pen_paper.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The main code is in the last cell\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[79, 108, 76], [162, 255, 255]]\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import time\n",
    "# A required callback method that goes into the trackbar function.\n",
    "def nothing(x):\n",
    "    pass\n",
    "\n",
    "# Initializing the webcam feed.\n",
    "cap = cv2.VideoCapture(0)\n",
    "cap.set(3,1280)\n",
    "cap.set(4,720)\n",
    "\n",
    "# Create a window named trackbars.\n",
    "cv2.namedWindow(\"Trackbars\")\n",
    "\n",
    "# Now create 6 trackbars that will control the lower and upper range of \n",
    "# H,S and V channels. The Arguments are like this: Name of trackbar, \n",
    "# window name, range,callback function. For Hue the range is 0-179 and\n",
    "# for S,V its 0-255.\n",
    "cv2.createTrackbar(\"L - H\", \"Trackbars\", 0, 179, nothing)\n",
    "cv2.createTrackbar(\"L - S\", \"Trackbars\", 0, 255, nothing)\n",
    "cv2.createTrackbar(\"L - V\", \"Trackbars\", 0, 255, nothing)\n",
    "cv2.createTrackbar(\"U - H\", \"Trackbars\", 179, 179, nothing)\n",
    "cv2.createTrackbar(\"U - S\", \"Trackbars\", 255, 255, nothing)\n",
    "cv2.createTrackbar(\"U - V\", \"Trackbars\", 255, 255, nothing)\n",
    " \n",
    "while True:\n",
    "    \n",
    "    \n",
    "    # Start reading the webcam feed frame by frame.\n",
    "    ret, frame = cap.read()\n",
    "    if not ret:\n",
    "        break\n",
    "    # Flip the frame horizontally (Not required)\n",
    "    frame = cv2.flip( frame, 1 ) \n",
    "    \n",
    "    # Convert the BGR image to HSV image.\n",
    "    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n",
    "    \n",
    "    # Get the new values of the trackbar in real time as the user changes \n",
    "    # them\n",
    "    l_h = cv2.getTrackbarPos(\"L - H\", \"Trackbars\")\n",
    "    l_s = cv2.getTrackbarPos(\"L - S\", \"Trackbars\")\n",
    "    l_v = cv2.getTrackbarPos(\"L - V\", \"Trackbars\")\n",
    "    u_h = cv2.getTrackbarPos(\"U - H\", \"Trackbars\")\n",
    "    u_s = cv2.getTrackbarPos(\"U - S\", \"Trackbars\")\n",
    "    u_v = cv2.getTrackbarPos(\"U - V\", \"Trackbars\")\n",
    " \n",
    "    # Set the lower and upper HSV range according to the value selected\n",
    "    # by the trackbar\n",
    "    lower_range = np.array([l_h, l_s, l_v])\n",
    "    upper_range = np.array([u_h, u_s, u_v])\n",
    "    \n",
    "    # Filter the image and get the binary mask, where white represents \n",
    "    # your target color\n",
    "    mask = cv2.inRange(hsv, lower_range, upper_range)\n",
    " \n",
    "    # You can also visualize the real part of the target color (Optional)\n",
    "    res = cv2.bitwise_and(frame, frame, mask=mask)\n",
    "    \n",
    "    # Converting the binary mask to 3 channel image, this is just so \n",
    "    # we can stack it with the others\n",
    "    mask_3 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)\n",
    "    \n",
    "    # stack the mask, orginal frame and the filtered result\n",
    "    stacked = np.hstack((mask_3,frame,res))\n",
    "    \n",
    "    # Show this stacked frame at 40% of the size.\n",
    "    cv2.imshow('Trackbars',cv2.resize(stacked,None,fx=0.4,fy=0.4))\n",
    "   \n",
    "    # If the user presses ESC then exit the program\n",
    "    key = cv2.waitKey(1)\n",
    "    if key == 27:\n",
    "        break\n",
    "    \n",
    "    # If the user presses `s` then print this array.\n",
    "    if key == ord('s'):\n",
    "        \n",
    "        thearray = [[l_h,l_s,l_v],[u_h, u_s, u_v]]\n",
    "        print(thearray)\n",
    "        \n",
    "        # Also save this array as penval.npy\n",
    "        np.save('penval',thearray)\n",
    "        break\n",
    "    \n",
    "# Release the camera &amp; destroy the windows.    \n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This variable determines if we want to load color range from memory \n",
    "# or use the ones defined here. \n",
