Won Pound by Won Pound is released!

This post is one in a series about GANce

Close-readers, twitter-followers and corporeal-comrades will have already beheld the good news that Won Pound by Won Pound has been released! This is Won’s second album-length project (first of course being Post Space released in 2018), and graces listener’s ears courtesy of Minaret Records, a California jazz label.

The record is accompanied by an album-length music video synthesized with GANce, containing a completely unique video for each track. These 93960 frames have been the ultimate goal of this project since it’s inception, and serve as the best demonstration as to what GANce can do. Within the video (linked below), the video for ‘buzzz’ is a personal favorite, demonstrating the three core elements of a projection file blend:

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GANce Overlays

This post is one in a series about GANce

As it stood, the three main features that would comprise the upcoming collaboration with Won Pound (slated for release mid-April) were:

  • Projection Files (using a styleGAN2 network to project each of the individual frames in a source video, resulting in a series of latent vectors that can be manipulated and fed back into the network to create synthetic videos)
  • Audio Blending (using alpha compositing to combine a frequency domain representation of an audio signal with a series of projected vectors)
  • Network Switching (feeding the same latent vector into multiple networks produced in the same training run, resulting in visually similar results)

As detailed in the previous post. The effect of these three features can be seen in this demo:

 

Knowing we had enough runway to add another large feature to the project, and feeling particularly inspired following a visit to Clifford Ross’ exhibit at the Portland Museum of Art, I began exploring the relationship between the projection source video and the output images synthesized by the network.

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High performance GPU cooler for the NVIDIA Tesla K80

The “forthcoming” project mentioned throughout this post has been released! Check it out here.

Here’s a (long winded) video overview of this project:

Background

Rendered desperate for VRAM by a forthcoming stylegan-related project, I recently had to wade thermistor first into the concernedly hot and strange world of GPUs without video outputs to design a high performance cooler for the NVIDIA Tesla K80.

Too esoteric to game on, and too power hungry to mine cryptocurrencies with, the K80 (allegedly the ‘The World’s Most Popular GPU’) can be had for under $250 USD on ebay, a far cry from it’s imperial MSRP of $5000. By my math, the card is one of the most cost-efficient ways to avail one’s self of video ram by the dozen of gigabytes.

This sounds great on paper, but actually getting one of these configured to do useful work is a kind of a project in, and of itself. I’ll eventually get to this in the aforementioned upcoming post. Today’s topic however, is upstream of all that: the task of keeping these things cool.

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Quickly drawing grids of rectangles, and updating their colors with VisPy

Here’s a demo run of the code:

Background

From the VisPy website:

VisPy is a Python library for interactive scientific visualization that is designed to be fast, scalable, and easy to use.

While looking for a near real time data visualization alternative to the venerable matplotlib, I came across this jaw dropping demo:

Absolutely insane, achieving that kind of performance in python is amazing to say the least. This demo in particular seems like it would be more likely to come from a pygame application at the least, but looks more like it would be a Unity project.

The VisPy project is massive, but luckily, there is a set of really good examples included in the repo. Reminds me of the Arduino standard library in this way. After through all of running these, I didn’t find exactly what I was looking for.

For how simple the finished product looks, the learning curve on the way there was surprisingly steep. Hopefully this post saves you some time.

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How to host private Python packages on Bitbucket for free, AND how to use them in a circleci pipeline

Bitbucket is great for hosting private git repos. Turns out, it can also be used to turn those repos into python packages that you can integrate into your projects with pip. This took a bit of trial and effort to make happen, let me know if there is anything additional you had to do to get things working on your end and I can add them to the guide.

Background

This whole process is built on pip’s ability to install packages from common VCS’s using SSH keys for access credentials. The syntax for doing that looks like this:

Pretty slick, you can even specify a branch or tag:

Since this repo is public, let’s try installing the package into a python virtual environment:

No dice. It didn’t work because our development environment isn’t configured correctly. Let’s get started with the guide.

Using private repo packages locally

Note: I’m on ubuntu 18.04, but I will leave Windows notes in each step if applicable.

Step 1: Make sure your repo CAN be installed as a python package

The key here is a proper setup.py file. Here are best the best set of docs I’ve found on how to make this file.
You can also look at the test repo for this project (https://bitbucket.org/esologic/sample_project/src/master/), it contains an example setup.py. This repo will also be the standard example for this post.
To make sure things are working correctly, you can try installing the package into your local python environment, or into a virtual one like I’m doing. Using sample_project as an example, we can do this like so:

If your package behaves as expected when installed like this locally, you’re all set to push the changes to your bitbucket repo and continue with the rest of the guide.

