P1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Self-Driving Car Engineer Nanodegree\n",
    "\n",
    "\n",
    "## Project: **Finding Lane Lines on the Road** \n",
    "***\n",
    "In this project, you will use the tools you learned about in the lesson to identify lane lines on the road.  You can develop your pipeline on a series of individual images, and later apply the result to a video stream (really just a series of images). Check out the video clip \"raw-lines-example.mp4\" (also contained in this repository) to see what the output should look like after using the helper functions below. \n",
    "\n",
    "Once you have a result that looks roughly like \"raw-lines-example.mp4\", you'll need to get creative and try to average and/or extrapolate the line segments you've detected to map out the full extent of the lane lines.  You can see an example of the result you're going for in the video \"P1_example.mp4\".  Ultimately, you would like to draw just one line for the left side of the lane, and one for the right.\n",
    "\n",
    "In addition to implementing code, there is a brief writeup to complete. The writeup should be completed in a separate file, which can be either a markdown file or a pdf document. There is a [write up template](https://github.com/udacity/CarND-LaneLines-P1/blob/master/writeup_template.md) that can be used to guide the writing process. Completing both the code in the Ipython notebook and the writeup template will cover all of the [rubric points](https://review.udacity.com/#!/rubrics/322/view) for this project.\n",
    "\n",
    "---\n",
    "Let's have a look at our first image called 'test_images/solidWhiteRight.jpg'.  Run the 2 cells below (hit Shift-Enter or the \"play\" button above) to display the image.\n",
    "\n",
    "**Note: If, at any point, you encounter frozen display windows or other confounding issues, you can always start again with a clean slate by going to the \"Kernel\" menu above and selecting \"Restart & Clear Output\".**\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**The tools you have are color selection, region of interest selection, grayscaling, Gaussian smoothing, Canny Edge Detection and Hough Tranform line detection.  You  are also free to explore and try other techniques that were not presented in the lesson.  Your goal is piece together a pipeline to detect the line segments in the image, then average/extrapolate them and draw them onto the image for display (as below).  Once you have a working pipeline, try it out on the video stream below.**\n",
    "\n",
    "---\n",
    "\n",
    "<figure>\n",
    " <img src=\"examples/line-segments-example.jpg\" width=\"380\" alt=\"Combined Image\" />\n",
    " <figcaption>\n",
    " <p></p> \n",
    " <p style=\"text-align: center;\"> Your output should look something like this (above) after detecting line segments using the helper functions below </p> \n",
    " </figcaption>\n",
    "</figure>\n",
    " <p></p> \n",
    "<figure>\n",
    " <img src=\"examples/laneLines_thirdPass.jpg\" width=\"380\" alt=\"Combined Image\" />\n",
    " <figcaption>\n",
    " <p></p> \n",
    " <p style=\"text-align: center;\"> Your goal is to connect/average/extrapolate line segments to get output like this</p> \n",
    " </figcaption>\n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Run the cell below to import some packages.  If you get an `import error` for a package you've already installed, try changing your kernel (select the Kernel menu above --> Change Kernel).  Still have problems?  Try relaunching Jupyter Notebook from the terminal prompt.  Also, consult the forums for more troubleshooting tips.**  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing some useful packages\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "import numpy as np\n",
    "import cv2\n",
    "%matplotlib inline\n",
    "\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\"\n",
    "\n",
    "#install ffmpeg\n",
    "import imageio\n",
