sirkster_dev

The final week is upon us. I have the 50/50 model up and running, and I plan to finish the full "ouroboros" style generator this coming week, to unveil at the exhibition. Here's some examples of various epochs of training, keeping in mind this order of "sketch/original generated image/newly regenerated image."

A cool effect you'll notice is the smoothing out of certain visual artifacts: I actually curated these images, so I had to pull certain pieces to use for the retraining set--some images were unintelligible, and I could not have those taint the retraining. However, some of these were deemed acceptable by me, despite a few artifacts, and as you can see here, these get mellowed out as it retrains, which is really cool.

Things are really ramping up with the curational aspect, and I admit it has meant my project has taken a bit of the backburner as a result. However, I have currently made quite a few sketches in the background to feed into the generator, so that I may curate around half of them to feed back into the dataset. My goal is to have that 50/50 generator model finished, then have the full "ouroboros" model in line for week 10, so that I may have time to fix any kinks I find with the generator.

Well, things are finally getting into motion! Saturday's meeting with the other curators was a great success! Still chugging along in the model training, although I have a nice little mockup of what's to come!

You can see the labels underneath are as follows: ・Original Sketch: My original sketch given as an input to the varying models. Sketches can have varying levels of looseness (such as construction lines still present). ・Sketch2Line Model: This is the first model I tested with, and merely shows an attempt to replicate my lineart. It was an important model that served as a stepping stone to thinking bigger than just "replicate my art." ・Sketch2Full Model: This model is the fully stable model trained to finish my sketches to full pieces, with a wide array of different pieces. This is an important checkpoint. ・89to11 Model: This model is named because it is 89% my art, 11% AI-assisted art, as I am starting to feed its own imagery back into the training sets. I hope to have later models that eventually feed more art back into itself, and I would love to explore how it evolves based on my own curation of art I deem "good enough to approve."

Okay, I have introduced some of the images back into the dataset, curating the best of the generated images to pass on as good enough to retrain itself on. While the majority of images are still my art (89%), the effects seen on the simulated outputs look really promising:

Hey all, not much in news today for updates, but that is not a bad thing.

I'll be honest, I had a bit of an off week this time around: been feeling particularly low mentally speaking, but once again, thank you past me for making good progress that allowed me to take a sort of break week.

My HP Sprocket Plus had died, and I have acquired a new HP Sprocket Select to replace it (turns out the Plus model is discontinued, who would have known?); I've also been having it a bit tough in my own personal matters of life.

Regardless, I feel I have really gotten to the core of what I want to do: for exhibition, I think showing off my drawings, with input and output, is the way to go. I will also show early progress to show the budding starts of it, and it will really sell the durational aspect of my project.

I think the part that will be most influential too will be the moment I finally take the AI off of my own art, and have enough curated test images to then fully train off of. In essence, I can "finish" the project off at the exhibition. As such, these weeks will merely continue to train, as I start to replace the dataset with more images of my own art. This will be really really cool to see, and I'll probably leave hell week (week 20, or week 10 of this quarter) as a test week for the fully independent model.

Big day today: midterm updates!

For me, most of the moving parts are in place: I have acquired an even better HP Sprocket Plus, so the pictures are ever a bit bigger, which is awesome (thank you mom for you HP admin connections).

I have also begun to see what it may be like to introduce trained art back into the training dataset. I figure since I am working with a purposefully small dataset, I need to really be careful in what I choose as "good." Due to the nature of now having my model input my sketch to output a full piece, I have also made it easier to produce a larger volume of sketches to generate final images: in essence, I can make generated art relatively quickly. As such, I can curate the right pieces and observe the evolution.

So where does that leave us? I think what is nice is that I can use the remaining weeks to streamline the process but also simulate what could be happening as the machine learns more off of its own artwork, seeing what semblance of style it may try to push forth. Or I could find that it may take a long while before a meaningful shift can be found. Either way, I think it'll really help me in making such a process interesting. If viewed like a science experiment, I could even then say that the null hypothesis is true: the imagination cannot exist within the machine, as it needs too much input from me to exist properly.

Hooray! Things are working quite smoothly: I was able to run the code locally on my machine, so no more messing with Google Colab and needing to rerun the cells every single session, nor reuploading certain files like the generator.

I have also acquired an HP Sprocket! As such, I am able to print out pieces on a small 2in x 3in piece of paper; these don't come cheap, so while it's fun to sketch, I have to be a bit more choosy with what I decide to print. Perhaps, depending on the quality of the pieces, I can curate the best generated artworks to print out. But yeah: I may need less wall space than I originally expected!

Hello again, and while I need to update this post with a reply later when I return home (and have access to better quality images), I want to give an update into the process!