    "# This variable determines if we want to load color range from memory \n",
    "# or use the ones defined here. \n",
    "load_from_disk = True\n",
    "import numpy as np\n",
    "import cv2\n",
    "# If true then load color range from memory\n",
    "if load_from_disk:\n",
    "    penval = np.load('penval.npy')\n",
    "\n",
    "cap = cv2.VideoCapture(0)\n",
    "cap.set(3,1280)\n",
    "cap.set(4,720)\n",
    "\n",
    "# Creating A 5x5 kernel for morphological operations\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "\n",
    "while(1):\n",
    "    \n",
    "    ret, frame = cap.read()\n",
    "    if not ret:\n",
    "        break\n",
    "        \n",
    "    frame = cv2.flip( frame, 1 )\n",
    "\n",
    "    # Convert BGR to HSV\n",
    "    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n",
    "    \n",
    "    # If you're reading from memory then load the upper and lower ranges \n",
    "    # from there\n",
    "    if load_from_disk:\n",
    "            lower_range = penval[0]\n",
    "            upper_range = penval[1]\n",
    "            \n",
    "    # Otherwise define your own custom values for upper and lower range.\n",
    "    else:             \n",
    "       lower_range  = np.array([26,80,147])\n",
    "       upper_range = np.array([81,255,255])\n",
    "    \n",
    "    mask = cv2.inRange(hsv, lower_range, upper_range)\n",
    "    \n",
    "    # Perform the morphological operations to get rid of the noise.\n",
    "    # Erosion Eats away the white part while dilation expands it.\n",
    "    mask = cv2.erode(mask,kernel,iterations = 1)\n",
    "    mask = cv2.dilate(mask,kernel,iterations = 2)\n",
    "\n",
    "    res = cv2.bitwise_and(frame,frame, mask= mask)\n",
    "\n",
    "    mask_3 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)\n",
    "    \n",
    "    # stack all frames and show it\n",
    "    stacked = np.hstack((mask_3,frame,res))\n",
    "    cv2.imshow('Trackbars',cv2.resize(stacked,None,fx=0.4,fy=0.4))\n",
    "    \n",
    "    k = cv2.waitKey(5)  ;0xFF\n",
    "    if k == 27:\n",
    "        break\n",
    "\n",
    "cv2.destroyAllWindows()\n",
    "cap.release()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This variable determines if we want to load color range from memory \n",
    "# or use the ones defined in the notebook. \n",
    "load_from_disk = True\n",
    "import numpy as np\n",
    "import cv2\n",
    "# If true then load color range from memory\n",
    "if load_from_disk:\n",
    "    penval = np.load('penval.npy')\n",
    "\n",
    "cap = cv2.VideoCapture(0)\n",
    "cap.set(3,1280)\n",
    "cap.set(4,720)\n",
    "\n",
    "# kernel for morphological operations\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "\n",
    "# set the window to auto-size so we can view this full screen.\n",
    "cv2.namedWindow('image', cv2.WINDOW_NORMAL)\n",
    "\n",
    "# This threshold is used to filter noise, the contour area must be \n",
    "# bigger than this to qualify as an actual contour.\n",
    "noiseth = 500\n",
    "\n",
    "while(1):\n",
    "    \n",
    "    _, frame = cap.read()\n",
    "    frame = cv2.flip( frame, 1 )\n",
    "\n",
    "    # Convert BGR to HSV\n",
    "    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n",
    "    \n",
    "    # If you're reading from memory then load the upper and lower \n",
    "    # ranges from there\n",
    "    if load_from_disk:\n",
    "            lower_range = penval[0]\n",
    "            upper_range = penval[1]\n",
    "            \n",
    "    # Otherwise define your own custom values for upper and lower range.\n",
    "    else:             \n",
    "       lower_range  = np.array([26,80,147])\n",
    "       upper_range = np.array([81,255,255])\n",
    "    \n",
    "    mask = cv2.inRange(hsv, lower_range, upper_range)\n",
    "    \n",
    "    # Perform the morphological operations to get rid of the noise\n",
    "    mask = cv2.erode(mask,kernel,iterations = 1)\n",
    "    mask = cv2.dilate(mask,kernel,iterations = 2)\n",
    "    \n",
