjt/zsK7bvIx\n8TVzPHSEZ/jYOCBj/Tro8eiGR+48YiOp2T766ClLvO+oszyicyxf5qlkfiqdy4O3wfuCTj+y5Pyf\nVB537HwsuZwBddvK+3wuPz4+doww9gX95PPoa9SZcrc7yAWfl7JFlP6u7fdfoPQ3rzphfVv0GAmv\nt+iLp+7422pxTtOk9/e6o49FMwxDExyEeRpnLXPSuMwt31Da775dlkVJRUvZcl48v88BJYvVwY0b\nNg+fYOikWg9wGufd3whveG5p8/rWnYQqQctcawMuJSupqISo4XzRtCQt2UFQllRaLtXLy8tOqSvn\nlqvJbnQPXeIUcDY1SgFAhqfMmLvRdGPA3zHILO5miLuoOPSNgXDljLIgJxUvVSnr3A8qS9K0PBT7\nTfmw8El095Aa4+tF492Ae7sbOJ6TuljrKl4vt3ZPy7PstxJPnv/GPbR/6Laao27EAQdS0bKeeb2U\nfa1P1oRXCVAXax2+0yB1USktCmEf3gwhaDif205jLhw2N5hdV0/QCt2W3oEBaVGBaam1gA/gdcc+\nhNCe48DMDT1MHP9nXbtzxQ9ykXOu9QZlm3NCUOx7dcPQTgBbcm7MoGLdUdxA+8oee1jeDRfrkbGb\npll9v50Lj6PTKejU7TeJOGhCNlz+dwZ1yXo+xlbbMaeiedofqYkcN3Ym15O2as5wUFqn4JgSALg4\nMm7oK+aDSM7pdNJ5GBqzmH2TRowtP9lBgsvY6TxU9nyo5ep+5Whl0zMO8o/g3cFdc6JC1BC7Jt/s\nFmdOnfXmfcdc5W6dd9jiOe03C6H/p2lSVi3l0w3Drrakh7wduPX1KKWdY+YXDjc1tFuf1yiZbyp0\nHUp/3AEJIbQcWGd30XFcpZTW31BKq63tTsdzfDRGNIQaaZnSzyWM0BV+eqG/y9sJWGXN+to/X06t\nHrKTLDD8OecdSxtCDX2jX19eXprcegTHHWd0pddR5X2uo7gea6WRowOK80UU7na7VcAeO/VhK+nI\nfPtaR6amaaq79MepjUfTbadB3WloJI+07sxP6e9KKf0Cpb97OVvDv1E0TDqCjFAieIS1Ob6Mifa8\nG18gXoOMfI9lqTvuXMG7twtrgTACKPDyAJU8F+Pj3jqMlbQtZN9dmFLalc45eowAKWd6CW8cjeP9\nfpe0sS5uNJ3hRNE2oLNenmtaSmnKxo3FVqJpC+mjJPgO4+7A7RjeYrycdXSG8diuVqbL5IK+8vmx\nXcjTERzw7F+1CbnwECz3urFwIOzjKW3OTnMu0s8nQXkfjgrWmTBnhPgM+UeujmFJN/puCGiHK1bW\nnXvwvIvnArJR7L8CpMy55wU6iPE1xnucUefiXtaZs6T83WXD2RrGm8tZYE894DvOpnE5Y+KMFY6I\nf9+dG2+Py5gz074Ojg6RRxBYry4bjJmDVWTXdZfLKbKH0Xb9yny5rCLLHsXxZ+M0w/ghOw4MnI1m\n3Jdl2ekCl1FkkM9d7h1gsAZ8rXstSZcjnsl7aZs/m7Y7keBRAGf1uHyeIBGQV8aR/tN+X0u0H73n\nMsq69FCyr4kjY/crZhc5c2fiKPPuODEe6LojY0u7sVE49n3ft9O0GGdOBqtO3dRAIVEy10nYVuaS\ntUmfAIcxxlY/FLAISPZ5Qf58wy6fM6aMAXK0LMsu+uNzzDuw78w57eY+1gs6h/d73VfmnXuQr9fX\n150spINT8/97fYHS371K0eVylkrQ58e9nRXfxb6ygnP66bQIJtEZAIwHgu6C6EqvhQKKtOQttMLZ\n3EpFZT1DmPqOzoSyQD23EmN+DH2gPGAlHo+HcknqesuPXBUWytNzRptH3m/HAaJQXl5elHPNpU1z\nzbsi/xbDFlUUtSmwJeeWWyYzXK4U+L+0GXiOV8wl6XzZPOJpHmu1g75TDtqOgVvqyRdzTvp8Pra5\nC1Ic6o7DEjej5eGnX7Efzgowtsx/VaY1N8pZS+YJ48hYMhfMTQiVcWtnlJsyczCBUj2GqI/GGyXl\nfWthqJXp4dkOXJDfZVk050VJuVWSKFn1XOv1HfSHwvgOSHFgpKqcegNAR7DvhoxcusvpVHPqVkCI\ncSav1mXDQZ7LsqR6QpUB6+YgxljHO+/D8O2evNQc2oPjcARerMVfORoe7gMIuXP2KwDpIWFPP2Ee\nGygrucqvOXMYegeLzvp5jqXLjLe3ATupykgpLQ/yfD63PM+uX3c7p6XuAu6i5pyUgxqbPOdUa6B2\nG0AJsdaf9FJiw8oIjsYuSitISqnVJ+aIREAYAAW9xTxO81gjWQYu3elwQIKxPqbBsA7q+NZd6cNw\nUghRIWXFvK/j6mCC57XyXOuazsuiYmAYHQhT2cBxSa1yS861aH4uacttLWoVXFjTtU5qkXJq8+ak\nhjN1Hn52kMPfqXftTiyf+96BfuhUlFWiNOdtY05e+9aqCuTKsC9zavnKjFkppVUjOfeDOoXdWnVi\nxckgxhc7gc7yNULf/RAC10vcx9pyppzUMsAa48FcnU71nHr2QMDeMgYuD4BlyAknwJossGbWNXC5\nXFruLJui/LhSX79eajHaWu37vuaJrxEtTm2a854ccmfw+Xz+XUTpFyj93SvYBg8vQ+QKG6XIIkCY\n2XHvzKjv2M251kVj0bh37JtajgYQYXFvzJmwYorHvSwWKIpf2nJyAMkYRxYJeTDe3yPAcHDritQZ\nLBaPs7osaE43gWmFLWFMXFnw+8hE/SpvEaaC9sKKYaCdkTsys26AjrvF3TNlrBwcuMfMvKMYCHU7\nWKS/rkydQXDFwnedoWGMSLbncsNxZLucJUPe3LHCYaJ9PibOyvmzAcXO/PpBD8d5c3aAdeQbM3x8\n+D7OEfPB3HkI0Nk0mBX/u/cBOWFNAG54BzLljJuPL/PL5zyHdjAWPhceQvR5QN79N0bLNz+xhtwZ\nwflkvPyZvNOdUuaO+eYdPjYO2jwMS5/d6XV2TNr0lLeJ9mBUuY9+OmvoOtVllnf7db1ed9GqI+h2\n+fSxhX33Mfd7XWaRFcAuc8wclFKkvtN9Gnef47z6uvU5kTZ2lfH197o8uy1wPco7nORwZszXEv12\nB59xYRc/6TO8x9lGBzqex0x/mdthGFrb6NNRZyJXzuzSLklNHxB1Yb34+vYIybHOpxMJroOxg36k\nprOPPm7MrdfFbo5U2PZG+Gle1+v1l2vJnX13jFy/eWTK7Tl9ZJ2SNobu5Khv2gkTDAtKP52dTyk1\nm0t7eS8OHnLTdV09geZvuL5A6W9eORdNy+bhMtGAIP9BQMkpwsAiCO6puQB8+/atCfo8LToNZzty\ns54U1DzmENoZ3q5QpM2gIuj+NxadJz1LW/iaI+fad0L1zPtuqDtv12ewwxUhxnh4TtDQnzSNdVGT\nC9WfTgpdp8c46vF4VOC45hyST+egxBc0OU4qoeW6sQte2nZ27vJa57QDAq6YlLKup3MzBo9prLm8\ngNep7kRtICzUU4eOQEKh6Hw5NcAzzaO6Pup8OakoK6qoj1uoZxh6LcssdiDT9lPXK5afd0k7gxlK\naT/SPpyMPKHACetx36/CgvwduXCD7x6yM40xBtWd09u6SEU1z7Tvdu9gHr1QNEaUv88pKayMSSql\n7ZDvLHWEWrjcw7OOCp5xc4fPc8ocwLFWU0rqhkHPaTs7+zwMdee8sZ87Q5GlGLYcvqS6Q53xYkey\nOxOeY+e1hXkHesBBkztBrjMcnAIGYlxPcQlr9CR0u3HySANzjo4ohzF1tvTI5PBd5naeZ3Uh6NT3\nyjmtsr05VTiHjE3Xdeq7oTHrQcZArTUzPecO4CxVho35Z72XsuWfU+0glNJOZOJy1jDn3HLOkZs0\nz+rjflOR99ef4zLRwEWMjQUsYStvhsyksuXPp1L0GEH2pGoAACAASURBVMd6Kt0K4mFMGacGFle9\nmJS1lO3UpK5fmWXmNkSduv2Rr0fWvs5vxRU/RQf082EiHh2QiqZpK97OngByaaWiGEPbK+GMqySV\nKE1plnJSScsuP9zn55hqBAgLfbfL1/Z62kdHCefcnX3a0jaIrpVYGutZpFPXK6fSTrtyveLjCLkB\nkeJrxAEtOtcjUUdyxR0pdyh8AzDPcdCPcwCoxLF2JpaUQanalaSipNJS8HLObZx4zzAMuyOjXX8N\nw1nhq07pP+NCIFEyr6+vjQHwBYJxkdQ27rghgrXjPjcA3MfCcc/cUwFc6XgYDg8cgZK2k3RQorSX\nfgDSHIh4rpiztm7EMYrO6pHXwiKQ9mUwnJW5XC5tDPnMQaj31xc0/XJm6ZhbxmLCWNMXBwOMoSsY\nFjb9+9V3oxktz0Pknc62wPoiA1RNIEfIx+kYkv1Vv9x7RRm6sTnW73SvmHbRNkm7Qw74HFn09jhg\ncsZS2sCfK0bGDYXKfa7gaPP9ft8AieX2kRd2Pp93xgWWGKfKD1dwNsHlCIWLfDsbzthjQN2ZO44X\nY3HMGebyzUnOJnP9iuVDBqnU4M+F+f8VQ310WpArT+U4Ajrm/Bg69CiGj+PRgXEw6+NMH3w83Bmi\n3UcQ7N8/yjn3OYPmOu1Ya5LveUTCx5j5+ZW+dNbY+8o9MMgeQuc55K07aGUdoXc9f5U+OuN5JCxc\nF6J7ACwOTJAnT2mibS6XyJL/jT4fGXB/t2+CJGpAvwD2R+YPu0AbHfjST48iSFs6jW+2oS28j89g\n9Fz/u87lPmwYz8bZZEydlaTdrH9+aBtri/87000aF2PqGIG/HfUrETba76cwuU5wfXyM8BCBw7HH\nHriOIfooaTeOrHnmikiWr/fd5s2cd3beZf13ri9Q+psXCwtFR5FcJgxj/HyMLc/04/2zKVbC4nyX\nskVe9wzPivegKBFiF+SwsgNdqLsdASsAFgdYrqxIE3Dh88VLHifKo4VqKv3QALNCqTVb19NoXIGx\n4FFmLARnilJKmnPSc66LP+es03lou2NRduwqdIDjit6ZH09P4DsOtBkHPEk3JoTYS9lY4LzUs91L\nrtUIeLcbWZRRKaXlsjo7t6yM37Qufjc8G4gISmlZa4FueaL05ajcGwu47gTth67uLA5bysUxyd2N\nFPmqpJHwncbQSS2Xl74y5q4w+75TKbmxJMsyV/akC7W+6eogpVRP9ZL2ThCg3RUmsqBca3IyXi3X\nK2cl2zR1VKg815WpP98NXYxRyzTV3b8GUGjD0fA5kCH3cXOUirou7uTBAb23j+c643Yehv0Z37nm\n6KoEpcXC/6W03dclhLZeqQHLWfC+kcENPe1xltzn38eSNXVknXEukF/G9rguHKB3sTJQOZXGQDkQ\npb3OsDpghaniHnZuu05xgJ1SaiwsV5XZfnM4Sqin86GTSqlVEgAYq451QJ5SUl4WDQZ8p2WppzOF\nLY+vX/O/YXXpJ5enb6FXXAbRsw6SGUsH0OhE5MnB/tHJ2ZyhoFLW+q5rHmswwEqNzabvSlYoW+1W\ndUFLSa0Kh+chppTayXnYM+ZxGScp5ZbHX9Z8dJdHfrqua0z6NM4qWe1EM+zN7XbbkRU4MoTcYTKd\naAkhaB4f6uMG/mKRyrIRRP3Q6fZyrXnjedtIzLGjPO9yuTSygXXmejelGq3LaV+9wckod8SZYy/r\nxel3RVEh9iqKqqVfO4W4bWBmDbUc7aFXiZtMsYkLNp05o62OOcj/529HRyPEL6b0H3N5uAhj6EoC\nT47J8516zph5eSM/G949MEm7RQbgQvHyPt4ByPIEei4UFTlCHkp7PB475oJKAdzPQvI2UMbKwyf+\nHGeWnB2j/UdGzvMYUQBuBGk333ew62CNNrvCBni1ENA6/rCjGBtnkPj9q9xhFJkzqR7e8PCR584y\n3uQX832MLZfX1uMe5pa5nKaphbN5rrd9Bwa6bfe1j5//3ZXj0Qt2EHUcH3cSjuyGRwcAop6fhEOA\nQaJ+rrSdKMX4UlkB+XY21tcFwITv+AYnB+zMIf3z5/kc+7yxFp25yDnvGAqXEwcYLjvObPkacBny\n9cJYef6yp2XAiByZFAdxx3d7aofLHqFtH0/vv6cLONvqzLrngzrDDvPkAOS4M97b6PLpjoaDC8bC\nZdSjPM6UexsdVPscS1v0AN3u8+mAz+faAYU73Q66W2qRfq6ve5RJQJeDey6PUByBvzv/2AcvN0Q4\nmO+5rnQdUkotCn/MdT3qEQecyFhzGszJQedwr594xHvR7x5qZy3wbmdFAUr031lbxoG2+1z4/PhY\ne7oIjCn9IyxPpBM5QL+TqkC/nIByG4WsNHCv/aEayBjvK6U04O19PDoe6CXeiZ5zm+zrE1lkfD3C\n5Sy8y73bjaON+P+9vkDp33DBungooo9R8zgqzbOWaWqnRGCsEIbPz88aeohRqZR28giCBgPiRsuV\ncM5JpWSdzydJ9f/D0Os+PpRU86M4ycbDGFxHBgNwdrpcau2xGNUNg67ncxOW+/3evCwWCwDJFdw4\nji2kFmNsuylR/iS6Ywwp6B3DmlsGA7V6xV4ug++g4Ph3KUUlpVZL0tmoo9fsZ4YP/UmpSOO8SF2s\nuxoB5an+xL5vdTNh5/KyKJSiU9/Xs9ONNffxRU4cDAxd184ldyX0eDyah41sSeuJNqb4uKcZ6PVE\nK1fCOW8y4ACZcT+Cj6MRYuy8dI0rcjd+OReVIk3TrBg3QMfO+CitDL7UBbUd2pfTSS/Xa92tnbPO\nw6DLmnsNM9XG2EADbcu57px+PO879s83eTgbLmkH7D382sBIV8/1xtmbU2r/3923rhcfz66rp8Jw\nTnp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8evvRu0QfW7/DPnrR8rHX9ZGDpC62Y2hpT4s6hn3aGP13W+GHlQCinYho7GfoNE/b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A2nFm3xaArPYkw94oZeoK2ME+1zPTDPs56fn6tNwQnwMfeT83gf48fco9+QL2TKdSw6k4jk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\neOLwAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/png": {
              "width": 338,
              "height": 252
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j7OwKBVMOzek",
        "colab_type": "code",
        "outputId": "3a70a339-9f23-4036-bece-fb49d1995734",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# remove previously processed images\n",
        "\n",
        "!rm -r segmented_img\n",
        "!mkdir -p segmented_img/img1"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "rm: cannot remove 'segmented_img': No such file or directory\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ftOopQRYGZhS",
        "colab_type": "code",
        "outputId": "e2871ad6-389f-4659-b37f-f5b22217c466",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        }
      },
      "source": [
        "### Process image to get characters\n",
        "\n",
        "import cv2 \n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import os\n",
        "\n",
        "np.set_printoptions()\n",
        "\n",
        "#------------------Functions------------------#\n",
        "\n",
        "def line_array(array):\n",
        "\tlist_x_upper = []\n",
        "\tlist_x_lower = []\n",
        "\tfor y in range(5, len(array)-5):\n",
        "\t\ts_a, s_p = strtline(y, array)\n",
        "\t\te_a, e_p = endline(y, array)\n",
        "\t\tif s_a>=7 and s_p>=5:\n",
        "\t\t\tlist_x_upper.append(y)\n",
        "\t\t\t# bin_img[y][:] = 255\n",
        "\t\tif e_a>=5 and e_p>=7:\n",
        "\t\t\tlist_x_lower.append(y)\n",
        "\t\t\t# bin_img[y][:] = 255\n",
        "\treturn list_x_upper, list_x_lower\n",
        "\n",
        "def strtline(y, array):\n",
        "\tcount_ahead = 0\n",
        "\tcount_prev = 0\n",
        "\tfor i in array[y:y+10]:\n",
        "\t\tif i > 3:\n",
        "\t\t\tcount_ahead+= 1  \n",
        "\tfor i in array[y-10:y]:\n",
        "\t\tif i==0:\n",
        "\t\t\tcount_prev += 1  \n",
        "\treturn count_ahead, count_prev\n",
        "\n",
        "def endline(y, array):\n",
        "\tcount_ahead = 0\n",
        "\tcount_prev = 0\n",
        "\tfor i in array[y:y+10]:\n",
        "\t\tif i==0:\n",
        "\t\t\tcount_ahead+= 1  \n",
        "\tfor i in array[y-10:y]:\n",
        "\t\tif i >3:\n",
