Create WORKING QR Code Art With Stable Diffusion! (QR Code Monster)

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Welcome to our YouTube channel in today's video we'll delve into the world of QR codes those handy visual representations that store various data but we're taking QR codes to the next level by creating not just functional but visually impressive ones using stable diffusion and control [Music] net to embark on our journey to create stunning QR code Art here's what you'll need first make sure you have the automatic 1111 stable diffusion gu installed you'll also need the control net extension so follow our control net installation guide to set that up lastly don't forget to download the QR code monster model for control net this model can be found on the hugging face website link is in the description once you've downloaded the safe tensor file simply move it to your control net models folder like this before we get into the creative process with stable diffusion you need a QR code that meets certain criteria for better results make sure your QR code meets these requirements it should use a high fault tolerance setting of 30% ensure there's a white margin also known as a quiet Zone around it utilize a basic Square fill with a black and white pattern avoid generators that introduce thin white lines between black elements after generating your QR code code downloaded as a PNG file you can use a free QR code generator to meet these criteria and we recommend Anthony's QR toolkit inside this QR toolkit set the error correction to H margin to four and pixel size to 20 to create captivating QR codes we use stable diffusions text to image function alongside the QR code monster model here's how to set it up first access the text to image page in the automatic 1111 web UI select a checkpoint of your choice and enter a prompt and a negative prompt Now set the text to image settings as follows choose a sampling method I will use DPM plus plus 2m SD Caris set the sampling steps to 30 to 40 but feel free to experiment with both of these settings though we recommend at least 30 steps for width and height set them both to 768 and the CFG scale should be set at around 7 although this doesn't matter that much next enable highres fix and adjust the following settings for the upscaler choose either e arore 4X or 4X ultr sharp if you have it set high res steps to 20 denoising strength to something low like 0.2 or 0.3 and set upscale by to a minimum of 1.25 and a maximum of two I discovered that boosting the resolution with high-res fix makes the QR code scan more smoothly however it does take longer to generate if you have an older GPU I suggest starting without highres fix perfecting the image and then generating it once more with highres fix enabled and using the same seed now let's move on to the advanced control net settings keep in mind that these settings were optimal for my specific setup prompts and checkpoints when you tweak the prompts or checkpoints you may need to make slight adjustments to the control net settings we'll delve into those modifications shortly but let's start with the basic settings for now first drag your QR code into the control net unit and enable control net now adjust the following settings set Pixel Perfect to yes for the pre-processor choose none select the QR code monster model adjust the control weight which is typically around 1.7 but we will adjust this later as needed the starting control step should be set to 0.2 and the ending control step to 0.8 and control mode should always be set to balanced now you're all set to generate keep your mobile device ready to quickly test the QR code after generation this way you can make instant adjustments if the QR code isn't scannable or too prominent once you've configured your setup and generated the image you may find that you're not entirely satisfied with the result but don't sweat it this is the point at which we refine the control net settings to address any issues you can follow a few straightforward steps to achieve this if you're content with how the image looks ensure you use the same seed when regenerating it by simply clicking on the recycle icon next to seed this consistency helps maintain the aspects you like in the generated image if the QR code is not scannable increase the control weight and ending control step in steps of 0.1 if the QR code is too visible simply decrease the ending control step and control weight in steps of 0.1 you can play around with both the control weight and the ending control step to find find the right balance sometimes adjusting the starting control step by a small amount can also help be cautious not to exceed a value of 0.3 as it might render the QR code unscannable in this example the QR code was too visible for my liking so I increased the starting control step by 0.05 while I also slightly adjusted the control weight and the ending control step this one is perfect the QR code is still easily scannable and it looks amazing so there you have it the art of creating stunning QR codes using stable diffusion and control net you've learned the essentials from setting up your environment to perfecting your QR codes remember it's all about finding that balance if you want to learn more I highly recommend you visit our website nexto fusion. thanks for watching and we can't wait to see the QR code masterpieces you'll create don't forget to like subscribe and hit that notification Bell for more AI Adventures until next time stay creative
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Channel: Next Diffusion
Views: 1,656
Rating: undefined out of 5
Keywords: stable diffusion, ai, midjourney, ai image generation, ai video generation, stable diffusion tutorial, Stable diffusion tutorial, ai art tutorial, control net tutorial, chatgpt4, ai tools, ai news, artificial intelligence, ai animation, ai art, ai design, ai graphic design, ai tutorials, visual art, stable diffusion models, digital art, inpainting, ai editing, best ai, ai tutorial, AI tutorial, best AI, automatic 1111 update, controlnet tutorial, controlnet, QR code art
Id: BV0vGzsmlK0
Channel Id: undefined
Length: 6min 11sec (371 seconds)
Published: Thu Oct 26 2023
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