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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Petra Duckietown - Mobile Robot Design Class - Assignment 3\n",
"\n",
"* Objective: this jupyter notebook is intended to evaluate how the students understand the Duckietown repo\n",
"\n",
"Credit to Prof. Nick Wang"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Instructions: \n",
"1. $ cp PetraDuckietown_Assignment3.ipynb PetraDuckietown_Assignment3-XXXXXXX.ipynb (XXXXXXX is your name) You also need to add your name, setup, and state the contributions in the setup and contributions section.\n",
"2. You can already see the desired outputs of each cell, and you need to find the relevant code in the Duckietown repo and reproduce the results.\n",
"3. Each student needs to submit one to your mentor, via email. Please do not commit your ipynb to github repo. Please do not modify the original file of NCTU's Duckietown assignment1.ipynb.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Steup and Conributions:\n",
"\n",
"This work is done by: YOUR NAME.\n",
"\n",
"You need to state your contribution here. What's your working environment (e.g., VirtualBox XXX version on Window XX). If you get some help from your TA or classmates, you need to describe here."
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Line Detector"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.Load the image and resize"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
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6pbccVQxmYBaumHH9GWMiZeOJcwJ1xpg1vKAUM6ysWWtjGDAPRr7cvP4Ya8nG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jG0A1GkqRrBab0hTWPQitEKbC/JT0eybEZeHPnw4T15UWH8mKfHR25uL1ivG0Yr2e1ypBy5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\nzjrrrLPO+hnofwKRgKLyRuzNkwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1384682c50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import cv2\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"\n",
"#Use your own image\n",
"img = cv2.imread(\"images/curve-right.jpg\")\n",
"\n",
"image_cv = cv2.resize(img, (160, 120),interpolation=cv2.INTER_NEAREST)\n",
"\n",
"dst1 = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)\n",
"plt.subplot(121),plt.imshow(dst1,cmap = 'brg')\n",
"plt.title('Original Image'), plt.xticks([]), plt.yticks([])\n",
"\n",
"dst2 = cv2.cvtColor(image_cv,cv2.COLOR_BGR2RGB)\n",
"plt.subplot(122),plt.imshow(dst2,cmap = 'brg')\n",
"plt.title('Resized Image'), plt.xticks([]), plt.yticks([])\n",
"\n",
"plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2.Find the edge (15%)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'edges' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-4-5f392b0edb6e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 7\u001b[0m '''\n\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medges\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcmap\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'gray'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Edge Image'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxticks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0myticks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: name 'edges' is not defined"
]
}
],
"source": [
"\n",
"'''\n",
"#You should find the config file 'universal.yaml'\n",
"#You code this\n",
"gray = ???\n",
"edges = ???\n",
"'''\n",
"\n",
"plt.imshow(edges,cmap = 'gray')\n",
