For now, DALL-E 2 is still where its at for photorealistic images, but if you can make more artistic and artificial-looking images work for your application, then you have a rapidly growing menu of Stable Diffusion-based options to choose from. This story nicely illustrates an important rule of prompt engineering: words, above. My main application for this right now is when my output image is missing a part that I want to see. This is a complex tool, but if it's supported can give a lot of good options for more subtle or smaller details. Can be quite slow, depending on your hardware, Installers are still new and not as rapidly updated, If you go the command line route, installation can be a beast depending on your platform and your knowledge of Python tooling. 2. But if you work with a local tool and do only one step, youll get something like the following (prompt was, Often, depending on the type of image, its hard to predict what the impact of adding steps will be. So as youre generating images, pay attention as you tweak different knobs and sliders to see how they impact the cost per generation. A negative prompt may prevent generating specific things, styles or fix some image abnormalities. We added some examples made with Stable Diffusion. But the other thing you can do is modify your images to fill in parts that are missing using a technique calledinpainting. Each of these has its advantages and disadvantages, which I break down, below. So with our prompt-as-flashlight analogy, youre still highlighting the same region or point in latent space, but then youre taking the extra step of finding its opposite coordinates and rendering the image from those. Me and someone else have created a prompt engineering sheet for DALL-E 2! This is not going to have the performance you could wring out of an optimized, heavily tweaked command-line installation, but if you just want to get up and going on Stable Diffusion for free then this is the best way Ive found. Updated DiffusionBee now records the seed used (& all other settings used) in the history tab. You can run it from your own computer preferably with 8GB VRAM+ GPU, or cloud-based virtual machine (I managed to run it on. You need to pile on the modifiers that most closely relate to the result you want. The reason for this metered billing model is that using the Stable Diffusion to generate an image requires a non-trivial amount of computing resources. For a very detailed guide to crafting the best stable diffusion prompts, see A Guide to Writing Prompts for Text-to-image AI if you feel like you want to read more. Stable diffusion is an open-source technology. https://docs.google.com/document/d/1O41qGvE69qnDoaqcdeokCObcRR_4yUUjRCmvPEVd2MU/edit?usp=sharing. I tried a number of variants before I settled on the output you see above some of them were just barely recognizable from my input image, while others were just a cleaned-up version of my sketch. Create detailed prompts for unique AI generated designs. The post is about how to enhance your, Were on the last step of the installation. lavinia first dates Stable Diffusion text2imgimg2img. A negative prompt may prevent generating specific things, styles or fix some image abnormalities. The model takes a noisy input image, then produces a slightly less noisy output image. So just as with text-to-image, youll have a text prompt and all the other options described above, but in addition to those, youll set the above two options. Google also personalizes your results by taking in a lot of other data, from your prior search history to your geographic location, in order to infer search intent and improve quality. Ask yourself what terms users would probably type into Google in order to find your image if they had already seen it and wanted to locate it again. Stable Diffusion is a State of the Art AI model for generating images based on prompts. This business of tweaking your text prompt in order to navigate the models latent space to find what you want has a name: To me, the results above looked spot-on this was exactly what I was envisioning in my minds eye when she gave me the prompt to type in. If you're trying to produce portraits the majority of your credits are going to be wasted on images with messed-up eyes and 7 finger claw hands. When specified, it guides the generation process not to include things in the image according to a given text. Canon50: Makes the picture into a camera photograph Forces picture to be realistic. Right now, my only recommendation is to save the image files with the seed and prompt as the filename, e.g. , but in some cases, you may not want this. May be worth knowing about Automatic1111 (https://github.com/AUTOMATIC1111/stable-diffusion-webui) for Windows/Nix environments. Right now, my only recommendation is to save the image files with the seed and prompt as the filename, e.g. Most of the tools well be working with wont let you put the value 1in for the number of steps 10is the common minimum. They already have more optimized stuff for anatomy coming, but for now there doesn't seem . Just like with a Google search, where you try to add specifics to your query so you can narrow in on the right URL in Googles database, adding specifics to your prompt will get you into the right region of the models latent space. But if youre willing to invest a little time into learning the basics, you can get started without spending any money at all. Start