    "imageio.plugins.ffmpeg.download()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read in an Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This image is: <class 'numpy.ndarray'> with dimensions: (540, 960, 3)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4df70f9be0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4df7177748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#reading in an image\n",
    "image = mpimg.imread('test_images/solidWhiteRight.jpg')\n",
    "\n",
    "#printing out some stats and plotting\n",
    "print('This image is:', type(image), 'with dimensions:', image.shape)\n",
    "plt.imshow(image)  # if you wanted to show a single color channel image called 'gray', for example, call as plt.imshow(gray, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ideas for Lane Detection Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Some OpenCV functions (beyond those introduced in the lesson) that might be useful for this project are:**\n",
    "\n",
    "`cv2.inRange()` for color selection  \n",
    "`cv2.fillPoly()` for regions selection  \n",
    "`cv2.line()` to draw lines on an image given endpoints  \n",
    "`cv2.addWeighted()` to coadd / overlay two images\n",
    "`cv2.cvtColor()` to grayscale or change color\n",
    "`cv2.imwrite()` to output images to file  \n",
    "`cv2.bitwise_and()` to apply a mask to an image\n",
    "\n",
    "**Check out the OpenCV documentation to learn about these and discover even more awesome functionality!**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helper Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below are some helper functions to help get you started. They should look familiar from the lesson!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "\n",
    "def grayscale(img):\n",
    "    \"\"\"Applies the Grayscale transform\n",
    "    This will return an image with only one color channel\n",
    "    but NOTE: to see the returned image as grayscale\n",
    "    (assuming your grayscaled image is called 'gray')\n",
    "    you should call plt.imshow(gray, cmap='gray')\"\"\"\n",
    "    return cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n",
    "    # Or use BGR2GRAY if you read an image with cv2.imread()\n",
    "    # return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "def canny(img, low_threshold, high_threshold):\n",
    "    \"\"\"Applies the Canny transform\"\"\"\n",
    "    return cv2.Canny(img, low_threshold, high_threshold)\n",
    "\n",
    "def gaussian_blur(img, kernel_size):\n",
    "    \"\"\"Applies a Gaussian Noise kernel\"\"\"\n",
    "    return cv2.GaussianBlur(img, (kernel_size, kernel_size), 0)\n",
    "\n",
    "def region_of_interest(img, vertices):\n",
    "    \"\"\"\n",
    "    Applies an image mask.\n",
    "    \n",
    "    Only keeps the region of the image defined by the polygon\n",
    "    formed from `vertices`. The rest of the image is set to black.\n",
    "    \"\"\"\n",
    "    #defining a blank mask to start with\n",
    "    mask = np.zeros_like(img)   \n",
    "    \n",
    "    #defining a 3 channel or 1 channel color to fill the mask with depending on the input image\n",
    "    if len(img.shape) > 2:\n",
    "        channel_count = img.shape[2]  # i.e. 3 or 4 depending on your image\n",
    "        ignore_mask_color = (255,) * channel_count\n",
    "    else:\n",
    "        ignore_mask_color = 255\n",
    "        \n",
    "    #filling pixels inside the polygon defined by \"vertices\" with the fill color    \n",
    "    cv2.fillPoly(mask, vertices, ignore_mask_color)\n",
    "    \n",
    "    #returning the image only where mask pixels are nonzero\n",
    "    masked_image = cv2.bitwise_and(img, mask)\n",
    "    return masked_image\n",
    "\n",
    "def draw_edges(img, lines, color=[255, 0 ,0], thickness=2):\n",
    "    \"\"\" NOTE: this is the initial draw_lines that was provided in the starter code,  \n",
    "    used to draw the edges of identified in the image using the hough transform, \n",
    "    to be combined with the output of the line drawing later for superposition \n",
    "    \"\"\"\n",
    "    \n",
    "    for line in lines:\n",
    "       \n",
    "        for x1,y1,x2,y2 in line:\n",
    "            cv2.line(img, (x1, y1), (x2, y2), color, thickness = 2)\n",
    "    \n",
    "\n",