    "    # Find Contours in the frame.\n",
    "    contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL,\n",
    "                                           cv2.CHAIN_APPROX_SIMPLE)\n",
    "    \n",
    "    # Make sure there is a contour present and also make sure its size \n",
    "    # is bigger than noise threshold.\n",
    "    if contours and cv2.contourArea(max(contours, \n",
    "                               key = cv2.contourArea)) > noiseth:\n",
    "        \n",
    "        # Grab the biggest contour with respect to area\n",
    "        c = max(contours, key = cv2.contourArea)\n",
    "        \n",
    "        # Get bounding box coordinates around that contour\n",
    "        x,y,w,h = cv2.boundingRect(c)\n",
    "        \n",
    "        # Draw that bounding box\n",
    "        cv2.rectangle(frame,(x,y),(x+w,y+h),(0,25,255),2)        \n",
    "\n",
    "    cv2.imshow('image',frame)\n",
    "    \n",
    "    k = cv2.waitKey(5); 0xFF\n",
    "    if k == 27:\n",
    "        break\n",
    "\n",
    "cv2.destroyAllWindows()\n",
    "cap.release()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "load_from_disk = True\n",
    "if load_from_disk:\n",
    "    penval = np.load('penval.npy')\n",
    "\n",
    "cap = cv2.VideoCapture(0)\n",
    "cap.set(3,1280)\n",
    "cap.set(4,720)\n",
    "\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "\n",
    "# Initializing the canvas on which we will draw upon\n",
    "canvas = None\n",
    "\n",
    "# Initilize x1,y1 points\n",
    "x1,y1=0,0\n",
    "\n",
    "# Threshold for noise\n",
    "noiseth = 800\n",
    "\n",
    "while(1):\n",
    "    _, frame = cap.read()\n",
    "    frame = cv2.flip( frame, 1 )\n",
    "    \n",
    "    # Initialize the canvas as a black image of the same size as the frame.\n",
    "    if canvas is None:\n",
    "        canvas = np.zeros_like(frame)\n",
    "\n",
    "    # Convert BGR to HSV\n",
    "    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n",
    "    \n",
    "    # If you're reading from memory then load the upper and lower ranges \n",
    "    # from there\n",
    "    if load_from_disk:\n",
    "            lower_range = penval[0]\n",
    "            upper_range = penval[1]\n",
    "            \n",
    "    # Otherwise define your own custom values for upper and lower range.\n",
    "    else:             \n",
    "       lower_range  = np.array([26,80,147])\n",
    "       upper_range = np.array([81,255,255])\n",
    "    \n",
    "    mask = cv2.inRange(hsv, lower_range, upper_range)\n",
    "    \n",
    "    # Perform morphological operations to get rid of the noise\n",
    "    mask = cv2.erode(mask,kernel,iterations = 1)\n",
    "    mask = cv2.dilate(mask,kernel,iterations = 2)\n",
    "    \n",
    "    # Find Contours\n",
    "    contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n",
    "    \n",
    "    # Make sure there is a contour present and also its size is bigger than \n",
    "    # the noise threshold.\n",
    "    if contours and cv2.contourArea(max(contours, \n",
    "                                 key = cv2.contourArea)) > noiseth:\n",
    "                \n",
    "        c = max(contours, key = cv2.contourArea)    \n",
    "        x2,y2,w,h = cv2.boundingRect(c)\n",
    "        \n",
    "        # If there were no previous points then save the detected x2,y2 \n",
    "        # coordinates as x1,y1. \n",
    "        # This is true when we writing for the first time or when writing \n",
    "        # again when the pen had disappeared from view.\n",
    "        if x1 == 0 and y1 == 0:\n",
    "            x1,y1= x2,y2\n",
    "            \n",
    "        else:\n",
    "            # Draw the line on the canvas\n",
    "            canvas = cv2.line(canvas, (x1,y1),(x2,y2), [255,0,0], 4)\n",
    "        \n",
    "        # After the line is drawn the new points become the previous points.\n",
    "        x1,y1= x2,y2\n",
    "\n",
    "    else:\n",
    "        # If there were no contours detected then make x1,y1 = 0\n",
    "        x1,y1 =0,0\n",
    "    \n",
