How to use Google Navigation and street view API and extract some features from a image

GoogleAPI.py

import urllib2;
import numpy as np;
import json;
from pyproj import Geod;

def decode_line(encoded):
    """copied from https://github.com/jconst/Byway-Server/blob/master/polyline.py
    """

    encoded_len = len(encoded)
    index = 0
    array = []
    lat = 0
    lng = 0

    while index < encoded_len:

        b = 0
        shift = 0
        result = 0

        while True:
            b = ord(encoded[index]) - 63
            index = index + 1
            result |= (b & 0x1f) << shift
            shift += 5
            if b < 0x20:
                break

        dlat = ~(result >> 1) if result & 1 else result >> 1
        lat += dlat

        shift = 0
        result = 0

        while True:
            b = ord(encoded[index]) - 63
            index = index + 1
            result |= (b & 0x1f) << shift
            shift += 5
            if b < 0x20:
                break

        dlng = ~(result >> 1) if result & 1 else result >> 1
        lng += dlng

        array.append((lat * 1e-5, lng * 1e-5))

    return array

# if __name__ == "__main__":
#     latlngs = decode_line("grkyHhpc@B[[_IYiLiEgj@a@q@yEoAGi@bEyH_@aHj@m@^qAB{@IkHi@cHcAkPSiMJqEj@s@CkFp@sDfB}Ex@iBj@S_AyIkCcUWgAaA_JUyAFk@{D_]~KiLwAeCsHqJmBlAmFuXe@{DcByIZIYiBxBwAc@eCcAl@y@aEdCcBVJpHsEyAeE")
#     for latlng in latlngs:
#         print str(latlng[0]) + "," + str(latlng[1])



def GSV_json(origin='kirby+state,Champaign,IL',destination='Illini+Union,Urbana,IL',gotype="driving"):
    api_key='AI';
    url_json='https://maps.googleapis.com/maps/api/directions/json?origin='+origin+'&destination='+destination+'&sensor=false&key='+api_key+'&mode='+gotype+'&alternatives=true';
    print url_json;

    req = urllib2.Request(url_json)
    f = urllib2.urlopen(req);
    content = f.read();
    response = json.loads(content)
    print len(response['routes'])
    all_alternative=[]
    for alternative in response['routes']:
        steps=alternative['legs'][0]['steps']

        allstepPoints=[];
        allDistance=[];
        for step in steps:
            ### parse the points from polyline
            step_distance=step['distance'];
            step_start=step['start_location'];
            step_end=step['end_location'];
            poly_encode=step['polyline']['points'];
            print poly_encode;
            coord_points=decode_line(poly_encode);

            print step_start;
            print step_end;
            # print coord_points;

            allstepPoints.append(coord_points);
            allDistance.append(step_distance);

        all_alternative.append(allstepPoints)

    # return allstepPoints;
    return all_alternative

def GSVimages(all_alternative,gotype="driving",direction=0):
    g = Geod(ellps='clrk66')
    nImage=1
    
    all_coords=[]

    for alt_index, allstepPoints in enumerate(all_alternative):
        coords=[]
        nImage=1
        for nleg,leg in enumerate(allstepPoints):
            num_points=len(leg);
            escape=0;
            print num_points;
            print "$$$$$$$$$$$$"
            for i in range(num_points-1):
                if escape==1:
                    continue;

                escape=0;
                currentLat=leg[i][0];
                currentLong=leg[i][1];

                coords.append([currentLat,currentLong])
                nextLat=leg[i+1][0];
                nextLong=leg[i+1][1];
                az12,az21,dist = g.inv(currentLong,currentLat,nextLong,nextLat); # Calculate the Azimuth between two points to find the road direction
                
                az12=az12+direction;

                if az12<0:
                    az12=360+az12;

                if dist<20: #if distance <20m
                    escape=0;

                # print currentLat,currentLong,dist,az12;
                url="http://maps.googleapis.com/maps/api/streetview?size=640x640&location="+str(currentLat)+","+str(currentLong)+"&sensor=True&key=AIzaSyt1FQgDQYNnPM&heading="+str(az12);
                req = urllib2.Request(url)
                f = urllib2.urlopen(req);
                content = f.read();
                # im=Image.open(StringIO(content))
                output = open("./test/"+gotype+"_"+str(alt_index)+"_"+str(nImage).zfill(3)+"_view.jpg",'wb')
                output.write(content)
                output.close()
                nImage+=1
            
        all_coords.append(coords)

    return all_coords

def saveCoords(all_coords,filename):
    with open(filename,"w") as outputfile:
        for coords in all_coords:
            for i in coords:    
                line=str(i[0])+","+str(i[1])+"\n";
                outputfile.write(line)

if __name__=="__main__":
    origin='76+E+University+Ave,Champaign,IL+61820'
    desti='801+W+Main+St,Urbana,IL+61801'
    alternative_routes=GSV_json(origin,desti,"driving");
    
    coords_driving=GSVimages(alternative_routes,"driving")
    # print coords_driving
    saveCoords(coords_driving,"driving_coords.txt")


    # allstepPoints=GSV_json(origin,desti,"walking");
    coords_walking=GSVimages(alternative_routes,"walking",90)
    saveCoords(coords_walking,"walking_coords.txt")

ImageFeatureExtraction.m

function [ FeatureCols ] = ExtractFeature( path,filename )
%UNTITLED2 Summary of this function goes here
%   Detailed explanation goes here
    param.imageSize = [256 256]; % it works also with non-square images (use the most common aspect ratio in your set)
    param.orientationsPerScale = [8 8 8 8]; % number of orientations per scale
    param.numberBlocks = 4;
    param.fc_prefilt = 4;
   
    img=imread([path filename]);
    label=-1;
    type=0;
	[gist,param]=LMgist(img,'',param);	% 1* 512

	im_hsv = rgb2hsv(img);
	im_hue = im_hsv(:,:,1); 
    im_sat=im_hsv(:,:,2);
    im_val=im_hsv(:,:,3);
    
    r=img(:,:,1);
    g=img(:,:,2);
    b=img(:,:,3);
    
    justGreen=g-r/2-b/2;
    bw=justGreen>10;
    greenness=sum(bw(:));
    
    subplot(1,2,1), subimage(img);
    subplot(1,2,2), subimage(bw);
    
    print ('-djpeg',[path 'green/' filename]);
%     imshow(bw)
%     imwrite(h,[path,'green' filename]);
    
	%- Hue Histogram
	hue_hist = imhist(im_hue);  %1 * 256
    sat_hist=imhist(im_sat);    %1 * 256
    val_hist=imhist(im_val);    %1 * 256
    
	%- Edge orientation Histogram
	edgeOH=edgeOrientationHistogram(rgb2gray(img)); % 16*5=80

	% Add features and add it to variable feature. Do remember to adjust the m values at the begining.
	
	%%%%

	FeatureCols = [type,label,greenness,gist,transpose(sat_hist),transpose(hue_hist),transpose(val_hist),reshape(edgeOH,1,[])];
end