"plt.title('Edge Image'), plt.xticks([]), plt.yticks([])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3-1.Setup HSV space threshold (15%)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"'''\n",
"#You should find the config file 'universal.yaml'\n",
"hsv_white1 = ???\n",
"hsv_white2 = ???\n",
"hsv_yellow1 = ???\n",
"hsv_yellow2 = ???\n",
"hsv_red1 = ???\n",
"hsv_red2 = ???\n",
"hsv_red3 = ???\n",
"hsv_red4 = ???\n",
"'''"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3-2.Threshold colors in HSV space (15%)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"'''\n",
"#change color space to HSV\n",
"hsv = ???\n",
"\n",
"find the color\n",
"white = ???\n",
"kernel = ???\n",
"white = ???\n",
"\n",
"yellow = ???\n",
"kernel = ???\n",
"yellow = ???\n",
"\n",
"red1 = ???\n",
"red2 = ???\n",
"red = ???\n",
"kernel = ???\n",
"red = ???\n",
"'''\n",
"# Uncomment '#' to plot with color\n",
"#x = cv2.cvtColor(yellow, cv2.COLOR_GRAY2BGR)\n",
"#x[:,:,2] *= 1\n",
"#x[:,:,1] *= 1\n",
"#x[:,:,0] *= 0\n",
"#x = cv2.cvtColor(x, cv2.COLOR_BGR2RGB)\n",
"\n",
"#y = cv2.cvtColor(red, cv2.COLOR_GRAY2BGR)\n",
"#y[:,:,2] *= 1\n",
"#y[:,:,1] *= 0\n",
"#y[:,:,0] *= 0\n",
"#y = cv2.cvtColor(y, cv2.COLOR_BGR2RGB)\n",
"\n",
"plt.subplot(131),plt.imshow(white,cmap = 'gray')\n",
"plt.title('White'), plt.xticks([]), plt.yticks([])\n",
"\n",
"plt.subplot(132),plt.imshow(yellow,cmap = 'gray')\n",
"#plt.subplot(132),plt.imshow(x,cmap = 'brg')\n",
"plt.title('Yellow'), plt.xticks([]), plt.yticks([])\n",
"\n",
"plt.subplot(133),plt.imshow(red,cmap = 'gray')\n",
"#plt.subplot(133),plt.imshow(y,cmap = 'brg')\n",
"plt.title('Red'), plt.xticks([]), plt.yticks([])\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 4.Combine Edge and Colors (15%)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"'''\n",
"edge_color_white = ???\n",
"edge_color_yellow = ???\n",
"edge_color_red = ???\n",
"'''\n",
"\n",
"plt.imshow(edge_color_yellow,cmap = 'gray')\n",
"plt.title('Edge Color Y'), plt.xticks([]), plt.yticks([])\n",
"#plt.subplot(131),plt.imshow(edge_color_white,cmap = 'gray')\n",
"#plt.title('Edge Color W'), plt.xticks([]), plt.yticks([])\n",
"#plt.subplot(132),plt.imshow(edge_color_yellow,cmap = 'gray')\n",
"#plt.title('Edge Color Y'), plt.xticks([]), plt.yticks([])\n",
"#plt.subplot(133),plt.imshow(edge_color_red,cmap = 'gray')\n",
"#plt.title('Edge Color R'), plt.xticks([]), plt.yticks([])\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 5-1.Find the lines (15%)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"'''\n",
"#default threshold 20-> 10\n",
"lines_white = ???\n",
"lines_yellow = ???\n",
"lines_red = ???\n",
"'''\n",
"\n",
"color = \"yellow\"\n",
"lines = lines_yellow\n",
"bw = yellow\n",
"\n",
"if lines is not None:\n",
" lines = np.array(lines[0])\n",
" print \"found lines\"\n",
"\n",
"else:\n",
" lines = []\n",
" print \"no lines\"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Show the lines (yellow)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"image_with_lines = np.copy(dst2)\n",
"if len(lines)>0:\n",
" for x1,y1,x2,y2 in lines:\n",
" cv2.line(image_with_lines, (x1,y1), (x2,y2), (0,0,255), 2)\n",
" cv2.circle(image_with_lines, (x1,y1), 2, (0,255,0))\n",
" cv2.circle(image_with_lines, (x2,y2), 2, (255,0,0))\n",
" \n",
"plt.imshow(image_with_lines,cmap = 'brg')\n",
"plt.title('Line Image'), plt.xticks([]), plt.yticks([])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 6-1.Normals (15%)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"arr_cutoff = np.array((0, 40, 0, 40))\n",