Step 2: Create SSH keys and add them to bitbucket

Note: at a few places in this step I use my own email as a reference, dev@esologic.com. Make sure whenever you see that, to substitute email address associated with your bitbucket account.
If you already have ssh keys created on your computer or whatever you’re developing on, they should be located at ~/.ssh. If you don’t see both id_rsa and id_rsa.pub files in that directory, create them with:

Leave passphrase blank.
Now, copy the contents of ~/.ssh/id_rsa.pub to bitbucket. The following images should walk you through the steps, make sure to give the key a memorable name.
Now, the ssh key of whatever dev environment you’re on is added to bitbucket.

Windows steps to create ssh keys

I followed these two (1, 2) guides to create ssh keys on windows.
The short version goes something like this:

Then follow the step above to add the keys to your bitbucket account.

Step 3: Make sure your account can read from the private repo with your python package

This is a simple, but a trap for young players. Make sure the account you’re trying to install the module with has at least read settings on the repo.

Since the Devon account is an owner of the repo, it will be allowed to read from the repo. The account ci_bot will also be able to read from the repo because it has read permissions.

Step 4: Install the package from bitbucket

With the bitbucket repo permissions set, and your SSH key added to your bitbucket account, you should be able to re-run the installation command from earlier and use the package.

Fantastic! Remember, your pip command git+ssh://git@bitbucket.org/esologic/sample_project.git will be different for your package. It will look something like this: git+ssh://git@bitbucket.org/{your username}/{your project}.git.

Any user that you give read permissions to on the repo will be able to install your package as well. This includes a machine user, so your CI builds can use your private package as well, which I’ll show you how to do next.

Using private repo packages in circleci

Bitbucket and circleci go together like peanut butter and chocolate. Adding CI to a bitbucket project is made fast and easy using circleci.

Step 5: Create a “machine user” in bitbucket

This user should have read only access to the package repo that you want to add to ci, so in this example it’s the sample_project repo.
You can accomplish this very easy through the BB ui, just make sure to keep track of whatever username and password you decide on.
Just to be clear, a machine user is just a regular bitbucket user that is only used by machines.

Step 6: Create SSH keys and add them to your machine user’s account

On whatever you system you have been using so far, enter the following commands and remember to leave passphrase blank.

Add the contents of ~/.ssh/ci_bot_keys/id_rsa.pub to bitbucket while signed in as your machine user like we did in step 2.

Step 7: Try git+ssh key insertion locally

(Note: you can skip this step, but if things don’t work when you add the step to your CI build start looking for errors here.)

By setting the environment variable GIT_SSH_COMMAND you can select which SSH key gets used by pip when doing an ssh pull.
Let’s try out the concept, and try out our new key locally. Run these two commands:

And then install your project like you did before. The package should install no problem, and you should see the same output as step 4.

Step 8: Set the $KEY environment variable in circleci

We now want to make the private key we made for our ci bot (~/.ssh/ci_bot_keys/id_rsa) available to the circle build process.
The only tricky part here is that the private key will contain newlines. For simplicity, we can replace them with underscores, and add the newlines back in the circle build.
Copy the output of this command to your clipboard:

The output ends after -----END RSA PRIVATE KEY-----_ in case your terminal doesn’t wrap correctly.
Now we need to set this value to the env var $KEY in the circleci build that we are trying to use our private package (sample_project) in.
Click the gear on the project page for your project in circle. For me, this brought me to https://circleci.com/bb/esologic/crossbow/edit, where crossbow is the name of my project.
Go to build settings -> Environment Variables and then set the variable like so:

Now that the variable is set, we need to change our circle config to use it.

Step 9: Add the step to your /.circleci/config.yml file

This does the same thing that we just tried locally, but in circle.

You have to make sure that the export GIT_SSH_COMMAND step happens in the same step as any pip commands. Your full  dependencies  installation circle step may look something like this:

Make sure you select a circle image that has a git version of 2.17.0 or later, or this step will fail without an explanation. I found that the python image of circleci/python:3.7-buster worked when testing.