    "    # Merge the canvas and the frame.\n",
    "    frame = cv2.add(frame,canvas)\n",
    "    \n",
    "    # Optionally stack both frames and show it.\n",
    "    stacked = np.hstack((canvas,frame))\n",
    "    cv2.imshow('Trackbars',cv2.resize(stacked,None,fx=0.6,fy=0.6))\n",
    "\n",
    "    k = cv2.waitKey(1) ; 0xFF\n",
    "    if k == 27:\n",
    "        break\n",
    "        \n",
    "    # When c is pressed clear the canvas\n",
    "    if k == ord('c'):\n",
    "        canvas = None\n",
    "\n",
    "cv2.destroyAllWindows()\n",
    "cap.release()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "import time\n",
    "load_from_disk = True\n",
    "if load_from_disk:\n",
    "    penval = np.load('penval.npy')\n",
    "\n",
    "cap = cv2.VideoCapture(0)\n",
    "cap.set(3,1280)\n",
    "cap.set(4,720)\n",
    "\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "\n",
    "# Making window size adjustable\n",
    "cv2.namedWindow('image', cv2.WINDOW_NORMAL)\n",
    "\n",
    "# This is the canvas on which we will draw upon\n",
    "canvas=None\n",
    "\n",
    "# Initilize x1,y1 points\n",
    "x1,y1=0,0\n",
    "\n",
    "# Threshold for noise\n",
    "noiseth = 800\n",
    "\n",
    "# Threshold for wiper, the size of the contour must be bigger than for us to\n",
    "# clear the canvas \n",
    "wiper_thresh = 40000\n",
    "\n",
    "# A variable which tells when to clear canvas, if its True then we clear the canvas\n",
    "clear = False\n",
    "\n",
    "while(1):\n",
    "    _, frame = cap.read()\n",
    "    frame = cv2.flip( frame, 1 )\n",
    "    \n",
    "    # Initialize the canvas as a black image\n",
    "    if canvas is None:\n",
    "        canvas = np.zeros_like(frame)\n",
    "\n",
    "    # Convert BGR to HSV\n",
    "    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n",
    "    \n",
    "    # If you're reading from memory then load the upper and lower ranges \n",
    "    # from there\n",
    "    if load_from_disk:\n",
    "            lower_range = penval[0]\n",
    "            upper_range = penval[1]\n",
    "            \n",
    "    # Otherwise define your own custom values for upper and lower range.\n",
    "    else:             \n",
    "       lower_range  = np.array([26,80,147])\n",
    "       upper_range = np.array([81,255,255])\n",
    "    \n",
    "    mask = cv2.inRange(hsv, lower_range, upper_range)\n",
    "    \n",
    "    # Perform the morphological operations to get rid of the noise\n",
    "    mask = cv2.erode(mask,kernel,iterations = 1)\n",
    "    mask = cv2.dilate(mask,kernel,iterations = 2)\n",
    "    \n",
    "    # Find Contours.\n",
    "    contours, hierarchy = cv2.findContours(mask,\n",
    "    cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)\n",
    "    \n",
    "    # Make sure there is a contour present and also its size is bigger than \n",
    "    # the noise threshold.\n",
    "    if contours and cv2.contourArea(max(contours,\n",
    "                                   key = cv2.contourArea)) > noiseth:\n",
    "                \n",
    "        c = max(contours, key = cv2.contourArea)    \n",
    "        x2,y2,w,h = cv2.boundingRect(c)\n",
    "        \n",
    "        # Get the area of the contour\n",
    "        area = cv2.contourArea(c)\n",
    "        \n",
    "        # If there were no previous points then save the detected x2,y2 \n",
    "        # coordinates as x1,y1. \n",
    "        if x1 == 0 and y1 == 0:\n",
    "            x1,y1= x2,y2\n",
    "            \n",
    "        else:\n",
    "            # Draw the line on the canvas\n",
    "            canvas = cv2.line(canvas, (x1,y1),(x2,y2),\n",
    "            [255,0,0], 5)\n",
    "        \n",
    "        # After the line is drawn the new points become the previous points.\n",
    "        x1,y1= x2,y2\n",
    "        \n",
    "        # Now if the area is greater than the wiper threshold then set the  \n",
    "        # clear variable to True and warn User.\n",
    "        if area > wiper_thresh:\n",