    "def draw_lines(img, lines, color=[255, 0, 0], thickness=5):\n",
    "    \"\"\"\n",
    "    NOTE: this is the function used to draw solid lines across the identified image through the identified lanes\n",
    "    \n",
    "    Think about things like separating line segments by their \n",
    "    slope ((y2-y1)/(x2-x1)) to decide which segments are part of the left\n",
    "    line vs. the right line.  Then, you can average the position of each of \n",
    "    the lines and extrapolate to the top and bottom of the lane.\n",
    "    \n",
    "    this function will draw on a black image to be combined with weighted_img later\n",
    "    \"\"\"\n",
    "    \n",
    "    rm = []\n",
    "    lm = [] \n",
    "    rc = []\n",
    "    lc = []\n",
    "    \n",
    "    max_slope = 0.8\n",
    "    min_slope = 0.5\n",
    "    \n",
    "    for line in lines:\n",
    "        \n",
    "        for x1,y1,x2,y2 in line:\n",
    "            #iterate through each line points (x1, y1, x2, y2) calculate slope and centers\n",
    "            slope = (y2-y1)/(x2-x1)\n",
    "            center = [(x1+x2)/2, (y1 + y2)/2]\n",
    "            \n",
    "            #separate right and left by measuring slope, throw out vertical/horizontal slope\n",
    "            if((slope > min_slope) & (slope < max_slope)): \n",
    "                rm.append(slope)\n",
    "                rc.append(center)\n",
    "\n",
    "            elif ((slope < -min_slope) & (slope > -max_slope)):\n",
    "                lm.append(slope)\n",
    "                lc.append(center)\n",
    "                \n",
    "\n",
    "            \n",
    "#             angle = np.arctan(slope)\n",
    "#             if ((angle > np.pi/6) & (angle < np.pi/2)):\n",
    "#                 rm.append(slope)\n",
    "#                 rc.append(center)\n",
    "#             elif((angle < -np.pi/6) & (angle > -np.pi/2)):\n",
    "#                 lm.append(slope)\n",
    "#                 lc.append(center)\n",
    "                \n",
    "    #average over all right/left center, slope values to get single center and slope\n",
    "    r_slope = np.sum(rm)/len(rm)\n",
    "    l_slope = np.sum(lm)/len(lm)\n",
    "\n",
    "    r_center = np.divide(np.sum(rc,axis = 0), len(rc))\n",
    "    l_center = np.divide(np.sum(lc,axis = 0), len(lc))\n",
    "    #specify line height (half way point of image height)\n",
    "    line_height = 330\n",
    "    line_height = int(round(line_height,0))\n",
    "    line_bottom = img.shape[0]\n",
    "    \n",
    "    #find new (x1, y1, x2, y2) from using center and slope values and fitting to bottom of image and the specified height\n",
    "    x_right_lower = -(r_center[1] - line_bottom)/r_slope + r_center[0]\n",
    "    x_right_upper = -(r_center[1] - line_height)/r_slope + r_center[0]\n",
    "    \n",
    "    x_left_lower = -(l_center[1] - line_bottom)/l_slope + l_center[0]\n",
    "    x_left_upper = -(l_center[1] - line_height)/l_slope + l_center[0]\n",
    "    \n",
    "    if (x_right_lower > img.shape[1]):\n",
    "        x_right_lower = img.shape[1]\n",
    "        \n",
    "    if (x_left_lower < 0):\n",
    "        x_left_lower = 0\n",
    "    \n",
    "    \n",
    "    x_right_lower = int(round(x_right_lower))\n",
    "    x_right_upper = int(round(x_right_upper))\n",
    "    x_left_upper = int(round(x_left_upper))\n",
    "    x_left_lower = int(round(x_left_lower))                    \n",
    "    \n",
    "    cv2.line(img, (x_right_lower, line_bottom), (x_right_upper, line_height), color, thickness = 5)\n",
    "    cv2.line(img, (x_left_lower, line_bottom), (x_left_upper, line_height), color, thickness = 5)\n",
    "    \n",
    "     \n",
    "\n",
    "def hough_lines(img, rho, theta, threshold, min_line_len, max_line_gap):\n",
    "    \"\"\"\n",
    "    `img` should be the output of a Canny transform.\n",
    "        \n",
    "    Returns an image with hough lines drawn.\n",
    "    \"\"\"\n",
    "    lines = cv2.HoughLinesP(img, rho, theta, threshold, np.array([]), minLineLength=min_line_len, maxLineGap=max_line_gap)\n",
    "    line_img = np.zeros((img.shape[0], img.shape[1], 3), dtype=np.uint8)\n",
