Prompting on stable diffusion reddit a deformed hand), do I just type in the element I want to generate or do I adjust the hole prompt I’ve used to generate the original image. I got the following: 1girl, bare_shoulders, black_hair with this prompt may appear 2-3 children, but usually with daemon horror deformed or brutally colored faces, in all models and VAE, independently from the negative prompt, I suppose this is some kind of censorship in the system itself 11 votes, 14 comments. 4 Stable Diffusion Model Checkpoint; it’s the default model. So many Stable Diffusion tutorials miss the "why". Guide the AI on the focus of the image. At least that is how I understand it. " Impact: Ensures the AI generates an image that respects the cultural or historical context of the scene. The prompt might read "three girls in the forest with hooks for hands," and the image will be one girl by a lake with a cybernetic hand. For example, I want high heels in a picture, it was difficult to remove it no matter where it was in the prompt. And here are 21 named poses. 6) if its less than 1. 2 Be respectful and follow Reddit's Content Policy. I've recently found that structuring your prompts in both Midjourney and Stable Diffusion really helps. Sounds innocent enough, but this was actually preventing the camera from moving to a position where IMPORTANT: For any images that feature a person or persons, and are also using the Medium of a photo, photograph or photorealistic in you response, you must always respond with the following literal keywords at the start of the NEGATIVE prompt paragraph, as the first keywords before listing other negative keywords (omit the quotes): "bad-hands Must be related to Stable Diffusion in some way, comparisons with other AI generation platforms are accepted. As soon as we add a conflicting concept like "spindly arms", it dreams up two concepts and tries to sample them as one solution to the noise reduction task at hand. Siliconthaumaturgy7593 - Creates in-depth videos on using Stable Diffusion. It depends on the implementation, to increase the weight on a prompt For A1111: Use in prompt increases model's attention to enclosed words, and [] decreases it, or you can use (tag:weight) like this (water:1. Now i know people say there isn't a master list of prompts that will get you magically get you perfect results and i know that and thats not quite what im looking for but i simply need help with prompts since im not really that descriptive especially when it comes to hairstyles and poses. " These were all tested with Waifu Diffusion, Euler A, with each prompt at the beginning of the prompt list, so results will vary a lot if you use Stable Diffusion and different settings. Stable Diffusion Training data info. Set CFG way higher than you normally would (e. A subreddit about Stable Diffusion. Is there a dictionary of these that SD understands? While we are on the topic does it recognize standard cinematography like 'tight cowboy', 'wide cowboy', and other terms I totally forgot? I’ve been training ChatGPT to output some fashion clothing styles prompts for Midjourney and Stable Diffusion. I fine tuned an LLM model (Mistral-7B) with a new dataset I created containing close to 5000 fairly good stable diffusion prompts along with "human style" descriptions of the prompt. I write stories from time to time, and since I discovered Stable Diffusion I had the idea of using this to accompany my stories with AI generated images. 105 votes, 16 comments. Nerdy Rodent - Shares workflow and tutorials on Stable Diffusion. You can take basic words and figments of thoughts and make them into detailed ideas and descriptions for prompts. Obviously not the same, but my quick process was: - import your photo into img2img- interrogate DeepBooru. Disco Diffusion Illustrated Settings. So I decided to try some camera prompts and see if they actually matter. Stable Diffusion: Trending on Art Station and other myths; part 2. You need to generate an input prompt for a text-to-image neural network. boilerplate, weird punctuation, and nothing at all, all fail to make stable diffusion get excited. Tags seem so much less detailed to me, because there's a ton less prepositions and such which give you an idea of well, the positioning and relativity of things with each, along with the assumed relativity where the imagination adds it's own variables, in the case of ourselves which is fine and totally unsurprising given that it doesn't take much experience with stable diffusion to imagine how unspectacular the results would be if you took any of those three negative prompts and rendered them as positive prompts. It's now able to interpret your prompt much more exact = better storytelling. After months of experiments, I realized that the model is more important than the order. Hereby, I present to you a Stable Diffusion Prompt Generator, which can randomly (or less randomly, depending on your inputs) build tons of prompts for you : Stable Diffusion Random Prompts Generator. The thing is I couldn't give prompt properly. I was asking it to remove bad hands. For instance, how to describe an image featuring a cat and a dog standing side by side the cat is prim and proper wearing a tuxedo and the dog is obese, wearing a tshirt with his belly spilling out over the jeans. 