    "           cv2.putText(canvas,'Clearing Canvas', (100,200), \n",
    "           cv2.FONT_HERSHEY_SIMPLEX,2, (0,0,255), 5, cv2.LINE_AA)\n",
    "           clear = True \n",
    "\n",
    "    else:\n",
    "        # If there were no contours detected then make x1,y1 = 0\n",
    "        x1,y1 =0,0\n",
    "    \n",
    "   \n",
    "    # Now this piece of code is just for smooth drawing. (Optional)\n",
    "    _ , mask = cv2.threshold(cv2.cvtColor(canvas, cv2.COLOR_BGR2GRAY), 20, \n",
    "    255, cv2.THRESH_BINARY)\n",
    "    foreground = cv2.bitwise_and(canvas, canvas, mask = mask)\n",
    "    background = cv2.bitwise_and(frame, frame,\n",
    "    mask = cv2.bitwise_not(mask))\n",
    "    frame = cv2.add(foreground,background)\n",
    "\n",
    "    cv2.imshow('image',frame)\n",
    "    \n",
    "    k = cv2.waitKey(5) ; 0xFF\n",
    "    if k == 27:\n",
    "        break\n",
    "    \n",
    "    # Clear the canvas after 1 second if the clear variable is true\n",
    "    if clear == True:\n",
    "        \n",
    "        time.sleep(1)\n",
    "        canvas = None\n",
    "        \n",
    "        # And then set clear to false\n",
    "        clear = False\n",
    "        \n",
    "cv2.destroyAllWindows()\n",
    "cap.release()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "import time\n",
    "load_from_disk = True\n",
    "if load_from_disk:\n",
    "    penval = np.load('penval.npy')\n",
    "\n",
    "cap = cv2.VideoCapture(0)\n",
    "\n",
    "# Load these 2 images and resize them to the same size.\n",
    "pen_img = cv2.resize(cv2.imread('pen.jpg',1), (50, 50))\n",
    "eraser_img = cv2.resize(cv2.imread('download.jpg',1), (50, 50))\n",
    "\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "\n",
    "# Making window size adjustable\n",
    "cv2.namedWindow('image', cv2.WINDOW_NORMAL)\n",
    "\n",
    "# This is the canvas on which we will draw upon\n",
    "canvas = None\n",
    "\n",
    "# Create a background subtractor Object\n",
    "backgroundobject = cv2.createBackgroundSubtractorMOG2(detectShadows = False)\n",
    "\n",
    "# This threshold determines the amount of disruption in the background.\n",
    "background_threshold = 600\n",
    "\n",
    "# A variable which tells you if you're using a pen or an eraser.\n",
    "switch = 'Pen'\n",
    "\n",
    "# With this variable we will monitor the time between previous switch.\n",
    "last_switch = time.time()\n",
    "\n",
    "# Initilize x1,y1 points\n",
    "x1,y1=0,0\n",
    "\n",
    "# Threshold for noise\n",
    "noiseth = 800\n",
    "\n",
    "# Threshold for wiper, the size of the contour must be bigger than this for # us to clear the canvas\n",
    "wiper_thresh = 40000\n",
    "\n",
    "# A variable which tells when to clear canvas\n",
    "clear = False\n",
    "\n",
    "while(1):\n",
    "    _, frame = cap.read()\n",
    "    frame = cv2.flip( frame, 1 )\n",
    "    \n",
    "    # Initilize the canvas as a black image\n",
    "    if canvas is None:\n",
    "        canvas = np.zeros_like(frame)\n",
    "        \n",
    "    # Take the top left of the frame and apply the background subtractor\n",
    "    # there    \n",
    "    top_left = frame[0: 50, 0: 50]\n",
    "    fgmask = backgroundobject.apply(top_left)\n",
    "    \n",
    "    # Note the number of pixels that are white, this is the level of \n",
    "    # disruption.\n",
    "    switch_thresh = np.sum(fgmask==255)\n",
    "    \n",
    "    # If the disruption is greater than background threshold and there has \n",
    "    # been some time after the previous switch then you. can change the \n",
    "    # object type.\n",
    "    if switch_thresh>background_threshold and (time.time()-last_switch) > 1:\n",
    "\n",
    "        # Save the time of the switch. \n",
    "        last_switch = time.time()\n",
    "        \n",
    "        if switch == 'Pen':\n",
    "            switch = 'Eraser'\n",
    "        else:\n",
    "            switch = 'Pen'\n",
    "\n",
    "    # Convert BGR to HSV\n",
    "    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n",
