captchas-eda.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.010346,
     "end_time": "2020-08-26T00:52:30.039121",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.028775",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# CAPTCHA EDA\n",
    "## By Sergei Issaev\n",
    "### Introduction\n",
    "This notebook is part of the preprocessing pipeline which takes in CAPTCHA images and outputs the solution. This is the first notebook in the four part series, which can be used as an EDA, and wherein I define step-by-step the preprocessing performed in order to invert, segment and save each of the 10 alphanumerics. For a more complete description, please see my article published at: https://medium.com/@sergei740."
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.007403,
     "end_time": "2020-08-26T00:52:30.055308",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.047905",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a",
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:30.079258Z",
     "iopub.status.busy": "2020-08-26T00:52:30.078409Z",
     "iopub.status.idle": "2020-08-26T00:52:30.420016Z",
     "shell.execute_reply": "2020-08-26T00:52:30.419156Z"
    },
    "papermill": {
     "duration": 0.356892,
     "end_time": "2020-08-26T00:52:30.420169",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.063277",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import cv2\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import random"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.007382,
     "end_time": "2020-08-26T00:52:30.435470",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.428088",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:30.458707Z",
     "iopub.status.busy": "2020-08-26T00:52:30.457793Z",
     "iopub.status.idle": "2020-08-26T00:52:30.581617Z",
     "shell.execute_reply": "2020-08-26T00:52:30.580813Z"
    },
    "papermill": {
     "duration": 0.138188,
     "end_time": "2020-08-26T00:52:30.581762",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.443574",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8503\n",
      "Fr3ExC7G4y.jpg\n"
     ]
    }
   ],
   "source": [
    "tot_size = len(os.listdir('/kaggle/input/captcha-images/'))\n",
    "num = random.randint(0, tot_size)\n",
    "print(num)\n",
    "alli = list(os.listdir('/kaggle/input/captcha-images/'))\n",
    "file = alli[num]\n",
    "print(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:30.606327Z",
     "iopub.status.busy": "2020-08-26T00:52:30.605315Z",
     "iopub.status.idle": "2020-08-26T00:52:30.610130Z",
     "shell.execute_reply": "2020-08-26T00:52:30.609516Z"
    },
    "papermill": {
     "duration": 0.020251,
     "end_time": "2020-08-26T00:52:30.610256",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.590005",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Fr3ExC7G4y'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solution = file.split('.')[0]\n",
    "solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:30.632697Z",
     "iopub.status.busy": "2020-08-26T00:52:30.631786Z",
     "iopub.status.idle": "2020-08-26T00:52:30.656109Z",
     "shell.execute_reply": "2020-08-26T00:52:30.655469Z"
    },
    "papermill": {
     "duration": 0.037794,
     "end_time": "2020-08-26T00:52:30.656253",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.618459",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "hi = cv2.imread('/kaggle/input/captcha-images/' + file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:30.679733Z",