6 (up to ~1, if the image is overexposed lower this value). By specifying resolution terms like “4K,” “8K,” “highly detailed”, or even “64K,” you instruct the AI to focus on creating a high-quality image with crisp details. How and why stable diffusion works for text to image generation: Illustrated visual explanation. The keyword here is "simple prompt", prompt adherence is following what the prompt says, and it usually requires moderate or long complex prompts to get evaluated and image quality has nothing to do with it. Adding "looking at viewer" to negative prompt also works good in conjuction with "looking away" in positive, so do both! Token placement in prompt and commas or lack there of, will also do a lot. In my positive prompt, I'd copied a phrase saying 'Photo Realistic'. Dec 15, 2024 · I am having hard times getting something, some are just giving tips on how to build a picture, the (lm_3_2_flux prompt stated by op) answered with a short but correct prompt (cyberpunk nswf fetish subject) for one time, then it kept spitting short paragraphs of random beautiful scenery prompts, with birds and flower singings and blue sky and Prompt: "A traditional Japanese tea ceremony, with participants wearing authentic kimonos. Monochome or black and white - massive influence - will make everything black and white Sepia - mild influence - will give a sepia colour palette. A quick correction: When you say "blue dress" in full body photo of young woman, natural brown hair, yellow blouse, blue dress, busy street, rim lighting, studio lighting, looking at the camera, dslr, ultra quality, sharp focus, tack sharp, dof, film grain, Fujifilm XT3, crystal clear, 8K UHD I created this for myself since I saw everyone using artists in prompts I didn't know and wanted to see what influence these names have. I made a 182 page prompt guidebook covering: The best models for photorealism Optimal program settings Prompt syntax and structure 350+ example images 200+ prompt tags for styles, lighting, angles, etc /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. Restart Stable Diffusion Compose your prompt, add LoRAs and set them to ~0. Stable Diffusion doesn't really like long complex prompts. Prompt Engineering. I was a big 1. Please provide the prompts in a code box so I can copy and paste it. Break forces the creation of a new batch by adding a bunch of empty tokens between sections of your prompt, so that they exceed the 75 limit. Keep it under a half dozen phrases at most if your prompt is misbehaving. i would love to see some research on that or get some details from someone more involved in training the initial dataset. This is done by breaking the prompt into chunks of 75 tokens, processing each independently using CLIP's Transformers neural network, and then concatenating the result before feeding into the next component of stable diffusion, the Unet. But it was very time consuming. This prompt library features the best ideas for generating stunning images, helping you unlock new creative possibilities in AI art. Sometimes my creativity get stuck, so this helped me a lot. In Stable Diffusion, parentheses are used to emphasize tokens. The problem is that it doesn't know what hands and other things are. Turn Hires fix on (or not, depending on your hardware and patience) Set up Dynamic Thresholding. No X-rated, lewd, or sexually suggestive content This is a public subreddit and there are more appropriate places for this type of content such as r/unstable_diffusion. TOTAL NEWB HERE: But after reading so many Civitai examples, it seems there's a massive amount of randomness about it. But typing a prompt into a word processor under the following headlines sees to streamline getting a usable result no end. i agree in most things you said except the point that the hands wouldnt be as bad or would be less noticeably. I'd much rather just type out an English sentence like I was describing an image to someone, rather than tags. 0 it decreases the weight The mental trigger was from writing a reddit comment a while back. I have only one question which I didn’t figured out yet: when I adjust the prompt for my inpainted area (e. Previously I'd just been placing the most important terms to the front. don't work. Note that the negative prompt here references "cartoon" but the output image is definitely much more cartoon-like than photorealistic Bad take; while in your imagination photorealism is an antagonist of cartoon, in reality they are just different styles, among many many others. In the original guide I had the negative prompt deconstructed and show what each part affected the rate of good image. A similar false positive pattern seems to be quite rampant in Stable Diffusion prompting. In your second prompt hair and hoodie are right next to each other, even though you have weighted ((purple hoodie)) the orange is bleeding into it. It just sees a bag of pink or brown or whatever pixels. (Won't go into models and loras in this video, just vanilla) Prompt Formatting: Tokens: Used to separate concepts in the prompt, as Stable Diffusion struggles with natural language understanding. SDXL does indeed need a lot less negative prompting. Prompt tokens in SDXL also have a much bigger impact now in general. A long prompt will muddle the encoder. For example, a prompt with 120 tokens would be separated into two chunks: first with 75 tokens, second with 45. **I didn't see a real difference** Prompts: man, muscular, brown hair, green eyes, Nikon Z9, Canon R6, Fuji X-T5, Sony A7 The whole wall of word salad text approach isn't really that effective for controlling what stable diffusion does. Dynamic Prompt is a script that you can use on AUTOMATIC1111 WebUI to make better, more variable prompts. 5 now a days. Public Prompts: Completely free prompts with high generation probability. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. Bottom line was that even if the negative prompt is ugly, in many case it just Apr 29, 2024 · Advanced Prompting Techniques in Stable Diffusion Weighting with Parentheses. Excellent guide. Hopefully some of you will find it useful. Fast-forward a few weeks, and I've got you 475 artist-inspired styles, a little image dimension helper, a small list of art medium samples, and I just added an image metadata checker you can use offline and without starting Stable Diffusion. 