"arr_ratio = np.array((1./160, 1./120, 1./160, 1./120))\n",
" \n",
"normals = []\n",
"centers = []\n",
"if len(lines)>0:\n",
" \n",
" #find the normalized coordinates\n",
" lines_normalized = ((lines + arr_cutoff) * arr_ratio)\n",
"'''\n",
" #find the dx dy\n",
" length = ???\n",
" dx = ???\n",
" dy = ???\n",
"\n",
" #find the center point\n",
" centers = ???\n",
"'''\n",
" #find the vectors' direction\n",
" x3 = (centers[:,0:1] - 3.*dx).astype('int')\n",
" x3[x3<0]=0\n",
" x3[x3>=160]=160-1\n",
"\n",
" y3 = (centers[:,1:2] - 3.*dy).astype('int')\n",
" y3[y3<0]=0\n",
" y3[y3>=120]=120-1\n",
"\n",
" x4 = (centers[:,0:1] + 3.*dx).astype('int')\n",
" x4[x4<0]=0\n",
" x4[x4>=160]=160-1\n",
"\n",
" y4 = (centers[:,1:2] + 3.*dy).astype('int')\n",
" y4[y4<0]=0\n",
" y4[y4>=120]=120-1\n",
" \n",
"''' \n",
" #find the dx dy direction\n",
" flag_signs = ???\n",
" normals = np.hstack([dx, dy]) * flag_signs\n",
"'''\n",
" \n",
" flag = ((lines[:,2]-lines[:,0])*normals[:,1] - (lines[:,3]-lines[:,1])*normals[:,0])>0\n",
" for i in range(len(lines)):\n",
" if flag[i]:\n",
" x1,y1,x2,y2 = lines[i, :]\n",
" lines[i, :] = [x2,y2,x1,y1]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 6-2.Draw the Normals "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"image_with_lines = np.copy(dst2)\n",
"if len(centers)>0:\n",
" for x,y,dx,dy in np.hstack((centers,normals)):\n",
" x3 = int(x - 2.*dx)\n",
" y3 = int(y - 2.*dy)\n",
" x4 = int(x + 2.*dx)\n",
" y4 = int(y + 2.*dy)\n",
" cv2.line(image_with_lines, (x3,y3), (x4,y4), (0,0,255), 1)\n",
" cv2.circle(image_with_lines, (x3,y3), 1, (0,255,0))\n",
" cv2.circle(image_with_lines, (x4,y4), 1, (255,0,0))\n",
" \n",
"plt.subplot(121),plt.imshow(image_with_lines,cmap = 'brg')\n",
"plt.title('Line Normals'), plt.xticks([]), plt.yticks([])\n",
"\n",
"image_with_lines = np.copy(dst2)\n",
"if len(lines)>0:\n",
" for x1,y1,x2,y2 in lines:\n",
" cv2.line(image_with_lines, (x1,y1), (x2,y2), (0,0,255), 2)\n",
" cv2.circle(image_with_lines, (x1,y1), 2, (0,255,0))\n",
" cv2.circle(image_with_lines, (x2,y2), 2, (255,0,0))\n",
" \n",
"plt.subplot(122),plt.imshow(image_with_lines,cmap = 'brg')\n",
"plt.title('Line Image'), plt.xticks([]), plt.yticks([])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 7-1.setup the segment class"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"class Vector2D():\n",
" def __init__(self):\n",
" self.x = 0\n",
" self.y = 0 \n",
"class Segment():\n",
" def __init__(self):\n",
" self.color = \"\"\n",
" self.pixels_normalized = np.array([Vector2D(),Vector2D()])\n",
" self.normal = Vector2D()\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 7-2.Store in the SegmentList "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"segmentMsgList = []\n",
"\n",
"for x1,y1,x2,y2,norm_x,norm_y in np.hstack((lines_normalized,normals)):\n",
" segment = Segment()\n",
" segment.color = color\n",
" segment.pixels_normalized[0].x = x1\n",
" segment.pixels_normalized[0].y = y1\n",
" segment.pixels_normalized[1].x = x2\n",
" segment.pixels_normalized[1].y = y2\n",
" segment.normal.x = norm_x\n",
" segment.normal.y = norm_y\n",
"\n",
" segmentMsgList.append(segment) \n",
" \n",
"#print segmentMsgList[2].pixels_normalized[1].x"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 7.3 Print the SegmentList"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"for i in segmentMsgList:\n",