     "iopub.status.busy": "2020-08-26T00:52:30.678832Z",
     "iopub.status.idle": "2020-08-26T00:52:30.805847Z",
     "shell.execute_reply": "2020-08-26T00:52:30.805173Z"
    },
    "papermill": {
     "duration": 0.141203,
     "end_time": "2020-08-26T00:52:30.805994",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.664791",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(hi, cmap=\"gray\")\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.0086,
     "end_time": "2020-08-26T00:52:30.823252",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.814652",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:30.849916Z",
     "iopub.status.busy": "2020-08-26T00:52:30.849126Z",
     "iopub.status.idle": "2020-08-26T00:52:30.860517Z",
     "shell.execute_reply": "2020-08-26T00:52:30.859845Z"
    },
    "papermill": {
     "duration": 0.028712,
     "end_time": "2020-08-26T00:52:30.860648",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.831936",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# convert to RGB\n",
    "image = cv2.cvtColor(hi, cv2.COLOR_BGR2RGB)\n",
    "# convert to grayscale\n",
    "gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:30.888433Z",
     "iopub.status.busy": "2020-08-26T00:52:30.887634Z",
     "iopub.status.idle": "2020-08-26T00:52:31.025455Z",
     "shell.execute_reply": "2020-08-26T00:52:31.024637Z"
    },
    "papermill": {
     "duration": 0.156001,
     "end_time": "2020-08-26T00:52:31.025601",
     "exception": false,
     "start_time": "2020-08-26T00:52:30.869600",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a binary thresholded image\n",
    "_, binary = cv2.threshold(gray, 225, 255, cv2.THRESH_BINARY_INV)\n",
    "# show it\n",
    "plt.imshow(binary, cmap=\"gray\")\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.054914Z",
     "iopub.status.busy": "2020-08-26T00:52:31.054091Z",
     "iopub.status.idle": "2020-08-26T00:52:31.066440Z",
     "shell.execute_reply": "2020-08-26T00:52:31.065738Z"
    },
    "papermill": {
     "duration": 0.031592,
     "end_time": "2020-08-26T00:52:31.066579",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.034987",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# find the contours from the thresholded image\n",
    "contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n",
    "# draw all contours\n",
    "image = cv2.drawContours(image, contours, -1, (0, 255, 0), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.097309Z",
     "iopub.status.busy": "2020-08-26T00:52:31.096453Z",
     "iopub.status.idle": "2020-08-26T00:52:31.168202Z",
     "shell.execute_reply": "2020-08-26T00:52:31.167438Z"
    },
    "papermill": {
     "duration": 0.092548,
     "end_time": "2020-08-26T00:52:31.168341",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.075793",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show the image with the drawn contours\n",
    "plt.imshow(image)\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.00939,
     "end_time": "2020-08-26T00:52:31.187488",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.178098",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Sort Contours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.225129Z",
     "iopub.status.busy": "2020-08-26T00:52:31.224040Z",
     "iopub.status.idle": "2020-08-26T00:52:31.227540Z",
     "shell.execute_reply": "2020-08-26T00:52:31.226769Z"
    },
    "papermill": {
     "duration": 0.030646,