2) or (water:0. A Traveler’s Guide to the Latent Space. g. Folks, I’m struggling - but in a good way. Models trained specifically for anime use "booru tags" like "1girl" or "absurdres", so I go to danbooru and look tags used there and try to describe picture I want using these tags (also there's an extention that gives an autocomplete with these tags if you forgot how it's properly written), things like "masterpiece, best quality" or "unity cg wallpaper" and etc. But for some reason I can't get me prompting right. What works for one model might not work for the next. . In this guide I will explain how to use it. 5 user for anime images and honestly was pretty wholly satisfied with it except for some few flaws like anatomy, taking forever to semi-correctly inpaint hands afterwards etc. Some of the prompts I've posted here don't use any negative prompt. Hey folks – I've put together a guide with all the learnings from the last week of experimentation with the SD3 model. best-prompts-for-text-to-image-models-and-how-to-find-them /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. You can use your own list of styles, characters, objects or use the default ones which are already kinda huge. SD gets confused and thinks you're asking for a specific camera 'photo' angle and tries to force this angle. We're open again. I still use them to tweak the fidelity or work on certain aspects. 5. 22K subscribers in the sdforall community. Guys, you need to check out the official DALL-E 2 Prompt Book! I'm sure a lot of the relatively generic promptwriting information can also be applied to Stable Diffusion. true. The Stable Diffusion model has the least problems (and thus needs the least steps) to filter one concept like "woman" from the starting noise. Stable Diffusion Prompt Library Explore the top AI prompts to inspire creativity with Stable Diffusion. For instance from here are 50 named poses. Overly long prompts will result in the influence of individual tokens getting "diluted" and reducing prompt compliance while also making the model rather inflexible. ~16). It was more noticeable in V2, and in the original guide I shared the % of good image the negative prompt was giving. you most proabably get different results but that they are statistically less screwed or less noticeable is a myth imo. Please do not use Reddit’s NSFW tag to try and skirt this rule. are more like conventions Negative prompts for anatomy etc. In my negative prompt, I'd copied a phrase saying 'out of frame'. I just uploaded a small image caption dataset of prompts which were likely used in the training of Stable Diffusion 3 and I hope this helps to clear up how to prompt for SD3. But bad hands don't exist. I was replying to an explanation of what stable diffusion actually does, with added information about why certain prompts or negs don't work. The default weight of a token is 1, and anything inside parentheses will be multiplied by 1. So as a new user I want to know that how to give a proper and good prompt to get the best results. Then I looked at my own base prompt and realised I'm a big dumb stupid head. The resulting model was great passable, though I will refine it more in the future. A vector is created for every batch. Except maybe for "Kermit the Frog, from Hackers (1994)" and other similar (short) prompts from which DALL-E yields way better results. ckpt. 100 votes, 13 comments. I wanted to share a free resource compiling everything I've learned, in hopes that it will help others. com Apr 3, 2024 · When crafting the perfect prompt for Stable diffusion AI, resolution keywords act as the brushstrokes defining the sharpness and clarity of your desired image. I’ve started mainly using SDXL (Fooocus is my current go-to UI) and I want some advice on SDXL prompting vs 1. Link to full prompt. 05. Where in your first prompt there is more distance between hair and hoodie changing the relative weights and the impact the color orange will have on the hoodie. Here it goes for some female summer ideas : Breezy floral sundress with spaghetti straps, paired with espadrille wedges and a straw tote bag for a beach-ready look. I haven't tested words like (masterpiece) enough to tell if they have an impact, but I feel like they're a myth The myth of "masterpiece" and "best quality" is that they're old wives tale style prompts that people use out of some superstitious belief they have some positive quality effect on their generations. What does Stable Diffusion understand as far as a syntax of poses. The creation of the dataset and any deviations of the original are described on the HF page. Every stable diffusion model responds differently to prompts. This multiplier stacks, allowing you to fine-tune the emphasis. I will be copy pasting these prompts into an AI image generator (Stable Diffusion). See full list on stable-diffusion-art. You are not going to find an LLM that works "well" for all of those models as its not dependent on the LLM but the base image model being used. Note that there is a lot of information in the Stable Diffusion 3 research paper. If you installed Stable Diffusion correctly, you should already have that file and should not need to configure that Prompts get processed in batches of 75 tokens. r/artbusiness is a place to discuss everything related to the business side of art: from dealing with clients and contracts to marketing, social media and merch production. PromptoMania: Highly detailed prompt builder. Hello there, I once read a random article about prompting in stable diffusion and it mentioned something about BREAK to separate certain details of your character so that they wont mixed up like a prime example would be colors. Stable Diffusion Modifier Studies: Lots of styles with “Model hash” just refers to the 1. Thank you for that. CivitAI: A platform where you can find inspiration, understand prompt formatting, and see how images were created. Prompt: "A close-up of a bee pollinating a vibrant sunflower, with a soft-focus background. See extension wiki for details I am using stable diffusion 1. Our brain is so desperate to find patterns that we tend to see faces in the clouds, on burnt toast, in the smokes of 9-11, or on top of a Latte.
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