" print (i.pixels_normalized[0].x,i.pixels_normalized[0].y),(i.pixels_normalized[1].x,i.pixels_normalized[1].y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Ground Projection "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"lines_normalized, normals\n",
"\n",
"\n",
"print lines_normalized[0,1],normals[0]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### camera parameters\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import cv2\n",
"import numpy as np\n",
"#camera_matrix = np.array([[1.3e+03, 0., 6.0e+02], [0., 1.3e+03, 4.8e+02], [0., 0., 1.]], dtype=np.float32)\n",
"#dist_coeffs = np.array([-2.4-01, 9.5e-02, -4.0e-04, 8.9e-05, 0.], dtype=np.float32)\n",
"\n",
"#Use your own homography & intrinsic camera_matrix and dist_coeffs\n",
"homography = np.array([[5.505818e-06, -0.0001388593, -0.2362917], [0.001106475, -3.803936e-05, -0.3573611], [-3.200042e-06, -0.009038727, 1]]\n",
")\n",
"matrix = np.array([[316.52597444317314, 0.0, 320.9948809392584], [0.0, 321.2731572848207, 205.92052874401818],\n",
" [0.0, 0.0, 1.0]])\n",
"coeffs = np.array([-0.2601671987836283, 0.04662981063335094, 0.005020360395041378, 0.0029019828987683857,\n",
" 0.0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"pt_img = np.array([[0.5*640],[0.7*480],[1.]])\n",
"#print pt_img\n",
"G = np.dot(homography,pt_img)\n",
"G/=G[2]\n",
"print G\n",
"\n",
"pt_img = np.array([[[0.5*640,0.7*480]]])\n",
"\n",
"xy_undistorted = cv2.undistortPoints(pt_img, matrix, coeffs,R=None, P=matrix)\n",
"pt_img = np.array([[xy_undistorted[0][0][0]],[xy_undistorted[0][0][1]],[1.]])\n",
"#print xy_undistorted\n",
"G_rect = np.dot(homography,pt_img)\n",
"G_rect/=G_rect[2]\n",
"print G_rect"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Rectify the image (15%) "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from matplotlib import pyplot as plt\n",
"#Use your own image\n",
"origin = cv2.imread(\"images/curve-right.jpg\")\n",
"\n",
"'''\n",
"#rectfy the image by opencv 'undistort'\n",
"rec_img = ???\n",
"'''\n",
"\n",
"origin = cv2.cvtColor(origin,cv2.COLOR_BGR2RGB)\n",
"plt.subplot(121),plt.imshow(origin,cmap = 'brg')\n",
"plt.title('Original Image'), plt.xticks([]), plt.yticks([])\n",
"\n",
"rec_img = cv2.cvtColor(rec_img,cv2.COLOR_BGR2RGB)\n",
"plt.subplot(122),plt.imshow(rec_img,cmap = 'brg')\n",
"plt.title('Rectified Image'), plt.xticks([]), plt.yticks([])\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Duckietown Lane Filter"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"up/down arrow keys to move, enter to edit\n",
"\n",
"Esc to exit edit mode\n",
"\n",
"Shift + enter to run code\n",
"\n",
"1/2/3... to add comment\n",
"\n",
"dd to delete cell\n",
"\n",
"press h for more shortcuts"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"from scipy.stats import multivariate_normal, entropy\n",
"from scipy.ndimage.filters import gaussian_filter\n",
"from math import floor, atan2, pi, cos, sin, sqrt\n",
"import time\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Environment Setup"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# constant\n",
"WHITE = 0\n",
"YELLOW = 1\n",
"RED = 2\n",
"\n",
"lanewidth = 0.4\n",
"linewidth_white = 0.04\n",
"linewidth_yellow = 0.02\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Generate Vote (Extra Credit 10% for generating multiple votes from all detected segments)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Setup a line segment\n",