     "end_time": "2020-08-26T00:52:31.227670",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.197024",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "x = {}\n",
    "for m in range(len(contours)):\n",
    "    mini = 1000\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][0]\n",
    "        if first < mini:\n",
    "            mini = first\n",
    "    mini1 = mini\n",
    "    #print(mini1)\n",
    "    \n",
    "    mini = 1000\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][1]\n",
    "        if first < mini:\n",
    "            mini = first\n",
    "    mini2 = mini\n",
    "    #print(mini2)\n",
    "    \n",
    "    maxi = 0\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][1]\n",
    "        if first > maxi:\n",
    "            maxi = first\n",
    "    maxi2 = maxi\n",
    "    #print(maxi2)\n",
    "    \n",
    "    maxi = 0\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][0]\n",
    "        if first > maxi:\n",
    "            maxi = first\n",
    "    maxi1 = maxi\n",
    "    #print(maxi1)\n",
    "    x[m] = maxi2 - mini2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.254125Z",
     "iopub.status.busy": "2020-08-26T00:52:31.253017Z",
     "iopub.status.idle": "2020-08-26T00:52:31.256133Z",
     "shell.execute_reply": "2020-08-26T00:52:31.256691Z"
    },
    "papermill": {
     "duration": 0.019363,
     "end_time": "2020-08-26T00:52:31.256859",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.237496",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "biggie = sorted(x, key=x.get)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.291726Z",
     "iopub.status.busy": "2020-08-26T00:52:31.285220Z",
     "iopub.status.idle": "2020-08-26T00:52:31.295433Z",
     "shell.execute_reply": "2020-08-26T00:52:31.294650Z"
    },
    "papermill": {
     "duration": 0.028717,
     "end_time": "2020-08-26T00:52:31.295568",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.266851",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "s = {}\n",
    "def plotting(num):\n",
    "    m = biggie[num]\n",
    "    mini = 1000\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][0]\n",
    "        if first < mini:\n",
    "            mini = first\n",
    "    mini1 = mini\n",
    "    #print(mini1)\n",
    "\n",
    "    mini = 1000\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][1]\n",
    "        if first < mini:\n",
    "            mini = first\n",
    "    mini2 = mini\n",
    "   # print(mini2)\n",
    "\n",
    "    maxi = 0\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][1]\n",
    "        if first > maxi:\n",
    "            maxi = first\n",
    "    maxi2 = maxi\n",
    "    #print(maxi2)\n",
    "\n",
    "    maxi = 0\n",
    "    for k in range(len(contours[m])):\n",
    "        first = contours[m][k][0][0]\n",
    "        if first > maxi:\n",
    "            maxi = first\n",
    "    maxi1 = maxi\n",
    "    #print(maxi1)\n",
    "    ret = [mini2, maxi2, mini1, maxi1]\n",
    "    s[num] = mini1\n",
    "    return ret"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.350621Z",
     "iopub.status.busy": "2020-08-26T00:52:31.334611Z",
     "iopub.status.idle": "2020-08-26T00:52:31.701128Z",
     "shell.execute_reply": "2020-08-26T00:52:31.700396Z"
    },
    "papermill": {
     "duration": 0.395658,
     "end_time": "2020-08-26T00:52:31.701265",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.305607",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 5)\n",
    "wow = plotting(-1)\n",
    "axs[0, 0].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[0,0].axis('off')\n",
    "wow = plotting(-2)\n",
    "axs[0, 1].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[0,1].axis('off')\n",
    "wow = plotting(-3)\n",
    "axs[0,2].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[0,2].axis('off')\n",
    "wow = plotting(-4)\n",
    "axs[0,3].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[0,3].axis('off')\n",
    "wow = plotting(-5)\n",
    "axs[0,4].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[0,4].axis('off')\n",
    "wow = plotting(-6)\n",
    "axs[1,0].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[1,0].axis('off')\n",
    "wow = plotting(-7)\n",
    "axs[1,1].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[1,1].axis('off')\n",
    "wow = plotting(-8)\n",
    "axs[1,2].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[1,2].axis('off')\n",
    "wow = plotting(-9)\n",
    "axs[1,3].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[1,3].axis('off')\n",
    "wow = plotting(-10)\n",
    "axs[1,4].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "axs[1,4].axis('off')\n",
    "wow = plotting(-11)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.00976,
     "end_time": "2020-08-26T00:52:31.721565",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.711805",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Sort left to right"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.748272Z",
     "iopub.status.busy": "2020-08-26T00:52:31.747424Z",
     "iopub.status.idle": "2020-08-26T00:52:31.750220Z",
     "shell.execute_reply": "2020-08-26T00:52:31.750785Z"
    },
    "papermill": {
     "duration": 0.019445,
     "end_time": "2020-08-26T00:52:31.750995",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.731550",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "siggie = sorted(s, key=s.get)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.793717Z",
     "iopub.status.busy": "2020-08-26T00:52:31.792599Z",
     "iopub.status.idle": "2020-08-26T00:52:31.795969Z",
     "shell.execute_reply": "2020-08-26T00:52:31.796533Z"
    },
    "papermill": {
     "duration": 0.035116,
     "end_time": "2020-08-26T00:52:31.796707",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.761591",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def checkforerror(wow):\n",
    "    white = cv2.countNonZero(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2])\n",
    "    total = (binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2]).shape[0] * (binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2]).shape[1]\n",
    "    div = white/total\n",
    "    if div > 0.63: \n",
    "        if (wow[1] - wow[0]) - (wow[3] - wow[2]) > -5:\n",
    "            return True\n",
    "    elif div < 0.29:\n",
    "        return True\n",
    "    else: return False\n",
    "def checkforerrorout(wow):\n",
    "    white = cv2.countNonZero(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2])\n",
    "    total = (binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2]).shape[0] * (binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2]).shape[1]\n",
    "    div = white/total\n",
    "    return div\n",
    "def checkfordoubles(wow):\n",
    "    if (wow[1] - wow[0]) - (wow[3] - wow[2]) < -4: \n",
    "        if checkforerrorout(wow) < 0.56: return True\n",
    "    elif (wow[1] - wow[0]) - (wow[3] - wow[2]) < 1:\n",
    "        if checkforerrorout(wow) < 0.40: return True\n",
