script.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Problem Definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "My client runs a drop shipping website and sells other supplier products on his website. one supplier sent him a [PDF file](files/products-data.pdf) that contains all of his products data and a folder that contains [products images](hq_unordered) in a full resolution, the PDF contains each product thumbnail image, product name, and product price. The problem is the high-quality images are not in the same order as it appears on the PDF file, so there has to be a solution to sort the images the exact sorting as it appears on the PDF to sync the images perfectly with each relevant product info.\n",
    "\n",
    "<img src=\"files/prods-info.png\" width=\"800\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first thing to do is extracting the thumbnail images from the PDF file. The easiest way is to save the PDF file as html page, and all the images will be saved in one folder. The problem of this method is for some reason it saves two versions of each image, one version is the same resolution as it appears in the PDF file and the other version is a compressed image with a very low resolution, but the good thing about this method is that it saves the images in the same ordering as on the PDF file.\n",
    "![](files/imgs-html-output.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import cv2\n",
    "from matplotlib import pylab as plt\n",
    "import re\n",
    "import shutil\n",
    "from tqdm import tqdm\n",
    "%matplotlib notebook\n",
    "%config Completer.use_jedi = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first step is cleaning the duplicated images, every two consecutive images on the thumbnail directory should be compared and the compressed version should be ignored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "THUMP_IMGS_PATH = 'thumpnail_imgs'\n",
    "FULL_RES_UNORDERED_IMGS_PATH = 'hq_unordered'\n",
    "thump_imgs_names = os.listdir(THUMP_IMGS_PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['image094.jpg', 'image095.jpg', 'image096.jpg', 'image097.jpg', 'image098.jpg', 'image099.jpg', 'image100.jpg', 'image1000.jpg', 'image1001.jpg', 'image1002.jpg']\n"
     ]
    }
   ],
   "source": [
    "print(thump_imgs_names[90:100])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After listing images names, it shows a name ordering issue, ```image1000.jpg``` comes after ```image100.jpg``` and this ordering should be edited to correctly compare every two consecutive images. So, images names should be renamed and image sequence number should be represented in 4 digits instead of 3 to be right sorted.\n",
    "To rename the images regular expression is used to add extra 0 when the image sequence number consists of 3 digits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rename_imgs():\n",
    "    thump_imgs_names_renamed = []\n",
    "    for img_name in thump_imgs_names:\n",
    "        img_name = re.sub(r'(image)([\\d]{3}[.])', r'image0\\2', img_name)\n",
    "        thump_imgs_names_renamed.append(img_name)\n",
    "    return thump_imgs_names_renamed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['image0094.jpg', 'image0095.jpg', 'image0096.jpg', 'image0097.jpg', 'image0098.jpg', 'image0099.jpg', 'image0100.jpg', 'image1000.jpg', 'image1001.jpg', 'image1002.jpg']\n"
     ]
    }
   ],
   "source": [
    "renamed_imgs_names = rename_imgs()\n",
    "print(imgs_names[90:100])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Images names are correctly edited. the images are copied to a new directory with the correct names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "RENAMED_THUMP_IMGS_PATH = 'renamed_thumpnail_imgs'\n",
    "for i in range(len(thump_imgs_names)):\n",
    "    src_img_path = os.path.join(THUMP_IMGS_PATH, thump_imgs_names[i])\n",
    "    target_img_path = os.path.join(RENAMED_THUMP_IMGS_PATH, renamed_imgs_names[i])\n",
    "    shutil.copy(src_img_path, target_img_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now it is the time to clean the duplicated images. ```image_diff``` function is implemented to compare between two images by subtraction, the parameter ```HW``` is for passing the height and width as a tuple to resize the images before subtraction, if it is not set the larger resolution image is resized to the resolution of the lower resolution image.\n",
    "```clean_duplicated_imgs``` function is defined to pass each two consecutive images and explicitly pass the height and width to a small resolution (90, 90) to speed up the process and returns the list of the calculated results of the subtraction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "renamed_imgs_names = os.listdir(RENAMED_THUMP_IMGS_PATH)\n",
    "\n",
    "def image_diff(img1, img2, HW=None):\n",
    "    if HW == None:\n",
    "        H1, W1, _ = img1.shape\n",
    "        H2, W2, _ = img2.shape\n",
    "        if H1 > H2:\n",
    "            WH = (W2, H2)\n",
    "            img1 = cv2.resize(img1, WH)\n",
    "        else:\n",
    "            WH = (W1, H1)\n",
    "            img2 = cv2.resize(img2, WH)\n",
    "    else:\n",
    "        WH = (HW[1], HW[0])\n",
    "        img1 = cv2.resize(img1, WH)\n",
    "        img2 = cv2.resize(img2, WH)\n",
    "\n",
    "    img1 = cv2.GaussianBlur(img1, (11, 11), 0)\n",
    "    img2 = cv2.GaussianBlur(img2, (11, 11), 0)\n",
    "\n",
    "    img1 = img1.astype(np.int16)\n",
    "    img2 = img2.astype(np.int16)\n",
    "\n",
    "    diff = np.subtract(img1, img2)\n",
    "    abs_diff = np.abs(diff)\n",
    "    sum_abs_diff = np.sum(abs_diff)\n",
    "\n",
    "    return sum_abs_diff / (WH[0] * WH[1])\n",
    "\n",
    "\n",
    "def clean_duplicated_imgs():\n",
    "    error_list = []\n",
    "\n",
    "    img_indx = 0\n",
    "    for i in range(int(len(thump_imgs_names) / 2)):\n",
    "        img1_name = renamed_imgs_names[img_indx]\n",
    "        img2_name = renamed_imgs_names[img_indx + 1]\n",
    "        img1 = cv2.imread(os.path.join(RENAMED_THUMP_IMGS_PATH, img1_name))\n",
    "        img2 = cv2.imread(os.path.join(RENAMED_THUMP_IMGS_PATH, img2_name))\n",
    "        error = image_diff(img1, img2, (90, 90))\n",
    "        error_list.append(error)\n",
    "        img_indx += 2\n",
    "\n",
    "    return error_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "error_list = clean_duplicated_imgs()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```error_list``` is plotted to better see the result values of the subtraction and decide whether they are reasonable values or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"960\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=plt.figaspect(0.5))\n",
    "plt.scatter(np.arange(len(error_list)),\n",
    "            error_list,\n",
    "            alpha=0.3,\n",
    "            s=25)\n",
    "plt.xlabel('image samples')\n",
    "_ = plt.ylabel('error value')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the plot it is obvious that the first miss sequencing happens after about 100 subtraction operation, from manual checking it seems that not all images are duplicated. The function should be modified to consider that not every image has a duplicate.\n",
    "![missequencing](files/missequencing.png)\n",
    "\n",
    "Reasonable error value should be less than 13 otherwise the image is considered to has no duplicate.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_heigher_res_img(img1_name, img2_name, path):\n",
    "    im1 = cv2.imread(os.path.join(path, img1_name))\n",
    "    im2 = cv2.imread(os.path.join(path, img2_name))\n",
    "\n",
    "    res1 = im1.shape[0] * im1.shape[1]\n",
    "    res2 = im2.shape[0] * im2.shape[1]\n",
    "\n",
    "    if res1 > res2:\n",
    "        return img1_name\n",
    "    else:\n",
    "        return img2_name\n",
    "\n",
    "def clean_duplicated_imgs():\n",
    "    error_thresh = 13\n",
    "    \n",
    "    single_imgs_indx = []\n",
    "    single_imgs_error = []\n",
    "    duplicate_imgs_error = []\n",
    "    duplicate_imgs_indx = []\n",
    "    \n",
    "    unique_imgs = []\n",
    "\n",
    "    img_indx = 0\n",
    "    while img_indx < len(thump_imgs_names) - 1:\n",
    "        img1_name = renamed_imgs_names[img_indx]\n",
    "        img2_name = renamed_imgs_names[img_indx + 1]\n",
    "        img1 = cv2.imread(os.path.join(RENAMED_THUMP_IMGS_PATH, img1_name))\n",
    "        img2 = cv2.imread(os.path.join(RENAMED_THUMP_IMGS_PATH, img2_name))\n",
    "        error = image_diff(img1, img2, (90, 90))\n",
    "\n",
    "        if error > error_thresh:\n",
    "            # (images are different) image has no duplicate\n",
    "            single_imgs_indx.append(img_indx)\n",
    "            single_imgs_error.append(error)\n",
    "            unique_imgs.append(img1_name)\n",
    "            img_indx += 1\n",
    "        else:\n",
    "            # identical images, keep only the higher res img\n",
    "            duplicate_imgs_indx.append(img_indx)\n",
    "            duplicate_imgs_error.append(error)\n",
    "            unique_imgs.append(get_heigher_res_img(img1_name, img2_name, RENAMED_THUMP_IMGS_PATH))\n",
    "            img_indx += 2\n",
    "\n",
    "    errors = {'single_imgs_indx': single_imgs_indx,\n",
    "             'single_imgs_error': single_imgs_error,\n",
    "             'duplicate_imgs_indx': duplicate_imgs_indx,\n",
