Monday, 29 June 2015

Stabilizing and slowing down videos

Those of us with a regular camera and no tripod are used to shaky videos. To fight this disease, we can use software to help stabilizing it. In my current system, Ubuntu 14.04, the software 'transcode' already has everything you need, and it is extremely easy to get it working. Assuming you have a shaky video, just issue the following two commands:

transcode -J stabilize -i ORIGINAL.MOV
transcode -J transform -i ORIGINAL.MOV -y xvid -o STABILIZED.MOV

The result can be pretty good. As a comparison, see below (left: original; right: after stabilizing).



Another nice thing to be able to do with videos is to slow them down in certain parts, but creating interpolated frames between the original ones to allow for smooth transition between frames. This can be accomplished with 'slowmoVideo'. The user interface allows you to select which parts you want faster or slower by changing the slope of the line describing the relative speed of the rendered video vs. the original one. As an example of how the GUI looks like:


And a demo of the resulting video, where we slow down the part from second 2 to 5 approximately (again left: original; right: modified video).

Thursday, 7 May 2015

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):




Thursday, 30 April 2015

Creating a virtual hiking tour

Lately I'm back to hiking and when I do a route I use my mobile phone with a GPS application (at the moment I use Wikiloc) to record the track. Last week I climbed Teide, and Wikiloc offers the possibility of easily embedding the data from their site, which is nice:



But you shouldn't stop there and you can also create a guided tour of the route. Doing it is quite simple, and I list below the steps I took to create the video tour of the Teide climb:

  • First, download the file from Wikiloc in KML format, and open it with Google Earth. Then, select the route and you can see an icon in the right part of the left panel that says "Play Tour" (play it a couple of times first to cache all the necessary images). Options to modify the speed, camera angles, etc. are available at Tools::Options::Touring.
  • Then, when we are ready, we just play it and at the same time record it with, for example, Kazam (30 FPS gives pretty good quality).
  • The resulting file is pretty big. To make it smaller we can use WinFF with output as MPEG-4 (very high quality). As an example, from 656MB this turns the file into 71MB, which can now be mildly edited with Kdenlive, and we render it all together for Web site::YouTube 1280x720. The resulting video is now 51MB, and we can upload it directly to YouTube: https://youtu.be/HgzXkAG7XjM 




Thursday, 12 February 2015

Classical guitar progress logging (Feb'15)

With many obvious mistakes... plenty to improve yet, but I want to move on... (This time I did found the webcam, but synchronizing audio and video is really tough sometimes...) :

Tuesday, 16 December 2014

Classical guitar progress logging (Dec'14)

After almost a year without playing the guitar. For this one, I couldn't find the webcam, so only audio, at SoundCloud:

Sunday, 1 December 2013

Introduction to Music Production (Coursera)

I just finished another course at Coursera: Introduction to Music Production by Loudon Stearns of Berklee College of Music.

The most demanding stuff from this course were the assignments, in which we had to create short lessons explaining some of the concepts that we learned each week. I went for the screencast mode of teaching, and these are the assignments for each week. Doing the assignments was hard work, but I learned a lot that way, and I hope I can take another music-related course from Coursera in the near future...

Week 1: Topic: "Typical recording signal flow using your own equipment"




Week 2: Topic: "Efficiently create a compile from multiple audio recordings in your DAW."



Week 3: Topic: "Submix practical: Demonstrate the configuration of a Submix in a DAW or physical mixing board and Parallel effects practical: Demonstrate the configuration of parallel effects in a DAW or physical mixing board."


Week 4: Topic: "Demonstrate how to use a specific compression plugin, including threshold, ratio, attack, and release. Describe what visuals the device has, including gain reduction meters, transfer functions, and gain reduction traces if any."



Week 5: Topic: "Demonstrate the delay spectrum with examples of comb filtering, creating pitches with delays, slapback delays, and synchronized long delays."



Week 6: Topic: "On a synthesizer of your choice demonstrate the usage of these controls: Oscillator waveform, oscillator frequency, filter type, filter frequency, filter resonance, and amplitude envelope ADSR. How are they similar and how are they different from the simple synthesizer used in the video demonstrations?"


Thursday, 14 November 2013

Classical guitar progress logging (Nov'13)

Soon I'll have a decent microphone, but for the moment another recording with the crappy one. This month a very nice piece by Julio Sagreras: "Maria Luisa: Mazurka".



Maria Luisa: Mazurka (by Julio Sagreras) from Angel de Vicente on Vimeo.


The video is here.