    "    else: return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:31.828339Z",
     "iopub.status.busy": "2020-08-26T00:52:31.826687Z",
     "iopub.status.idle": "2020-08-26T00:52:32.026991Z",
     "shell.execute_reply": "2020-08-26T00:52:32.027537Z"
    },
    "papermill": {
     "duration": 0.220657,
     "end_time": "2020-08-26T00:52:32.027719",
     "exception": false,
     "start_time": "2020-08-26T00:52:31.807062",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test 1 False\n",
      "False\n",
      "0.4015151515151515\n",
      "False\n",
      "test 2 False\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAN0AAAD4CAYAAABopeOfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAOQElEQVR4nO3dbagc53nG8f9V2fpQxcEORoosKY0bhEEJ5cQI1UFtkNvayMJUSUmLRGnU1CAnVJBAC1FTSEIhYChOmlDj9CQRtiGRbWhERKNYEibUDsSOXpAsKZLiE6NUx0dIOKayjQPmWHc/7CNnu9qV9uzsuXd29/rBsjszz+w8s0eX5mVn7lVEYGZ5fmfQHTAbNw6dWTKHziyZQ2eWzKEzS3bdoDvQjiSfUrWhFxFqN95bOrNklUInab2k05KmJG1vM12SvlGmvyDp9irLMxsJEdHTA1gA/BL4fWAhcBRY1dJmA/AjQMAdwPNdvnf44cewPzr9+66ypVsDTEXESxHxFvA4sLGlzUbgsWh4DrhR0tIKyzQbelVCtww42zQ8XcbNtQ0AkrZKOijpYIU+mdVelbOX7c7MRA9tGiMjJoFJ8NlLG21VtnTTwIqm4eXATA9tzMZKldAdAFZKulXSQmATsLulzW7gk+Us5h3AxYg4V2GZZkOv593LiJiVtA3YS+NM5o6IOCHp02X6N4E9NM5gTgFvAp+q3mWz4aY63k/nYzobBb4ixawmHDqzZA6dWTKHziyZQ2eWzKEzS+bQmSVz6MySOXRmyWpZI6Xu6ngVz1xJbS+WqI1uPuO6r0Mn3tKZJXPozJI5dGbJHDqzZA6dWTKHzixZz6GTtELSjyWdlHRC0mfbtFkn6aKkI+XxxWrdNRt+Vb6nmwX+ISIOS7oBOCRpf0T8vKXdsxFxb4XlmI2Unrd0EXEuIg6X168DJ+lQ09LMfqsvV6RIej/wYeD5NpM/IukojdJ7/xgRJzq8x1Zgaz/602oUriDpt1H4TAa1DlWvhKlcmEjSu4D/Br4SEd9vmfZu4FJEvCFpA/D1iFjZxXv29dMchX9gVh/dhq5TYaJKoZN0PfBfwN6I+GoX7c8AqyPilWu0c+istqqGrsrZSwHfAU52Cpyk95Z2SFpTlvfrXpdpNgqqHNOtBf4GOCbpSBn3BeB98E6x2U8An5E0C/wG2BTe7NiYG4tis3VcRxteA9u9NLPeOHRmyRw6s2QOnVmysaiRMocD33nuiZm3dGbpHDqzZA6dWTKHziyZQ2eWzKEzS+bQmSVz6MySOXRmycbiipRx0u9fshmnq3SyfgXIWzqzZJVCJ+mMpGOlkOzBNtMl6RuSpiS9IOn2KsszGwX92L288yqFhu4BVpbHHwIPl2ezsTXfu5cbgcei4TngRklL53mZZrVWNXQB7JN0qBSLbbUMONs0PE2HKtCStko62G431WyUVN29XBsRM5IWA/slnYqIZ5qmtzsd1PZ0WERMApPQ/8JEZnVSaUsXETPl+QKwC1jT0mQaWNE0vJxGeXWzsVWl2Oyi8ms9SFoE3A0cb2m2G/hkOYt5B3AxIs713FuzEVBl93IJsKt8oXgd8L2IeErSp+GdYrN7gA3AFPAm8Klq3bVsLnXRf2NRbLZbdfws5irrqopW/uyu5GKzZjXh0Jklc+jMkjl0ZskcOrNkDp1ZMofOLJlDZ5bMoTNL5tCZJXPozJI5dGbJHDqzZA6dWTKHzixZlTvHbyv1Li8/XpP0uZY26yRdbGrzxepdNhtuPd85HhGngQkASQuAl2nUSWn1bETc2+tyzEZNv3Yv/xT4ZUT8qk/vZzay+hW6TcDODtM+IumopB9J+mCnN3DdS5svkrp6pPWnam0LSQtplNX7YEScb5n2buBSRLwhaQPw9YhY2cV7ukZKj1wj5UoD/EzmrUbKPcDh1sCVhb4WEW+U13uA6yXd3Idlmg2tfoRuMx12LSW9V+W/GUlryvJ+3Ydlmg2tSmXVJf0ucBdwf9O45rqXnwA+I2kW+A2wKeq8H2KWwHUvm9Txs5grH9NdaRSP6cxsDhw6s2QOnVkyh84sWT9+c3xk+BdqrjRO65rFWzqzZA6dWTKHziyZQ2eWzKEzS+bQmSVz6MySOXRmyRw6s2S+ImXE+AqS+vOWzizZNUMnaYekC5KON417j6T9kl4szzd1mHe9pNOSpiRt72fHzYZVN1u6R4D1LeO2A0+Xyl5Pl+H/pxSgfYhG4aJVwGZJqyr11mwEXDN0EfEM8GrL6I3Ao+X1o8DH2sy6BpiKiJci4i3g8TKf2Vjr9ZhuSUScAyjPi9u0WQacbRqeLuPacrFZGxfzefay3c1pHU+tRcQkMAmDK0xklqHXLd15SUsByvOFNm2mgRVNw8tpVII2G2u9hm43sKW83gL8oE2bA8BKSbeW0uubynxmY62brwx2Aj8FbpM0Lek+4AHgLkkv0ig2+0Bpe4ukPQARMQtsA/YCJ4EnI+LE/KyG2fBwsdke1PEzs85cbNZszDl0ZskcOrNkDp1ZMofOLJlDZ5bMoTNL5tCZJXPozJK5RsqYGoVfKBrUlSZVeUtnlsyhM0vm0Jklc+jMkjl0ZskcOrNkvRab/VdJpyS9IGmXpBs7zHtG0jFJR1zly6yh12Kz+4EPRcQfAL8A/ukq898ZERMRsbq3LpqNlp6KzUbEvlIDBeA5GpW+zKwL/bgi5e+AJzpMC2BfqXnyH6W2ZVuStgJb+9CfsdbvqzQGdeXKsF5t0o1KoZP0z8As8N0OTdZGxIykxcB+SafKlvMKLjZr46Lns5eStgD3An8dHf6bi4iZ8nwB2EXj9w3MxlpPoZO0Hvg88OcR8WaHNosk3XD5NXA3cLxdW7Nx0mux2X8HbqCxy3hE0jdL23eKzQJLgJ9IOgr8DPhhRDw1L2thNkRcbLYHdfzMLhtgYdW+vt8onEhxsVmzmnDozJI5dGbJHDqzZK6RYn0xCic+snhLZ5bMoTNL5tCZJXPozJI5dGbJHDqzZA