    "    \n",
    "    # If you're reading from memory then load the upper and lower ranges \n",
    "    # from there\n",
    "    if load_from_disk:\n",
    "            lower_range = penval[0]\n",
    "            upper_range = penval[1]\n",
    "            \n",
    "    # Otherwise define your own custom values for upper and lower range.\n",
    "    else:             \n",
    "       lower_range  = np.array([26,80,147])\n",
    "       upper_range = np.array([81,255,255])\n",
    "    \n",
    "    mask = cv2.inRange(hsv, lower_range, upper_range)\n",
    "    \n",
    "    # Perform morphological operations to get rid of the noise\n",
    "    mask = cv2.erode(mask,kernel,iterations = 1)\n",
    "    mask = cv2.dilate(mask,kernel,iterations = 2)\n",
    "    \n",
    "    # Find Contours\n",
    "    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, \n",
    "    cv2.CHAIN_APPROX_SIMPLE)\n",
    "    \n",
    "    # Make sure there is a contour present and also it size is bigger than \n",
    "    # noise threshold.\n",
    "    if contours and cv2.contourArea(max(contours,\n",
    "                                      key = cv2.contourArea)) > noiseth:\n",
    "                \n",
    "        c = max(contours, key = cv2.contourArea)    \n",
    "        x2,y2,w,h = cv2.boundingRect(c)\n",
    "        \n",
    "        # Get the area of the contour\n",
    "        area = cv2.contourArea(c)\n",
    "        \n",
    "        # If there were no previous points then save the detected x2,y2 \n",
    "        # coordinates as x1,y1. \n",
    "        if x1 == 0 and y1 == 0:\n",
    "            x1,y1= x2,y2\n",
    "            \n",
    "        else:\n",
    "            if switch == 'Pen':\n",
    "                # Draw the line on the canvas\n",
    "                canvas = cv2.line(canvas, (x1,y1),\n",
    "                (x2,y2), [255,0,0], 5)\n",
    "                \n",
    "            else:\n",
    "                cv2.circle(canvas, (x2, y2), 20,\n",
    "                (0,0,0), -1)\n",
    "            \n",
    "            \n",
    "        \n",
    "        # After the line is drawn the new points become the previous points.\n",
    "        x1,y1= x2,y2\n",
    "        \n",
    "        # Now if the area is greater than the wiper threshold then set the \n",
    "        # clear variable to True\n",
    "        if area > wiper_thresh:\n",
    "           cv2.putText(canvas,'Clearing Canvas',(0,200), \n",
    "           cv2.FONT_HERSHEY_SIMPLEX, 2, (0,0,255), 1, cv2.LINE_AA)\n",
    "           clear = True \n",
    "\n",
    "    else:\n",
    "        # If there were no contours detected then make x1,y1 = 0\n",
    "        x1,y1 =0,0\n",
    "    \n",
    "   \n",
    "    # Now this piece of code is just for smooth drawing. (Optional)\n",
    "    _ , mask = cv2.threshold(cv2.cvtColor (canvas, cv2.COLOR_BGR2GRAY), 20, \n",
    "    255, cv2.THRESH_BINARY)\n",
    "    foreground = cv2.bitwise_and(canvas, canvas, mask = mask)\n",
    "    background = cv2.bitwise_and(frame, frame,\n",
    "    mask = cv2.bitwise_not(mask))\n",
    "    frame = cv2.add(foreground,background)\n",
    "\n",
    "    # Switch the images depending upon what we're using, pen or eraser.\n",
    "    if switch != 'Pen':\n",
    "        cv2.circle(frame, (x1, y1), 20, (255,255,255), -1)\n",
    "        frame[0: 50, 0: 50] = eraser_img\n",
    "    else:\n",
    "        frame[0: 50, 0: 50] = pen_img\n",
    "\n",
    "    cv2.imshow('image',frame)\n",
    "\n",
    "    k = cv2.waitKey(5); 0xFF\n",
    "    if k == 27:\n",
    "        break\n",
    "    \n",
    "    # Clear the canvas after 1 second, if the clear variable is true\n",
    "    if clear == True: \n",
    "        time.sleep(1)\n",
    "        canvas = None\n",
    "        \n",
    "        # And then set clear to false\n",
    "        clear = False\n",
    "        \n",
    "cv2.destroyAllWindows()\n",
    "cap.release()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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