    "    draw_lines(line_img, lines)\n",
    "    return line_img\n",
    "\n",
    "# Python 3 has support for cool math symbols.\n",
    "\n",
    "def weighted_img(img, initial_img, α=0.8, β=1., γ=0.):\n",
    "    \"\"\"\n",
    "    `img` is the output of the hough_lines(), An image with lines drawn on it.\n",
    "    Should be a blank image (all black) with lines drawn on it.\n",
    "    \n",
    "    `initial_img` should be the image before any processing.\n",
    "    \n",
    "    The result image is computed as follows:\n",
    "    \n",
    "    initial_img * α + img * β + γ\n",
    "    NOTE: initial_img and img must be the same shape!\n",
    "    \"\"\"\n",
    "    return cv2.addWeighted(initial_img, α, img, β, γ)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Images\n",
    "\n",
    "Build your pipeline to work on the images in the directory \"test_images\"  \n",
    "**You should make sure your pipeline works well on these images before you try the videos.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['solidYellowCurve2.jpg',\n",
       " 'solidYellowLeft.jpg',\n",
       " 'solidYellowCurve.jpg',\n",
       " 'whiteCarLaneSwitch.jpg',\n",
       " 'solidWhiteCurve.jpg',\n",
       " 'solidWhiteRight.jpg']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "image_list = os.listdir(\"test_images/\")\n",
    "image_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build a Lane Finding Pipeline\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Build the pipeline and run your solution on all test_images. Make copies into the `test_images_output` directory, and you can use the images in your writeup report.\n",
    "\n",
    "Try tuning the various parameters, especially the low and high Canny thresholds as well as the Hough lines parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pipeline(image):\n",
    "    # TODO: Build your pipeline that will draw lane lines on the test_images\n",
    "    \n",
    "    ##Get x and y size of image\n",
    "    ysize = image.shape[0]\n",
    "    xsize = image.shape[1]\n",
    "\n",
    "    ##Define four sided polygon for mask edges image to operate o\n",
    "    #top_left = (xsize/7,ysize/2)\n",
    "    #top_right = (6*xsize/7, ysize/2)\n",
    "    #bottom_left = (xsize/7, ysize)\n",
    "    #bottom_right = (6*xsize/7, ysize)\n",
    "    apex = (500, 300)\n",
    "    #top_left = (0,0)\n",
    "    #top_right = (xsize,0)\n",
    "    bottom_left = (0, ysize)\n",
    "    bottom_right = (xsize, ysize)\n",
    "    vertices = np.array([[bottom_left, apex, bottom_right]], dtype=np.int32)\n",
    "\n",
    "    ##Perform color masking \n",
    "    #Define color selection criteria\n",
    "    red_threshold = 0\n",
    "    green_threshold = 120\n",
    "    blue_threshold = 120\n",
    "    rgb_threshold = [red_threshold, green_threshold, blue_threshold]\n",
    "\n",
    "    #Mask pixels below the threshold\n",
    "    color_thresholds = (image[:,:,0] < rgb_threshold[0]) | \\\n",
    "                        (image[:,:,1] < rgb_threshold[1]) | \\\n",
    "                        (image[:,:,2] < rgb_threshold[2])\n",
    "\n",
    "\n",
    "    #mask color section\n",
    "    color_select = np.copy(image)\n",
    "    color_select[color_thresholds] = [0, 0, 0]\n",
    "    masked_edges = region_of_interest(color_select, vertices)\n",
    "\n",
    "    ##Convert to grayscale\n",
    "    gray = grayscale(masked_edges)\n",
    "\n",
    "    ##Define kernel size for gaussian smoothing and blurring\n",
    "    kernel_size = 5 \n",
    "    blur_gray = gaussian_blur(gray, kernel_size)\n",
    "\n",
    "    ##define parameters for canny and run \n",
    "    low_threshold = 150\n",
    "    high_threshold = 230\n",
    "    edges = canny(blur_gray, low_threshold, high_threshold)\n",
    "\n",
    "    ##Define Hough transform parameters\n",
    "    rho = 1\n",
    "    theta = np.pi/180\n",
    "    threshold = 1\n",
    "    min_line_length = 5\n",
    "    max_line_gap = 1\n",
    "    lines = cv2.HoughLinesP(edges, rho, theta, threshold, \n",
    "                          np.array([]), min_line_length, max_line_gap)\n",