One aspect, in terms of live drawing and later image exhibit after I have left (with a durational component over the days), is that I plan on getting my hands on an HP Sprocket printer. These are meant to print small images, which is my plan when showing off the images--they are meant to be looked at closely, but they are also meant to exist as part of a large collection of works to really show the steps of training when it comes to the model (and future retraining as the days pass by).

Originally I wanted to translate from sketch to line art, due to wanting a more accurate recreation--however, in this quarter, the idea has evolved into purposefully making big leaps in hopes of finding weird "errors" to be used creatively.

As such, in this past week I had experimented with training sets with the biggest leap: sketch to full piece. I had not initially considered it as I was too scared to make such big a leap, especially not having much data, but now, I have embraced both limitations as a way to confront more avenues of creativity.

I also wanted to say that one idea I really would like to tackle is the idea of abstraction, in both the computing and the artistic sense of it. With my self-identification of creative first, academic second, this feels like a perfect marriage to combine both. I hope that in by training this model on my character art (as I primarily draw characters), I can use that translation to abstract other full pieces, and in a sense, explore a genre of art I have not much considered doable on my part. One could argue I am making a mockery of abstractions in art, but I like to see it more as another foray into that realm, able to coexist with established forms.

Hello all again! I know the dev posts have been quite quiet since the end of last quarter: I took a well needed break from this project entirely, and I am raring to go as we finish off this quarter!

I want to start out with saying that I am quite close to being done honestly: a lot of the work now is creative experimentation, so pats on the back to myself for really doing the heavy lifting in the first half.

The state I left it at during our final week of the quarter is nicely summarized here:

During demos, I had the important criticism that it merely tries to replicate my lineart, but terribly. Thus ideas were thrown around about intentionally breaking it--giving it images it was not trained to take, and seeing where those results could lead. As such, I don't feel like I want to chase the line art anymore: I want to chase full pieces, and I want to fully embrace all the imperfections that can occur.

As such, we can see it is quite rough--even in training it still struggles to fully replicate, but again, that is the point, and I am okay with playing with the imperfections.

Breaking stuff is going to be a focal point of my experimentations.

So while I still have things to work out creatively, here's the big thing I want to share here in this update: the tentative layout of how I wish to exhibit.

I really want to run this similar to an artist alley situation, but with that fun twist, and a display of my works after I finish the live drawing. This is my fun and intentional take, plus the portability aspect would make it very easy to transport to other locations if need be. I also want to help my fellow colleagues if need be, as I care about their success just as much as mine.

So, here we are, at week 10. I think the best thing for this post would be to summarize this quarter's timeline now.

Week 2: Artist statement and motivations have been established.

Week 3: Timeline established, with explorations into possible models such as Teachable Machine from Google, the text-to-image generators like Stable Diffusion and DALL-E, as well as the image-to-image cGAN known as Pix2Pix.

Week 4: Further locking into Pix2Pix, using tutorials from YouTube to learn more about cGANs in general and understanding a bit better as to the method of how this model trains off data.

Week 5: Further learning of bits of Python coding, as well as a lot of troubleshooting: installed the needed libraries that were missing. My idea of injecting my sketches into a machine that can finish them into lineart is fully established--I just need to figure out how to actually train this model.

Week 6: Troubleshooting still occurring, and worried about midterm presentations. Got pushed to week 7, but progress seemed quite slow. There were some improvements to the code made, after realizing the nearly 4 year old code had some weird kinks to work out, due to it utilizing an older version of python.

Week 7: TRAINING SUCCESS! Pulled through on Monday night, and finally got through a training set in the nick of time. Tuesday I was able to give my midterm presentation with training results. Very exciting breakthrough week.

Week 8: Further dataset production (making more sketches for the model to train off of, but not a big priority currently). Looking into real-time implementation, but it involves other languages with other libraries I am not familiar with. Definitely will take some more learning.

Week 9: Got some nice pointers from the great Prof. Memo Akten--turns out I may be able to use Python to achieve what I want. Not much progress done this week other than image drawings, had other projects to work on from other classes.

So I have reached my minimum checkpoint, that being getting the model to spit out images after being trained. Currently I want to do some implementation of real time.

I've been looking at other GitHub repos, but I admit the implementation notes are a bit above what I am currently used to--after all, it took me 4 weeks before I could properly get the model to finally train. I have a few options at the ready, like Memo Akten's branch that uses openCV, as well as another I found that uses Unity. I plan to work through these, and if somehow by the end of this I cannot get this real time option to work, I most definitely will pursue other avenues.

Hello again all; been a bit busied up lately, so my progress has been unfortunately on the slower end. I really want to get my model to generate images based on sketches it now has not seen.

I have found a promising video linked to the first tutorial I used, where it uses Google Colab. https://www.youtube.com/watch?v=fXgodCC2O7o