    "             'duplicate_imgs_error': duplicate_imgs_error\n",
    "             }\n",
    "    return unique_imgs, errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "unique_imgs, errors = clean_duplicated_imgs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"960\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=plt.figaspect(0.5))\n",
    "plt.scatter(errors['duplicate_imgs_indx'],\n",
    "            errors['duplicate_imgs_error'],\n",
    "            alpha=0.3,\n",
    "            s=25,\n",
    "            c='blue')\n",
    "plt.scatter(errors['single_imgs_indx'],\n",
    "            errors['single_imgs_error'],\n",
    "            alpha=0.3,\n",
    "            s=25,\n",
    "            c='red')\n",
    "plt.legend(['image that has a duplicate', 'single image'])\n",
    "plt.xlabel('image samples')\n",
    "_ = plt.ylabel('error value')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The plot looks acceptable, and all the red dots are images that have no duplicates. Now the unique images could be copied to a new directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "CLEANED_THUMP_IMGS_PATH = 'cleaned_thumpnail_imgs'\n",
    "for img in unique_imgs:\n",
    "    src_path = os.path.join(RENAMED_THUMP_IMGS_PATH, img)\n",
    "    dst_path = os.path.join(CLEANED_THUMP_IMGS_PATH, img)\n",
    "    shutil.copy(src_path, dst_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After the only unique images are copied to the new directory ```cleaned_thumpnail_imgs``` it is time to match each thumbnail image with the respective high resolution image. After manual inspection for some images an extra white borders are found.\n",
    "\n",
    "<img src=\"files/different-object-size.jpg\" width=\"600\">\n",
    "\n",
    "For these images simple subtraction would not work because the pixels would not match perfectly. one way to deal with this problem is to crop both images in a way that fits the objects on the image perfectly without any extra borders."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def crop_object(img):\n",
    "    img_grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "    img_grey = cv2.GaussianBlur(img_grey, (7, 7), 0)\n",
    "    img_grey = cv2.threshold(img_grey, 250, 255, cv2.THRESH_BINARY_INV)[1]\n",
    "    img_grey = cv2.morphologyEx(img_grey, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_RECT, (11, 11)))\n",
    "    detected_objects = cv2.findContours(img_grey, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)[0]\n",
    "\n",
    "    min_x = 65535\n",
    "    max_x = 0\n",
    "    min_y = 65535\n",
    "    max_y = 0\n",
    "    for obj in detected_objects:\n",
    "        # crop a box contains all contours\n",
    "        x, y, w, h = cv2.boundingRect(obj)\n",
    "        if x < min_x:\n",
    "            min_x = x\n",
    "        if x + w > max_x:\n",
    "            max_x = x + w\n",
    "\n",
    "        if y < min_y:\n",
    "            min_y = y\n",
    "        if y + h > max_y:\n",
    "            max_y = y + h\n",
    "    cropped_obj = img[min_y:max_y, min_x:max_x, :]\n",
    "    return cropped_obj"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```search_for_heigher_res``` function tries to match one thumbnail image with every high resolution image and returns the name of the high resolution image that has the minimum error value. If ```crop_objects``` parameter is set to True; both images are cropped with ```crop_object``` function before subtraction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def search_for_heigher_res(img, hq_imgs_list, crop_objects=False):\n",
    "    low_res_img = cv2.imread(os.path.join(CLEANED_THUMP_IMGS_PATH, img))\n",
    "    if crop_objects:\n",
    "        low_res_img = crop_object(low_res_img)\n",
    "    min_error = float('inf')\n",
    "    for hq_img_name in hq_imgs_list:\n",
    "        #hq_img = cv2.imread(os.path.join(FULL_RES_UNORDERED_IMGS_PATH, hq_img_name))\n",
    "        im_path = os.path.join(FULL_RES_UNORDERED_IMGS_PATH, hq_img_name)\n",
    "        hq_img = cv2.imdecode(np.fromfile(im_path, np.uint8), cv2.IMREAD_UNCHANGED)\n",
    "        if crop_objects:\n",
    "            hq_img = crop_object(hq_img)\n",
    "        diff_error = image_diff(low_res_img, hq_img, HW=(150, 150))\n",
    "        if diff_error < min_error:\n",
    "            min_error = diff_error\n",
    "            matched_img = hq_img_name\n",
    "        \n",