6dWTKHziyZQ2eWzFekNKnzLTs2Onqte/llSS+XG1iPSNrQYd71kk5LmpK0vZ8dNxtWvda9BPhaqWc5ERF7WidKWgA8BNwDrAI2S1pVpbNmo6CnupddWgNMRcRLEfEW8DiwsYf3MRspVU6kbCtl1XdIuqnN9GXA2abh6TLObKz1GrqHgQ8AE8A54ME2bdrd69HxTIWkrZIO+jcPbNT1FLqIOB8Rb0fEJeBbtK9nOQ2saBpeDsxc5T0nI2K1f/PARl2vdS+XNg1+nPb1LA8AKyXdKmkhsAnY3cvyzEbJNb+nK3Uv1wE3S5oGvgSskzRBY3fxDHB/aXsL8O2I2BARs5K2AXuBBcCOiDgxL2thNkRc97JJHT+LuXLZhPpw3UuzmnDozJI5dGbJHDqzZA6dWTKHziyZQ2eWzKEzS+bQmSUbi3INo3CliY0Ob+nMkjl0ZskcOrNkDp1ZMofOLJlDZ5asmzvHdwD3Ahci4kNl3BPAbaXJjcD/RsREm3nPAK8DbwOzrn9i1sWd45I+CrwBPHY5dC3THwQuRsS/tJl2BlgdEa/MqVN9vnN8nL6n853j9dHpzvFrbuki4hlJ7283TY2/8F8Bf1Klc2bjpOox3R8D5yPixQ7TA9gn6ZCkrVd7I9e9tHFR9TKwzcDOq0xfGxEzkhYD+yWdKmXarxARk8AkDK4wkVmGnrd0kq4D/gJ4olObiJgpzxeAXbQvSms2VqrsXv4ZcCoipttNlLRI0g2XXwN3074ordlY6eb36XYCPwVukzQt6b4yaRMtu5aSbpF0+WezlgA/kXQU+Bnww4h4qn9dNxtOY1Fsto7rOF/8lUF9uNisWU04dGbJHDqzZA6dWTKHziyZQ2eWzKEzS+bQmSVz6MySOXRmyRw6s2QOnVkyh84smUNnlsyhM0vm0Jkl6+bO8RWSfizppKQTkj5bxr9H0n5JL5bnmzrMv17SaUlTkrb3ewXMhk03xWaXAksj4nCpeXII+Bjwt8CrEfFACdNNEfH5lnkXAL8A7gKmgQPA5oj4+TWW6TvHe+Q7x+uj5zvHI+JcRBwur18HTgLLgI3Ao6XZozSC2GoNMBURL0XEW8DjZT6zsTWnY7pS6fnDwPPAkog4B41gAovbzLIMONs0PF3GtXtvF5u1sdB1sVlJ7wL+E/hcRLzW5W5Mu0Zt9/VcbNbGRVdbOknX0wjcdyPi+2X0+XK8d/m470KbWaeBFU3Dy4GZ3rtrNvy6OXsp4DvAyYj4atOk3cCW8noL8IM2sx8AVkq6VdJCGrUyd1frstlw6+bs5R8BzwLHgEtl9BdoHNc9CbwP+B/gLyPiVUm3AN+OiA1l/g3AvwELgB0R8ZVrdspnL3vms5f10ens5VgUmzUbBBebNasJh84smUNnlsyhM0vm0Jklc+jMkjl0ZskcOrNkDp1Zsq7vMkj2CvCrlnE3l/HDzOtQH/O9Hr/XaUItLwNrR9LBiFg96H5U4XWoj0Guh3cvzZI5dGbJhil0k4PuQB94HepjYOsxNMd0ZqNimLZ0ZiPBoTNLVvvQjUqFaElnJB2TdGRYygxK2iHpgqTjTeO6quxdJx3W48uSXi5/jyOlrEiKWoeuVIh+CLgHWAVslrRqsL2q5M6ImBii77keAda3jNsOPB0RK4Gny3DdPcKV6wHwtfL3mIiIPVmdqXXocIXogYqIZ4BXW0Z3U9m7Vjqsx8DUPXRdV4geAgHsk3RI0tZBd6aCbip7D4ttkl4ou59pu8l1D13XFaKHwNqIuJ3GrvLfS/rooDs05h4GPgBMAOeAB7MWXPfQjUyF6IiYKc8XgF00dp2HUTeVvWsvIs5HxNsRcQn4Fol/j7qHbiQqREtaVH5mDEmLgLuB41efq7a6qexde5f/4yg+TuLfo6639gAQEbOStgF7+W2F6BMD7lYvlgC7SvXl64DvRcRTg+3StUnaCawDbpY0DXwJeAB4UtJ9lMreg+thdzqsxzpJEzQOV84A96f1x5eBmeWq++6l2chx6MySOXRmyRw6s2QOnVkyh84smUNnluz/AA5SkwKIiYgUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wow = plotting(siggie[0])\n",
    "plt.imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "print('test 1', checkforerror(wow))\n",
    "print((wow[1] - wow[0]) - (wow[3] - wow[2]) < -4)\n",
    "print(checkforerrorout(wow))\n",
    "\n",
    "print((wow[1] - wow[0]) - (wow[3] - wow[2]) < 1)\n",
    "print('test 2', checkfordoubles(wow))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:32.099347Z",
     "iopub.status.busy": "2020-08-26T00:52:32.079232Z",
     "iopub.status.idle": "2020-08-26T00:52:32.547278Z",
     "shell.execute_reply": "2020-08-26T00:52:32.546461Z"
    },
    "papermill": {
     "duration": 0.508941,
     "end_time": "2020-08-26T00:52:32.547414",
     "exception": false,
     "start_time": "2020-08-26T00:52:32.038473",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a =  0 desired =  10\n",
      "using position 0 0\n",
      "trying to plot  0 checking for errors...\n",
      "% =  0.4015151515151515\n",
      "No errors found!\n",
      "DONE PLOTTING - im 0\n",
      "a =  1 desired =  10\n",
      "using position 0 1\n",
      "trying to plot  1 checking for errors...\n",
      "% =  0.7875\n",
      "Error 1 at 1\n",
      "im bumped to 2\n",
      "trying to plot  2 checking for errors...\n",
      "% =  0.4243421052631579\n",
      "No errors in bumped image\n",
      "a =  2 desired =  10\n",
      "using position 0 2\n",
      "trying to plot  3 checking for errors...\n",