        "\t\t\tcount_prev += 1  \n",
        "\treturn count_ahead, count_prev\n",
        "\n",
        "def endline_word(y, array, a):\n",
        "\tcount_ahead = 0\n",
        "\tcount_prev = 0\n",
        "\tfor i in array[y:y+2*a]:\n",
        "\t\tif i < 2:\n",
        "\t\t\tcount_ahead+= 1  \n",
        "\tfor i in array[y-a:y]:\n",
        "\t\tif i > 2:\n",
        "\t\t\tcount_prev += 1  \n",
        "\treturn count_prev ,count_ahead\n",
        "\n",
        "def end_line_array(array, a):\n",
        "\tlist_endlines = []\n",
        "\tfor y in range(len(array)):\n",
        "\t\te_p, e_a = endline_word(y, array, a)\n",
        "\t\t# print(e_p, e_a)\n",
        "\t\tif e_a >= int(1.5*a) and e_p >= int(0.7*a):\n",
        "\t\t\tlist_endlines.append(y)\n",
        "\treturn list_endlines\n",
        "\n",
        "def refine_endword(array):\n",
        "\trefine_list = []\n",
        "\tfor y in range(len(array)-1):\n",
        "\t\tif array[y]+1 < array[y+1]:\n",
        "\t\t\trefine_list.append(array[y])\n",
        "\trefine_list.append(array[-1])\n",
        "\treturn refine_list\n",
        "\n",
        "\n",
        "\n",
        "def refine_array(array_upper, array_lower):\n",
        "\tupperlines = []\n",
        "\tlowerlines = []\n",
        "\tfor y in range(len(array_upper)-1):\n",
        "\t\tif array_upper[y] + 5 < array_upper[y+1]:\n",
        "\t\t\tupperlines.append(array_upper[y]-10)\n",
        "\tfor y in range(len(array_lower)-1):\n",
        "\t\tif array_lower[y] + 5 < array_lower[y+1]:\n",
        "\t\t\tlowerlines.append(array_lower[y]+10)\n",
        "\n",
        "\tupperlines.append(array_upper[-1]-10)\n",
        "\tlowerlines.append(array_lower[-1]+10)\n",
        "\t\n",
        "\treturn upperlines, lowerlines\n",
        "\n",
        "def letter_width(contours):\n",
        "\tletter_width_sum = 0\n",
        "\tcount = 0\n",
        "\tfor cnt in contours:\n",
        "\t\tif cv2.contourArea(cnt) > 20:\n",
        "\t\t\tx,y,w,h = cv2.boundingRect(cnt)\n",
        "\t\t\tletter_width_sum += w\n",
        "\t\t\tcount += 1\n",
        "\n",
        "\treturn letter_width_sum/count\n",
        "\n",
        "\n",
        "def end_wrd_dtct(lines, i, bin_img, mean_lttr_width):\n",
        "\tcount_y = np.zeros(shape = width)\n",
        "\tfor x in range(width):\n",
        "\t\tfor y in range(lines[i][0],lines[i][1]):\n",
        "\t\t\tif bin_img[y][x] == 255:\n",
        "\t\t\t\tcount_y[x] += 1\n",
        "\tend_lines = end_line_array(count_y, int(mean_lttr_width))\n",
        "\t# print(end_lines)\n",
        "\tendlines = refine_endword(end_lines)\n",
        "\tfor x in endlines:\n",
        "\t\tfinal_thr[lines[i][0]:lines[i][1], x] = 255\n",
        "\treturn endlines\n",
        "\n",
        "def letter_seg(lines_img, x_lines, i):\n",
        "\tcopy_img = lines_img[i].copy()\n",
        "\tx_linescopy = x_lines[i].copy()\n",
        "\t\n",
        "\tletter_img = []\n",
        "\tletter_k = []\n",
        "\t\n",
        "\tchalu_img, contours, hierarchy = cv2.findContours(copy_img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)\t\n",