    "    img_copy = np.copy(image)\n",
    "    img_black = img_copy * 0\n",
    "    draw_edges(img_copy, lines)\n",
    "    draw_lines(img_black, lines)\n",
    "    \n",
    "    img_final = weighted_img(img_black, img_copy, 0.8, 0.4, 0)\n",
    "    return img_final\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4da9541eb8>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4da94dd898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "image = plt.imread(\"test_images/solidWhiteRight.jpg\")\n",
    "im_out = pipeline(image)\n",
    "plt.imshow(im_out)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test on Videos\n",
    "\n",
    "You know what's cooler than drawing lanes over images? Drawing lanes over video!\n",
    "\n",
    "We can test our solution on two provided videos:\n",
    "\n",
    "`solidWhiteRight.mp4`\n",
    "\n",
    "`solidYellowLeft.mp4`\n",
    "\n",
    "**Note: if you get an import error when you run the next cell, try changing your kernel (select the Kernel menu above --> Change Kernel). Still have problems? Try relaunching Jupyter Notebook from the terminal prompt. Also, consult the forums for more troubleshooting tips.**\n",
    "\n",
    "**If you get an error that looks like this:**\n",
    "```\n",
    "NeedDownloadError: Need ffmpeg exe. \n",
    "You can download it by calling: \n",
    "imageio.plugins.ffmpeg.download()\n",
    "```\n",
    "**Follow the instructions in the error message and check out [this forum post](https://discussions.udacity.com/t/project-error-of-test-on-videos/274082) for more troubleshooting tips across operating systems.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import everything needed to edit/save/watch video clips\n",
    "from moviepy.editor import VideoFileClip\n",
    "from IPython.display import HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_image(image):\n",
    "    # NOTE: The output you return should be a color image (3 channel) for processing video below\n",
    "    # TODO: put your pipeline here,\n",
    "    # you should return the final output (image where lines are drawn on lanes)\n",
    "    result = pipeline(image)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try the one with the solid white lane on the right first ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[MoviePy] >>>> Building video test_videos_output/solidWhiteRight.mp4\n",
      "[MoviePy] Writing video test_videos_output/solidWhiteRight.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[MoviePy] Done.\n",
      "[MoviePy] >>>> Video ready: test_videos_output/solidWhiteRight.mp4 \n",
      "\n",
      "CPU times: user 8.2 s, sys: 193 ms, total: 8.39 s\n",
      "Wall time: 9.54 s\n"
     ]
    }
   ],
   "source": [
    "white_output = 'test_videos_output/solidWhiteRight.mp4'\n",
    "clip1 = VideoFileClip(\"test_videos/solidWhiteRight.mp4\")\n",
    "white_clip = clip1.fl_image(process_image) \n",
    "%time white_clip.write_videofile(white_output, audio=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<video width=\"960\" height=\"540\" controls>\n",
       "  <source src=\"test_videos_output/solidWhiteRight.mp4\">\n",
       "</video>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTML(\"\"\"\n",
    "<video width=\"960\" height=\"540\" controls>\n",
    "  <source src=\"{0}\">\n",
    "</video>\n",
    "\"\"\".format(white_output))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Play the video inline, or if you prefer find the video in your filesystem (should be in the same directory) and play it in your video player of choice."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Improve the draw_lines() function\n",
    "\n",
    "**At this point, if you were successful with making the pipeline and tuning parameters, you probably have the Hough line segments drawn onto the road, but what about identifying the full extent of the lane and marking it clearly as in the example video (P1_example.mp4)?  Think about defining a line to run the full length of the visible lane based on the line segments you identified with the Hough Transform. As mentioned previously, try to average and/or extrapolate the line segments you've detected to map out the full extent of the lane lines. You can see an example of the result you're going for in the video \"P1_example.mp4\".**\n",
    "\n",
    "**Go back and modify your draw_lines function accordingly and try re-running your pipeline. The new output should draw a single, solid line over the left lane line and a single, solid line over the right lane line. The lines should start from the bottom of the image and extend out to the top of the region of interest.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now for the one with the solid yellow lane on the left. This one's more tricky!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[MoviePy] >>>> Building video test_videos_output/solidYellowLeft.mp4\n",
      "[MoviePy] Writing video test_videos_output/solidYellowLeft.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "\u001b[A"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[MoviePy] Done.\n",
      "[MoviePy] >>>> Video ready: test_videos_output/solidYellowLeft.mp4 \n",
      "\n",
      "CPU times: user 24.7 s, sys: 572 ms, total: 25.3 s\n",
      "Wall time: 24.4 s\n"
     ]
    }
   ],
   "source": [
    "yellow_output = 'test_videos_output/solidYellowLeft.mp4'\n",
    "## To speed up the testing process you may want to try your pipeline on a shorter subclip of the video\n",
    "## To do so add .subclip(start_second,end_second) to the end of the line below\n",
    "## Where start_second and end_second are integer values representing the start and end of the subclip\n",
    "## You may also uncomment the following line for a subclip of the first 5 seconds\n",
    "##clip2 = VideoFileClip('test_videos/solidYellowLeft.mp4').subclip(0,5)\n",
    "clip2 = VideoFileClip('test_videos/solidYellowLeft.mp4')\n",
    "yellow_clip = clip2.fl_image(process_image)\n",
    "%time yellow_clip.write_videofile(yellow_output, audio=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<video width=\"960\" height=\"540\" controls>\n",
       "  <source src=\"test_videos_output/solidYellowLeft.mp4\">\n",
       "</video>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTML(\"\"\"\n",
    "<video width=\"960\" height=\"540\" controls>\n",
    "  <source src=\"{0}\">\n",
    "</video>\n",
    "\"\"\".format(yellow_output))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Writeup and Submission\n",
    "\n",
    "If you're satisfied with your video outputs, it's time to make the report writeup in a pdf or markdown file. Once you have this Ipython notebook ready along with the writeup, it's time to submit for review! Here is a [link](https://github.com/udacity/CarND-LaneLines-P1/blob/master/writeup_template.md) to the writeup template file.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Optional Challenge\n",
    "\n",
    "Try your lane finding pipeline on the video below.  Does it still work?  Can you figure out a way to make it more robust?  If you're up for the challenge, modify your pipeline so it works with this video and submit it along with the rest of your project!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "challenge_output = 'test_videos_output/challenge.mp4'\n",
    "## To speed up the testing process you may want to try your pipeline on a shorter subclip of the video\n",
    "## To do so add .subclip(start_second,end_second) to the end of the line below\n",
    "## Where start_second and end_second are integer values representing the start and end of the subclip\n",
    "## You may also uncomment the following line for a subclip of the first 5 seconds\n",
    "##clip3 = VideoFileClip('test_videos/challenge.mp4').subclip(0,5)\n",
    "clip3 = VideoFileClip('test_videos/challenge.mp4')\n",
    "challenge_clip = clip3.fl_image(process_image)\n",
    "%time challenge_clip.write_videofile(challenge_output, audio=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HTML(\"\"\"\n",
    "<video width=\"960\" height=\"540\" controls>\n",
    "  <source src=\"{0}\">\n",
    "</video>\n",
    "\"\"\".format(challenge_output))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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