      "% =  0.5185185185185185\n",
      "No errors found!\n",
      "DONE PLOTTING - im 3\n",
      "a =  3 desired =  10\n",
      "using position 0 3\n",
      "trying to plot  4 checking for errors...\n",
      "% =  0.6125\n",
      "No errors found!\n",
      "DONE PLOTTING - im 4\n",
      "a =  4 desired =  10\n",
      "using position 0 4\n",
      "trying to plot  5 checking for errors...\n",
      "% =  0.8888888888888888\n",
      "Error 1 at 4\n",
      "im bumped to 6\n",
      "trying to plot  6 checking for errors...\n",
      "% =  0.4666666666666667\n",
      "No errors in bumped image\n",
      "a =  5 desired =  10\n",
      "using position 1 0\n",
      "trying to plot  7 checking for errors...\n",
      "% =  0.4381818181818182\n",
      "No errors found!\n",
      "DONE PLOTTING - im 7\n",
      "a =  6 desired =  10\n",
      "using position 1 1\n",
      "trying to plot  8 checking for errors...\n",
      "% =  0.40153452685422\n",
      "No errors found!\n",
      "DONE PLOTTING - im 8\n",
      "a =  7 desired =  10\n",
      "using position 1 2\n",
      "trying to plot  9 checking for errors...\n",
      "% =  0.45168067226890757\n",
      "Error 2 at 7\n",
      "a =  8 desired =  10\n",
      "using position 1 3\n",
      "trying to plot  9 checking for errors...\n",
      "% =  0.45168067226890757\n",
      "Error 2 at 8\n",
      "a =  9 desired =  10\n",
      "using position 1 4\n",
      "trying to plot  10 checking for errors...\n",
      "% =  0.4323671497584541\n",
      "No errors found!\n",
      "DONE PLOTTING - im 10\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos = 0\n",
    "a = 0\n",
    "im = 0\n",
    "desired = 10\n",
    "fig, axs = plt.subplots(2, 5)\n",
    "first = False\n",
    "while a < desired:\n",
    "    print('a = ', a, 'desired = ', desired)\n",
    "    \n",
    "    n1 = pos // 5\n",
    "    n2 = pos % 5\n",
    "    print('using position', n1, n2)\n",
    "    wow = plotting(siggie[im])\n",
    "    print('trying to plot ', im, 'checking for errors...')\n",
    "    err = checkforerror(wow)\n",
    "    errs = checkfordoubles(wow)\n",
    "    print('% = ', checkforerrorout(wow))\n",
    "    if err:\n",
    "        print('Error 1 at', a)\n",
    "        #plt.imshow(binary[wow[0]-2:wow[1] + 2, wow[2]-2:wow[2] + half +7], cmap = 'gray')\n",
    "        #inp = str(input('Skip this image? '))\n",
    "        im += 1\n",
    "        print('im bumped to', im)\n",
    "        wow = plotting(siggie[im])\n",
    "        print('trying to plot ', im, 'checking for errors...')\n",
    "        err = checkforerror(wow)\n",
    "        errs = checkfordoubles(wow)\n",
    "        print('% = ', checkforerrorout(wow))\n",
    "        if errs:\n",
    "            \n",
    "            \n",
    "            print('Error 2 at bumped image')\n",
    "            if first == False:\n",
    "                half = abs(wow[0] - wow[1]) // 2\n",
    "                axs[n1, n2].imshow(binary[wow[0]-2:wow[1] + 2, wow[2]-2:wow[2] + half +7], cmap = 'gray')\n",
    "                xx = checkforerrorout(wow)\n",
    "                axs[n1,n2].set_title(solution[pos]+' '+ str(int(xx * 100)))\n",
    "                axs[n1,n2].axis('off')\n",
    "                im -= 1\n",
    "                first = True\n",
    "            else:\n",
    "                axs[n1, n2].imshow(binary[wow[0]-2:wow[1] + 2, wow[2] + half + 7:wow[3]+2], cmap = 'gray')\n",
    "                xx = checkforerrorout(wow)\n",