using the best prompt builder for Stable Diffusion. They are iterating rapidly. This is not going to have the performance you could wring out of an optimized, heavily tweaked command-line installation, but if you just want to get up and going on Stable Diffusion for free then this is the best way Ive found. Once again, if you come across something better that Ive missed, please drop a link to it in the comments, along with some color on why you prefer it! Krea.ai supports browsing and searching, and I find I use both depending on my needs. This article serves as a complete reference to everything related to Stable Diffusion, including tools, tutorials, and numerous resources for styles. that at the extreme it turns into a laser pointer that illuminates a single point in latent space. Some UIs expose prompt highlighting and/or cross-attention, which can allow you to put more emphasis on a part of a prompt, or even change the emphasis at certain progress steps. This is the latest, application-focused installment of my series on AI content generation. When specified, it guides the generation process not to include things in the image according to a given text. Animage strengthvalue that acts more or less like the cfg scale value does for the text prompt, i.e., it sets the amount of influence the image will have over your outcome. For prompt discovery, Im currently usingKrea.ai. ). But there are two that are a little more subtle and worth looking into. Its worth trying to develop an intuition about this value in terms of latent space. (At least, I personally find it pretty overwhelming!) Render: the act of transforming an abstract representation of an image into a final image. The level of the prompt you provide will directly affect the level of detail and quality of the artwork. One of the UI patterns Im seeing emerge in image generation tools is the filter metaphor. [] If you havent, then stop what youre doing and go sign up so you can follow along with the rest of this section. But you do need to understand some basics because prompt engineering presents a set of novel user interface requirements that the first wave of AI content generation apps is frantically trying to solve. Image URL ending in .jpg or .png. . With the command line version of Stable Diffusion, you can actually use a, . The post is about how to enhance your prompt image generation. But wow, there are already a lot of ways to run Stable Diffusion its overwhelming. May be worth knowing about Automatic1111 (, https://github.com/AUTOMATIC1111/stable-diffusion-webui. That is a whole other project, but a necessary one (for now) if you want to customize the model with your own images (a.k.a. You can add computing resources to Stable Diffusion in two ways: Linearly, by waiting longer for a generation to complete, In parallel, by throwing more hardware at the task and doing it faster. Some UIs will warn about exceeding token max, but most will silently truncate. You may end up using some other tool Im personally using and recommending. You need to pile on the modifiers that most closely relate to the result you want. With a local install, you can use a modified version of the workflow I describe, above: Use a tool like Krea.ai for prompt discovery, Put those prompts into your local machine for experimentation and iteration. You might have one field for the subject, with some helpful guidance (tooltips, links to help pages, other affordances), and then a separate widget for applying styles to the subject. The same seed and the same prompt given to the same version of Stable Diffusion will. Stable Diffusion can be used to fill in the missing parts of images. through the model for another de-noising pass. My recommendationStay away from these filters if they dont level up your knowledge of prompt styles by showing you how theyre changing your input. equation is that by holding the seed constant you can then subtly tweak the prompt to iterate closer to the exact image you want. Notice that I said morerelevantwords, above. Dialing the Cfg Scale towardzero produces an extremely wide beamthat highlights the entire latent space your output could come from literally anywhere. in August 2022, content creators who want to get started with AI image generation now have an affordable option with three critical advantages over, Its open to developers to implement in their apps without any oversight or censorship from the model maker. Whatever combination of tools lets you do that is the one you want to start out with. The drawback to the search query approach Ive advocated here and in previous articles is that the Google interface often gives you an effectively infinite number of results for both URLs and images. This isnt the place for a full introduction to this I dunno, is it art or science? Download and install the latest Git here. right now but I do recommend keeping a freebie Dream Studio account because its always going to have support for new features that will then trickle out to other apps. I think some naive users are going to imagine these as filters on the models output, but theyre really filters on your text. value that acts more or less like the cfg scale value does for the text prompt, i.e., it sets the amount of influence the image will have over your outcome. . Stable Diffusion Prompt Builder. But she gave these images a big thumbs down because. 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