Try running your job, with this step added, it should be able to pull the package from your private repo. Let me know if you run into issues and I can try to help you out. Maybe donate the money you saved on hosting fees to me via paypal? 🤷💖

Thanks to

  • http://redgreenrepeat.com/2018/05/25/specifying-different-ssh-key-for-git/

Play multiple sound files on multiple output devices with Python and sounddevice

Ever wanted to have multiple different sound files playing on different output devices attached to a host computer? Say you’re writing a DJing application where you want one mix for headphones and one for the speakers. Or you’re doing some sort of kiosk or art installation where you have many sets of speakers that need to all be playing their own sound file but the whole thing needs to be synchronized. This would even be cool for something like an escape room.

The ladder example is where I needed this bit of code. I’ve been working with interdisciplinary artist Sara Dittrich on a few projects recently and she asked if I could come up with a way to play 8 different mono sound files on 8 different loudspeakers. Here’s a video of the whole setup in action, and an explanation of the project:

I’ve wrapped up all of the code for the art installation project, and that can be found in a github repo here. It includes the startup functionality etc. If you’re interested in recreating the video above, that repo would be a good starting place. The following is a list of the parts used to make that build happen:

Multi-Audio Example

It is worth it to give a simple example of how to play multiple files on multiple audio devices using python. I couldn’t find an examples on how to do this online and had to spend some time experimenting to make it all come together. Hopefully this saves you the trouble.

To install sounddevice on my Raspberry Pi, I had to run the following commands:

For this example, let’s say there are 4 audio files in the same directory as multi.py , so the directory looks like this:

The code is based on the sounddevice library for python, whose documentation is pretty sparse. This script will find the audio files, and then play them on as many devices as there are attached. For example, if you have 3 sound devices it will play 1.wav, 2.wav and 3.wav on devices 1-3. If you have any questions, feel free to ask:

Here are some more photos of the build:

Why you should use Processes instead of Threads to isolate loads in Python

Key Learning

Python uses a Global Interpreter Lock to make sure that  memory shared between threads isn’t corrupted. This is a design choice of the language that has it’s pros and cons. One of these cons is that in multi-threaded applications where at least one  thread applies a large load to the CPU, all other threads will slow down as well.

For multi-threaded Python applications that are at least somewhat time-sensitive, you should use Processes over Threads.

Experiment

I wrote a simple python script to show this phenomenon. Let’s take a look.

The core is this increment function. It takes in a Value and then sets it over and over, increment each loop, until the running_flag is set to false. The value of count_value is what is graphed later on, and is the measure of how fast things are going.

The other important bit is the load function:

Like incrementload is the target of a thread or process. The z variable quickly becomes large and computing the loop becomes difficult quickly.

The rest of the code is just a way to have different combinations of increment and load running at the same time for varying amounts of time.

Result

The graph really tells the story. Without the load thread running, the process and thread versions of increment run at essentially the same rate. When the load thread is running, increment  in a thread grinds to a halt compared to the process which is unaffected.

That’s all! I’ve pasted the full source below so you can try the experiment yourself.

CHAMP: Compliant Hook Arboreal Mobility Platform (Senior Thesis Project)

For my senior thesis project at WPI, myself and two colleagues (Rachael Putnam – RBE/ME and Mead Landis – RBE/ME) designed a tree climbing robot. I was in charge of designing and implementing the electronics and controls software. I was the most intense project I have ever worked on, both in terms of difficulty and potential impact. Here is our poster for project presentation day:

Here’s a video of the prototype climbing:

We did a blog during the project, here is the best post I wrote:

The report is massive, check it out here: https://digital.wpi.edu/concern/student_works/s4655j16f?locale=en

 

Find distance between two zipcodes, dump the result in an excel file

I recently wrote a piece of software for a friend working on a project, you can find it on github here. The following is from the README.md:


zipcode-distance-excel

This is a command line utility to automatically calculate the distance between two zipcodes and then put the results in an excel (.xlsx) file. It works for US postal codes only.

It was developed to help a colleague and is very application-specific.

Prerequisites

Downloading is easy git, which is already on most systems, on ubuntu use:

For everyone else:

Installing

A step by step series of examples that tell you have to get a development env running

Say what the step will be

Usage

in a directory with the .xlsx file that you want to modify, run:

The program skips the first row in the spreadsheet to avoid headers.

Example Usage

Before:

Before

Terminal output:

After:

After

Authors

  • Devon Braysite
  • Miranda Lawellsite

License

This project is licensed under the MIT License

Comparing blank string definition in Python3

In python3 using

or

Produces the same result for the programmer. Which one is faster? Using the python module timeit, it’s really easy to find out!

Using string="" is WAY faster.

Here’s the source code for my tests: