GPX hyperlapse

In the last post I described how to create a virtual hiking tour (http://angel-de-vicente.blogspot.com.es/2015/04/creating-visual-tour-of-hiking-tour.html), and then I wondered if I could do something similar, but at street level, taking images from Google Street View. The goal was to take GPS data (either from a route that I have followed myself on foot, on bike, etc. or from data points generated by the driving directions of Google maps).

If we want driving directions from Google Maps, one easy way to generate GPS data points in a .GPX file is to:

• use google maps to generate a route

• grab the URL generated above in Google Maps and feed it to GPS Visualizer to get a .gpx file with the GPS data points following the given route

If, instead, we want GPS points from a route that we did previously, we can just, for example, download the GPX file directly from Endomondo.

At these point, we can try our luck with sites like http://gpxhyperlapse.com/ or http://alban.atchoum.fr/hyperlapse/ but if we want finer control, we will need to do some extra work.

If we use the .gpx files above, the results will not be very good, since there will be not many data points and/or due to the GPS receiver limitations, the points can be outside roads, resulting in shaky and jumpy street view images. So, we can do two things to improve this.

First, we are going to generate more data points by interpolating, with GPSbabel  (see http://www.gpsbabel.org/htmldoc-development/filter_interpolate.html) For example, to get data points every 5 meters:

gpsbael -i gpx -f track.gpx -x interpolate,distance=0.005k -o gpx -F newtrack.gpx

Second, we can try to fit those GPS points to a proper road (assuming we were on a bike tour, running, etc. on roads). To do this, we can use the site https://mapmatching.3scale.net/. You need to apply for an API key. Once you do that, we can convert our original shaky GPS data with

curl -X POST -H 'Content-Type: application/gpx+xml' --data-binary @newtrack.gpx "http://test.roadmatching.com/rest/mapmatch/?app_id=YOUR_APP_ID&app_key=YOUR_APP_KEY&output.waypoints=true" -o output.xml 

This works OK with the GPX file from Endomondo, which has time stamps, but it will break (the developer knows about this, so perhaps it is fixed when you try it) for the Google Maps generated GPX file, which doesn't have time stamps. To fix it, we just have to add timestamps to the GPX file before accessing test.roadmatching.com. So I turn all the trkpt from something like:

to something like (you can just put the same timestamp for all the trkpt's):

The output from TrackMatching matches the roads much better, hopefully, than the original GPX data, but it comes in an unfamiliar format that I have not been able to convert easily to a GPX file (if you know how to do it with some GPS conversion software, please let me know). I was too lazy to write a script to do the necessary transformations automatically, and instead I used search/replace in my text editor, so that from the output.xml file I extract all the wpt ....="" stuff and modify each waypoint of the form wpt y="28.465961" x="-16.269638" to (if you don't know how to do search/replace with regular expressions, this is a good time to learn!):

Now in the .gpx file obtained with GPSBabel, delete all the trkpt entries (so there will be an empty section, and in their place put all these new trkpt definitions.

With the help of GPS Visualizer again, you can verify that the new .gpx file is matched to roads better than the original one. Just use the options to convert a .gpx file to Google Maps as follows:

As an example, this is how the track looks like with the .gpx file directly downloaded from Endomondo:

And this after massaged by TrackMatching:

Now that we have .gpx files with many data points and nicely following roads, it is time to get the Google Street View images to put everything together. The code I used is a minimal variation of the code available at http://pastebin.com/FnsY8QFR (discovered at http://www.cyclechat.net/threads/my-cycling-video-c-o-python-strava-google.135566/). In case the pastebin expires, I uploaded the code to GitHub (https://gist.github.com/cac3a4434c4bd5b756ea.git). You can download it with:

git clone https://gist.github.com/cac3a4434c4bd5b756ea.git


The file gpxhyper.py is still very crude, so you will have to change things by hand. It will work by default on a file called input.gpx (either change that or make a symbolic link named input.gpx pointing to the file you want to work with). Next, leave uncommented the appropriate line: for the .gpx file coming from Endomondo:

gpx_trackseg = gpx_file.getroot()[1][3] # For Endomondo .gpx

For the .gpx file coming from Google Maps:

gpx_trackseg = gpx_file.getroot()[3][1] # For GPSBABEL .gpx

You should also have a Google Street View Image API Key (if you don't have one, you can get instructions at https://developers.google.com/maps/documentation/streetview/#api_key). Put it in gpxhyper.py (in place of YOUR_GOOGLE_API_KEY) and execute it as:

python gpxhyper.py

and all the corresponding images will be downloaded from Google Street View.

From these images use your favourite method to create a video. For example:

avconv -r 10 -i %5d.jpeg -b:v 1000k input.mp4

(Downloading the images takes a while, so make sure you calculate the appropriate rates beforehand. I found that around 10 FPS is a good number above (the images are taken at intervals, and if you try a normal video rate of 24FPS, the video will be too shaky). Assuming the 5 meters interval given to GPSBabel above, this will mean a virtual speed of 50 m/s or 180 km/h. Depending on the effect you want to create and the place where the images are taken (for example a city vs. a very open road with nothing near), this might be too fast or too slow. You will have to experiment a bit).

As an example, here it is the result for an Endomondo generated track (a bicycle route):




And here for a .gpx file generated via Google Maps as explained above (for this one, at the beginning there were some 'bad' frames that I removed by hand with Kdenlive video editor):