        "\tfor cnt in contours:\n",
        "\t\tif cv2.contourArea(cnt) > 50:\n",
        "\t\t\tx,y,w,h = cv2.boundingRect(cnt)\n",
        "\t\t\t# letter_img.append(lines_img[i][y:y+h, x:x+w])\n",
        "\t\t\tletter_k.append((x,y,w,h))\n",
        "\n",
        "\tletter = sorted(letter_k, key=lambda student: student[0])\n",
        "\t# print(letter)\n",
        "\tkernel = np.ones((2,2),np.uint8)\n",
        "\tword = 1\n",
        "\tletter_index = 0\n",
        "\tfor e in range(len(letter)):\n",
        "\t\tif(letter[e][0]<x_linescopy[0]):\n",
        "\t\t\tletter_index += 1\n",
        "\t\t\tletter_img_tmp = lines_img[i][letter[e][1]-5:letter[e][1]+letter[e][3]+5,letter[e][0]-5:letter[e][0]+letter[e][2]+5]\n",
        "\t\t\tletter_img = cv2.resize(letter_img_tmp, dsize =(28, 28), interpolation = cv2.INTER_AREA)\n",
        "\t\t\tletter_img = cv2.bitwise_not(letter_img)\n",
        "\t\t\tletter_img = cv2.dilate(255-letter_img,kernel,iterations = 1) #dilation\n",
        "\t\t\tcv2.imwrite('./segmented_img/img1/'+str(i+1)+'_'+str(word)+'_'+str(letter_index)+'.jpg', letter_img)\n",
        "\t\telse:\n",
        "\t\t\tx_linescopy.pop(0)\n",
        "\t\t\tword += 1\n",
        "\t\t\tletter_index = 1\n",
        "\t\t\tletter_img_tmp = lines_img[i][letter[e][1]-5:letter[e][1]+letter[e][3]+5,letter[e][0]-5:letter[e][0]+letter[e][2]+5]\n",
        "\t\t\tletter_img = cv2.resize(letter_img_tmp, dsize =(28, 28), interpolation = cv2.INTER_AREA)\n",
        "\t\t\tletter_img = cv2.bitwise_not(letter_img)\n",
        "\t\t\tletter_img = cv2.dilate(255-letter_img,kernel,iterations = 1) #dilation\n",
        "\t\t\tcv2.imwrite('./segmented_img/img1/'+str(i+1)+'_'+str(word)+'_'+str(letter_index)+'.jpg', letter_img)\n",
        "\t\t\t# print(letter[e][0],x_linescopy[0], word)\n",
        "\t\t\t\t\t\t\n",
        "#------------------/Functions-----------------#\n",
        "\n",
        "\n",
        "#-------------Thresholding Image--------------#\n",
        "\n",
        "\n",
        "print(\"\\n........Program Initiated.......\\n\")\n",
        "src_img= cv2.imread(image_path, 1)\n",
        "copy = src_img.copy()\n",
        "height = src_img.shape[0]\n",
        "width = src_img.shape[1]\n",
        "\n",
        "\n",
        "print(\"\\n Resizing Image........\")\n",
        "src_img = cv2.resize(copy, dsize =(1320, int(1320*height/width)), interpolation = cv2.INTER_AREA)\n",
        "\n",
        "height = src_img.shape[0]\n",
        "width = src_img.shape[1]\n",
        "\n",
        "print(\"#---------Image Info:--------#\")\n",
        "print(\"\\tHeight =\",height,\"\\n\\tWidth =\",width)\n",
        "print(\"#----------------------------#\")\n",
        "\n",
        "grey_img = cv2.cvtColor(src_img, cv2.COLOR_BGR2GRAY)\n",
        "\n",
        "print(\"Applying Adaptive Threshold with kernel :- 21 X 21\")\n",
        "bin_img = cv2.adaptiveThreshold(grey_img,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY_INV,21,20)\n",
        "bin_img1 = bin_img.copy()\n",
        "bin_img2 = bin_img.copy()\n",
        "\n",
        "kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))\n",
        "kernel1 = np.array([[1,0,1],[0,1,0],[1,0,1]], dtype = np.uint8)\n",
        "# final_thr = cv2.morphologyEx(bin_img, cv2.MORPH_OPEN, kernel)\n",
        "# final_thr = cv2.dilate(bin_img,kernel1,iterations = 1)\n",
        "print(\"Noise Removal From Image.........\")\n",
        "final_thr = cv2.morphologyEx(bin_img, cv2.MORPH_CLOSE, kernel)\n",
        "contr_retrival = final_thr.copy()\n",
        "\n",
        "#-------------/Thresholding Image-------------#\n",
        "\n",
        "\n",
        "#-------------Line Detection------------------#\n",
        "print(\"Beginning Character Semenation..............\")\n",
        "count_x = np.zeros(shape= (height))\n",
        "for y in range(height):\n",
        "\tfor x in range(width):\n",
        "\t\tif bin_img[y][x] == 255 :\n",
        "\t\t\tcount_x[y] = count_x[y]+1\n",
        "\t# print(count_x[y])\n",
        "\n",
        "# t = np.arange(0,height, 1)\n",
        "# plt.plot(t, count_x[t])\n",
        "# plt.axis([0, height, 0, 350])\n",
        "\n",
        "upper_lines, lower_lines = line_array(count_x)\n",
        "\n",
        "upperlines, lowerlines = refine_array(upper_lines, lower_lines)\n",
        "\n",
        "# print(upperlines, lowerlines)\n",
        "if len(upperlines)==len(lowerlines):\n",
        "\tlines = []\n",
        "\tfor y in upperlines:\n",
        "\t\tfinal_thr[y][:] = 255\t\n",
        "\tfor y in lowerlines:\n",
        "\t\tfinal_thr[y][:] = 255\n",
        "\tfor y in range(len(upperlines)):\n",
        "\t\tlines.append((upperlines[y], lowerlines[y]))\n",
        "\t\n",
        "else:\n",
        "\tprint(\"Too much noise in image, unable to process.\\nPlease try with another image. Ctrl-C to exit:- \")\n",
        "\tshowimages()\n",
        "\tk = cv2.waitKey(0)\n",
        "\twhile 1:\n",
        "\t\tk = cv2.waitKey(0)\n",
        "\t\tif k & 0xFF == ord('q'):\n",
        "\t\t\tcv2.destroyAllWindows()\n",
        "\t\t\texit()\n",
        "\n",
        "lines = np.array(lines)\n",
        "\n",
        "no_of_lines = len(lines)\n",
        "\n",
        "print(\"\\nGiven Text has   # \",no_of_lines, \" #   no. of lines\")\n",
        "\n",
        "lines_img = []\n",
        "\n",
        "for i in range(no_of_lines):\n",
        "\tlines_img.append(bin_img2[lines[i][0]:lines[i][1], :])\n",
        "\n",
        "#-------------/Line Detection-----------------#\n",
        " \n",
        "\n",
        "#-------------Letter Width Calculation--------#\n",
        "\n",
        "contr_img, contours, hierarchy = cv2.findContours(contr_retrival,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)\n",
        "final_contr = np.zeros((final_thr.shape[0],final_thr.shape[1],3), dtype = np.uint8)\n",
        "cv2.drawContours(src_img, contours, -1, (0,255,0), 1)\n",
        "\n",
        "mean_lttr_width = letter_width(contours)\n",
        "print(\"\\nAverage Width of Each Letter:- \", mean_lttr_width)\n",
        "\n",
        "#-------------/Letter Width Calculation-------#\n",
        "\n",
        "#--------------Word Detection-----------------#\n",
        "x_lines = []\n",