    "    return matched_img, min_error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This part uses the previous functions to search and match each thumbnail image with a high resolution image. a threshold with a value 15 is defined, if the thumbnail image has a minimum error larger than that threshold; the same process of matching would done but with cropping, if the minimum error is still larger than the threshold; the thumbnail image is considered missing and has no match for a high resolution image. During this process I kept track of all matched thumbnail images, number of matched thumbnail images after cropping, and matching error values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████| 1134/1134 [2:45:31<00:00,  8.76s/it]\n"
     ]
    }
   ],
   "source": [
    "CLEANED_THUMP_IMGS_PATH = 'cleaned_thumpnail_imgs'\n",
    "cleaned_thump_imgs_names = os.listdir(CLEANED_THUMP_IMGS_PATH)\n",
    "full_res_imgs_names = os.listdir(FULL_RES_UNORDERED_IMGS_PATH)\n",
    "OUTPUT_PATH = 'output_imgs'\n",
    "matched_imgs_after_crop = 0\n",
    "error_list = []\n",
    "matched_imgs = []\n",
    "matching_thresh = 15\n",
    "\n",
    "for img in tqdm(cleaned_thump_imgs_names):\n",
    "    heigh_res_img, error = search_for_heigher_res(img, full_res_imgs_names)\n",
    "    crop_obj = False\n",
    "    \n",
    "    if error > matching_thresh:\n",
    "        # crop the object and search for heigher res match image\n",
    "        crop_obj = True\n",
    "        heigh_res_img, error = search_for_heigher_res(img, full_res_imgs_names, crop_objects=crop_obj)\n",
    "\n",
    "    if error < matching_thresh:\n",
    "        shutil.copy(os.path.join(FULL_RES_UNORDERED_IMGS_PATH, heigh_res_img), os.path.join(OUTPUT_PATH, img))\n",
    "        matched_imgs.append(heigh_res_img)\n",
    "        if crop_obj:\n",
    "            matched_imgs_after_crop += 1\n",
    "        \n",
    "    else:\n",
    "        shutil.copy('files/missing.jpg', os.path.join(OUTPUT_PATH, img))\n",
    "\n",
    "    error_list.append(error)\n",
    "\n",
    "for img in full_res_imgs_names:\n",
    "    if img not in matched_imgs:\n",
    "        shutil.copy(os.path.join(FULL_RES_UNORDERED_IMGS_PATH, img), os.path.join('remaining_unmatched', img))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After matching all thumbnail images I printed here some statistics to get an idea of how well the code works and find out how many thumbnail images are not matched with a high resolution image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# matched images: 910\n",
      "# matched images after cropping: 15\n",
      "# unmatched images: 224\n",
      "-----------------------\n",
      "matching rate: %80.25\n"
     ]
    }
   ],
   "source": [
    "not_matched_imgs_zip = [(idx, error) for idx, error in enumerate(error_list) if error > matching_thresh]\n",
    "not_matched_imgs_idx, not_matched_imgs_error = zip(*not_matched_imgs_zip)\n",
    "\n",
    "matched_imgs_zip = [(idx, error) for idx, error in enumerate(error_list) if error < matching_thresh]\n",
    "matched_imgs_idx, matched_imgs_error = zip(*matched_imgs_zip)\n",
    "\n",
    "num_matched_imgs = len(matched_imgs_idx)\n",
    "num_umatched_imgs = len(not_matched_imgs_idx)\n",
    "\n",
    "print('# matched images: ' + str(num_matched_imgs))\n",
    "print('# matched images after cropping: ' + str(matched_imgs_after_crop))\n",
    "print('# unmatched images: ' + str(num_umatched_imgs))\n",
    "print('-----------------------')\n",
    "print('matching rate: %' + \"{:.2f}\".format((num_matched_imgs / (num_matched_imgs + num_umatched_imgs)) * 100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As it shows there are 224 thumbnail images that did not match with a high resolution image, I need to plot the error values to get an idea of the missing images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"960\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=plt.figaspect(0.5))\n",
    "plt.scatter(matched_imgs_idx,\n",
    "            matched_imgs_error,\n",
    "            alpha=0.2,\n",
    "            s=25, c='blue')\n",
    "plt.scatter(not_matched_imgs_idx,\n",
    "            not_matched_imgs_error,\n",
    "            alpha=0.2,\n",
    "            s=25, c='red')\n",
    "plt.legend(['image is matched', 'image is not matched'])\n",
    "plt.xlabel('image samples')\n",
    "plt.ylabel('error value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the plot and after manual inspection I found out that most of these images are actually missing and the supplier folder does not contain a high resolution image for all thumbnail images on the PDF file. Finally, I delivered the sorted images to my client and a placeholder image was placed for all the missing images to preserve image sequencing as on the PDF file and to define the missing images to my client so he could get back to the supplier and ask him for the missing images."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}