    "                axs[n1,n2].set_title(solution[pos]+' '+ str(int(xx * 100)))\n",
    "                axs[n1,n2].axis('off')\n",
    "                first = False\n",
    "\n",
    "        \n",
    "        \n",
    "        else:\n",
    "            print('No errors in bumped image')\n",
    "            axs[n1, n2].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "            #xx = checkforerrorout(wow)\n",
    "            axs[n1,n2].set_title(solution[pos]+' '+ str(int(xx * 100)))\n",
    "            axs[n1,n2].axis('off')\n",
    "    elif errs:\n",
    "        print('Error 2 at', a)\n",
    "        if first == False:\n",
    "            half = abs(wow[0] - wow[1]) // 2\n",
    "            axs[n1, n2].imshow(binary[wow[0]-2:wow[1] + 2, wow[2]-2:wow[2] + half +8], cmap = 'gray')\n",
    "            xx = checkforerrorout(wow)\n",
    "            axs[n1,n2].set_title(solution[pos]+' '+ str(int(xx * 100)))\n",
    "            axs[n1,n2].axis('off')\n",
    "            im -= 1\n",
    "            first = True\n",
    "        else:\n",
    "            axs[n1, n2].imshow(binary[wow[0]-2:wow[1] + 2, wow[2] + half + 8:wow[3]+2], cmap = 'gray')\n",
    "            xx = checkforerrorout(wow)\n",
    "            axs[n1,n2].set_title(solution[pos]+' '+ str(int(xx * 100)))\n",
    "            axs[n1,n2].axis('off')\n",
    "            first = False\n",
    "            \n",
    "    else:\n",
    "        print('No errors found!')\n",
    "        axs[n1, n2].imshow(binary[wow[0]-2:wow[1]+2, wow[2]-2:wow[3]+2], cmap = 'gray')\n",
    "        xx = checkforerrorout(wow)\n",
    "        axs[n1,n2].set_title(solution[pos]+' '+ str(int(xx * 100)))\n",
    "        axs[n1,n2].axis('off')\n",
    "        print('DONE PLOTTING - im', im)\n",
    "\n",
    "    a += 1\n",
    "    pos += 1\n",
    "    im += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.01051,
     "end_time": "2020-08-26T00:52:32.569058",
     "exception": false,
     "start_time": "2020-08-26T00:52:32.558548",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Compare the above segmentations with the original image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-26T00:52:32.602191Z",
     "iopub.status.busy": "2020-08-26T00:52:32.597302Z",
     "iopub.status.idle": "2020-08-26T00:52:32.774823Z",
     "shell.execute_reply": "2020-08-26T00:52:32.775425Z"
    },
    "papermill": {
     "duration": 0.195502,
     "end_time": "2020-08-26T00:52:32.775587",
     "exception": false,
     "start_time": "2020-08-26T00:52:32.580085",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(hi, cmap=\"gray\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {
    "papermill": {
     "duration": 0.011232,
     "end_time": "2020-08-26T00:52:32.799271",
     "exception": false,
     "start_time": "2020-08-26T00:52:32.788039",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Conclusion\n",
    "The above segmentation looks good. We can move on to the next file, captchas_saving.ipynb, where we will save to disk each segmentation in its appropriate directory. \n",
    "Thank you for reading, and if you enjoyed my work please don't forget to leave an upvote!"
   ]
  }
 ],
 "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": "3.7.6"
  },
  "papermill": {
   "duration": 8.121511,
   "end_time": "2020-08-26T00:52:32.919608",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2020-08-26T00:52:24.798097",
   "version": "2.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}