33 lines
3.3 KiB
Markdown
33 lines
3.3 KiB
Markdown
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title = "A story about the logo"
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description = "Automatically generated art"
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date = "2023-01-19"
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[taxonomies]
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tags = ["stable-diffusion", "blog"]
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# The existing logo
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I have used the same image in my Gravatar for many years, but the thing is... I can't find the source image any more. It has long since been lost to the sands of time and `format C: /q`. If you are unfamiliar with it, basically it is a diamond-shaped yellow road sign with Tux, the Linux mascot on it. I think that I found the original in a Linux magazine in the early 2000's, but there is no telling any more. It's time for a fresh look, anyways.
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<!-- more -->
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# My home setup
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I like to work on my desktop when I am at home. I have a wonderful [Dell Ultrasharp U4320Q](https://www.dell.com/en-us/shop/dell-ultrasharp-43-4k-usb-c-monitor-u4320q/apd/210-avke/monitors-monitor-accessories) display, a still-decent [i9-9900k](https://ark.intel.com/content/www/us/en/ark/products/186605/intel-core-i99900k-processor-16m-cache-up-to-5-00-ghz.html) processor, 64GB of DDR4 memory, and 2TB of NVMe primary storage. I recently used my Juno points (a self-help like service that gives you money each month to do something for yourself) to buy a used NVidia RTX 3090 GPU. This is kind of a big card; it requires something like 400W of power, two-and-a-half slots, and sports 24GB of GDDR5 memory. At the time of purchase, the RTX 4000 series was just announced, so while not quite top-of-the-line, it was still the newest available at the time. To make availability possible, Etherium had recently forked to a proof-of-stake model rather than the existing proof-of-work. This effectively made all of the at-home miners obsolete and there was a corresponding flood of GPUs on eBay.
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With the new GPU, I can finally run games at the native 4K resolution and respectable framerates to boot.
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# Stable Diffusion
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I was incredibly excited to hear about the announcement of DALL-E. The prospect of having a computer "just" make me an image was exciting. However, once I got an invite to the platform I realized that I was not impressed with the pricing model or the ineptitude of the generator. With having to pay-per-image generated and then having to cycle through so many images to get one good render, it seemed like a waste. But then I discovered [Stable Diffusion](https://github.com/Stability-AI/stablediffusion). It was __**magical**__. I made it work in Windows `git-bash` and now I have a self-hosted generator running on my GPU that can make an image in something like 4 seconds.
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Self-hosting also has the benefit of being able to load _different_ models like Stable Diffusion 1.4, SD 2.0, Waifu Diffusion, etc. I also have a choice in what interface to run. The in-built interface with the core Stable Diffusion is a CLI python script. It works great, but not so good unless you are sitting in front of a keyboard. For my current situation I have settled on [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui). It's got a lot of knobs to twist and options to change.
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# Final Result
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For this particular image, I had to generate around 50 different images to get one of "tux the penguin" on a "four sided yellow road sign" without too much in the background or whatever strange characters it thinks are words.
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