        "\n",
        "for i in range(len(lines_img)):\n",
        "\tx_lines.append(end_wrd_dtct(lines, i, bin_img, mean_lttr_width))\n",
        "\n",
        "for i in range(len(x_lines)):\n",
        "\tx_lines[i].append(width)\n",
        "\n",
        "print(x_lines)\n",
        "#-------------/Word Detection-----------------#\n",
        "\n",
        "#-------------Letter Segmentation-------------#\n",
        "\n",
        "for i in range(len(lines)):\n",
        "\tletter_seg(lines_img, x_lines, i)\t\n",
        "\n",
        "\n",
        "#------------\\Letter Segmentation-------------#\n",
        "\n",
        "\n",
        "#-------------Character segmenting------------#\n",
        "\n",
        "chr_img = bin_img1.copy()\n",
        "\n",
        "contr_img, contours, hierarchy = cv2.findContours(chr_img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)\n",
        "# print(len(contours))\n",
        "# final_contr = np.zeros((final_thr.shape[0],final_thr.shape[1],3), dtype = np.uint8)\n",
        "# cv2.drawContours(src_img, contours, -1, (0,255,0), 1)\n",
        "\n",
        "for cnt in contours:\n",
        "\tif cv2.contourArea(cnt) > 20:\n",
        "\t\tx,y,w,h = cv2.boundingRect(cnt)\n",
        "\t\tcv2.rectangle(src_img,(x,y),(x+w,y+h),(0,255,0),2)\n",
        "\t\t\n",
        "\n",
        "#-------------/Character segmenting-----------# "
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "........Program Initiated.......\n",
            "\n",
            "\n",
            " Resizing Image........\n",
            "#---------Image Info:--------#\n",
            "\tHeight = 990 \n",
            "\tWidth = 1320\n",
            "#----------------------------#\n",
            "Applying Adaptive Threshold with kernel :- 21 X 21\n",
            "Noise Removal From Image.........\n",
            "Beginning Character Semenation..............\n",
            "\n",
            "Given Text has   #  1  #   no. of lines\n",
            "\n",
            "Average Width of Each Letter:-  58.07692307692308\n",
            "[[441, 845, 1217, 1320]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_p-7Nl0KI469",
        "colab_type": "code",
        "outputId": "1e31fa67-8162-48b6-c24e-d5528a18c43a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        }
      },
      "source": [
        "# check processed character\n",
        "\n",
        "# Load image\n",
        "img = cv2.imread('segmented_img/img1/1_1_3.jpg')\n",
        "\n",
        "print(type(img))\n",
        "\n",
        "plt.imshow(img)\n",
        "img.size"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'numpy.ndarray'>\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2352"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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29d0z5/fee29X3xdffPHCbY8//viuvk844YSF2x5xxBFdfT/44INd7a+99tqF237jG9/o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\nSUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/png": {
              "width": 253,
              "height": 250