"* left edge of white lane\n",
"* right edge of white lane\n",
"* left edge of yellow lane\n",
"* right edge of white lane"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"# right edge of white lane\n",
"#p1 = np.array([0.8, 0.24])\n",
"#p2 = np.array([0.4, 0.24])\n",
"p1 = np.array([lines_normalized[0][0],lines_normalized[0][1]])\n",
"p2 = np.array([lines_normalized[0][2],lines_normalized[0][3]]) \n",
"seg_color = YELLOW\n",
"\n",
"# left edge of white lane\n",
"#p1 = np.array([0.4, 0.2])\n",
"#p2 = np.array([0.8, 0.2])\n",
"#seg_color = WHITE\n",
"\n",
"#plt.plot([p1[0], p2[0]], [p1[1], p2[1]], 'ro')\n",
"#plt.plot([p1[0], p2[0]], [p1[1], p2[1]])\n",
"#plt.ylabel('y')\n",
"#plt.axis([0, 5, 0, 5])\n",
"#plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### compute d_i, phi_i, l_i"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"\n",
"t_hat = (p2-p1)/np.linalg.norm(p2-p1)\n",
"n_hat = np.array([-t_hat[1],t_hat[0]])\n",
"d1 = np.inner(n_hat,p1)\n",
"d2 = np.inner(n_hat,p2)\n",
"l1 = np.inner(t_hat,p1)\n",
"l2 = np.inner(t_hat,p2)\n",
"\n",
"print (d1, d2, l1, l2)\n",
"\n",
"if (l1 < 0):\n",
" l1 = -l1;\n",
"if (l2 < 0):\n",
" l2 = -l2;\n",
"l_i = (l1+l2)/2\n",
"d_i = (d1+d2)/2\n",
"phi_i = np.arcsin(t_hat[1])\n",
"if seg_color == WHITE: # right lane is white\n",
" if(p1[0] > p2[0]): # right edge of white lane\n",
" d_i = d_i - linewidth_white\n",
" print ('right edge of white lane')\n",
" else: # left edge of white lane\n",
" d_i = - d_i\n",
" phi_i = -phi_i\n",
" print ('left edge of white lane')\n",
" d_i = d_i - lanewidth/2\n",
"\n",
"elif seg_color == YELLOW: # left lane is yellow\n",
" if (p2[0] > p1[0]): # left edge of yellow lane\n",
" d_i = d_i - linewidth_yellow\n",
" phi_i = -phi_i\n",
" print ('right edge of yellow lane')\n",
" else: # right edge of white lane\n",
" d_i = -d_i\n",
" print ('right edge of yellow lane')\n",
" d_i = lanewidth/2 - d_i\n",
"\n",
" \n",
"print (d_i, phi_i, l_i) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Measurement Likelihood"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# initialize measurement likelihood\n",
"\n",
"d_min = -0.7\n",
"d_max = 0.5\n",
"delta_d = 0.02\n",
"phi_min = -pi/2\n",
"phi_max = pi/2\n",
"delta_phi = 0.02\n",
"d, phi = np.mgrid[d_min:d_max:delta_d, phi_min:phi_max:delta_phi]\n",
"\n",
"measurement_likelihood = np.zeros(d.shape)\n",
"\n",
"fig = plt.figure()\n",
"ax = fig.add_subplot(111)\n",
"cax = ax.matshow(measurement_likelihood, interpolation='nearest')\n",
"fig.colorbar(cax)\n",
"plt.ylabel('phi')\n",
"plt.xlabel('d')\n",
"#ax.set_xticklabels(['']+alpha)\n",
"#ax.set_yticklabels(['']+alpha)\n",
"plt.show()\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"i = floor((d_i - d_min)/delta_d)\n",
"j = floor((phi_i - phi_min)/delta_phi)\n",
"measurement_likelihood[i,j] = measurement_likelihood[i,j] + 1/(l_i)\n",
"\n",
"print (i, j)\n",
"\n",
"fig = plt.figure()\n",
"ax = fig.add_subplot(111)\n",
"cax = ax.matshow(measurement_likelihood, interpolation='nearest')\n",
"fig.colorbar(cax)\n",
"plt.ylabel('phi')\n",
"plt.xlabel('d')\n",
"#ax.set_xticklabels(['']+alpha)\n",
"#ax.set_yticklabels(['']+alpha)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## Bayes' Filter (Extra Credit 10% for integrating Bayes' filter for multiple votes)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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