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XVWcccWXH6BV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# number of characters in whole image\n",
        "\n",
        "num=!ls -l segmented_img/img1/ | wc -l"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mSLO0X1q_ZO4",
        "colab_type": "code",
        "outputId": "9958650e-fa06-4ca3-dce4-7ab2f90eeb3a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 546
        }
      },
      "source": [
        "# check probability of one of the characters\n",
        "\n",
        "%matplotlib inline\n",
        "import helper\n",
        "\n",
        "transform = transforms.Compose([transforms.ToTensor(),\n",
        "  transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5))\n",
        "])\n",
        "data = datasets.ImageFolder('segmented_img/', transform=transform)\n",
        "loader = torch.utils.data.DataLoader(data, batch_size=int(num[0]))\n",
        "images,labels = next(iter(loader))\n",
        "img = images[2].view(1, 2352)\n",
        "with torch.no_grad():\n",
        "    logps = model(img)\n",
        "ps = torch.exp(logps)\n",
        "view_classify(img.view(3, 28, 28), ps)\n",
        "\n",
        "m = ps.argmax(1)\n",
        "print(\"Character: \"+str(chr(m.item()+65)))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Character: E\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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wQHACAAAYIDgBAAAMEJwAAAAGCE4AAAADBCcAAIABghMAAMAAwQkAAGCA4AQAADBAcAIA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\nQmCC\n",
            "text/plain": [
              "<Figure size 432x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/png": {
              "width": 423,
              "height": 512
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0e-Z2l1bvNZa",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "img_names=!ls segmented_img/img1/ | sort\n",
        "nwords=[]\n",
        "nlines=[]\n",
        "for name in img_names:\n",
        "  nwords.append(name[2])\n",
        "  nlines.append(name[0])\n",
        "nwords.append(-1)\n",
        "nlines.append(-1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J36hAaPqYtzf",
        "colab_type": "code",
        "outputId": "c5c74672-05e1-4ab0-e39f-4f8ad40901fe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# recognizing characters in whole image\n",
        "p=''\n",
        "count=1\n",
        "for i in images:\n",
        "  img = i.view(1, 2352)\n",
        "  with torch.no_grad():\n",
        "      logps = model(img)\n",
        "  ps = torch.exp(logps)\n",
        "  m = ps.argmax(1)\n",
        "  p+=str(chr(m.item()+65))\n",
        "  if nwords[count] != nwords[count-1]:\n",
        "    p+=\" \"\n",
        "  if nlines[count] != nlines[count-1]:\n",
        "    p+=\"\\n\"\n",
        "  count+=1\n",
        "print(p)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "S H E L L O A B C D D S C E \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dw1NZbJZe-nm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "## save model\n",
        "\n",
        "torch.save(model.state_dict(), 'digifymodel.pth')"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}