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description=Break down how diffusion models work, what makes them powerful for image generation, and where they re being applied across industries today.;

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Text of the page (random words):
eed same prompt and same version of stable diffusion will always result in the same image if you are getting different images for the same prompt it is likely caused by using a random seed instead of a fixed seed for example bright orange tennis shoes realistic lighting e commerce website can be varied by modifying the value of the random seed changing any of these values will result in a different image you can hold the prompt or seed in place and traverse the latent space by changing the other variable this method provides a deterministic way to find similar images and vary the images slightly varying the prompt to bright blue suede dress shoes realistic lighting e commerce website and holding the seed in place at 3732591490 produces results with similar compositions but matching the desired prompt and again holding that prompt in place and traversing the latent space by changing the seed produces different variations to summarize a good way to structure your prompts is to include the elements of frame main subject style type modifiers or a frame type of a main subject style example and an optional seed the order of these exact phrases may alter your outcome so if you are looking for a particular result it is best to experiment with all of these values until you are satisfied with the result 4 prompt length generally prompts should be just as verbose as you need them to be to get the desired result it is best to start with a simple prompt to experiment with the results returned and then refine your prompts extending the length as needed however many fine tuned prompts already exist that should be reused or modified modifiers such as ultra realistic octane render and unreal engine tend to help refine the quality of images as you can see in some of the examples below a female daytrader with glasses in a clean home office at her computer working looking out the window ultra realistic concept art intricate details serious highly detailed photorealistic octane render 8 k unreal engine portrait photo of a man staring serious eyes with green purple and pink facepaint 50mm portrait photography hard rim lighting photography beta ar 2 3 beta upbeta extremely detailed wide angle photograph atmospheric night reflections award winning contemporary modern interior design apartment living room cozy and calm fabrics and textiles geometric wood carvings colorful accents reflective brass and copper decorations reading nook many light sources lamps oiled hardwood floors color sorted book shelves couch tv desk plants hyperrealistic and heavy detailed fashion week runway show in the year 2050 leica sl2 50mm vivid color high quality high textured real life full body cyberpunk style sculpture of a young handsome colombian prince half android with a chest opening exposing circuitry and electric sparks glowing pink eyes crown of blue flowers flowing salmon colored silk fabric raptors baroque elements full length view baroque element intricate artwork by caravaggio many many birds birds on background trending on artstation octane render cinematic lighting from the right hyper realism octane render 8k depth of field 3d architectural illustration of an awesome sunny day environment concept art on a cliff architecture by kengo kuma with village residential area mixed development high rise made up staircases balconies full of clear glass facades cgsociety fantastic realism artstation hq cinematic volumetric lighting vray 5 additional tips a few additional items are worth mentioning placing the primary subject of the image closer to the beginning of the prompt tends to ensure that subject is included in the image for instance compare the two prompts a city street with a black velvet couch at times will miss the intent of the prompt entirely and the resulting image will not include a couch by rearranging the prompt to have the keyword couch closer to the beginning of the prompt the resulting images will almost always contain a couch there are combinations of subject and location that tend to yield poor results for instance a black velvet couch on the surface of the moon yields uneven results with different backgrounds and missing couches entirely however a similar prompt a black velvet couch in a desert tends to reflect the intent of the prompt capturing the velvet material the black color and the characteristics of the scene more accurately presumably there are more desert images contained in the training data making the model better at creating coherent scenes for deserts than the moon prompt engineering is an ever evolving topic with new tips and tricks being uncovered daily as more businesses discover the power of diffusion models to help solve their problems it is likely that a new type of career prompt engineer will emerge diffusion model limitations as powerful as they are diffusion models do have limitations some of which we will explore here disclaimer given the rapid pace of development these limitations are noted as of october 2022 face distortion faces become substantially distorted when the number of subjects exceeds 3 for example a family of six in a conversation at a cafe looking at each other and holding coffee cups a park in the background across the street leica sl2 50mm vivid color high quality high textured real life the faces become substantially distorted however increasing the number of subjects in the prompt causes the faces to become substantially distorted for example this updated prompt a family of six in a conversation at a cafe looking at each other and holding coffee cups a park in the background across the street leica sl2 50mm vivid color high quality high textured real life results in the following text generation in an ironic twist diffusion models are notoriously bad at generating text within images even though the images are generated from text prompts which diffusion models handle well for the prompt a man at a conference wearing a black t shirt with the word scale written in neon text the generated image will include words on the shirt in the best case but will not recreate scale in this case instead including the letters sc sa salee in other cases the words will be on signs the wall or not included at all this will likely to be fixed in future versions of these models but it is interesting to note limited prompt understanding for some images it does require a lot of massaging of the prompt to get the desired output reducing the potential efficiency of these models for a productivity tool though they are still a net productivity add diffusion models additional capabilities and tooling diffusion models flexibility gives them more capabilities than just pure image generation inpainting is an image editing capability that enables users to modify regions of an image and replace those regions with generated content from the diffusion model the model references surrounding pixels to ensure that the generations fit the context of the original image many tools enable changes within an image real world images or generated images by erasing or applying a mask to a specific image region and then asking the model to fill in the image with new content with inpainting you start with a real world or generated image in this case the image is of a model leaning against a wall in a modern city you then apply a mask to the areas of the image you would like to replace similar to erasing areas of the image first we will replace the jacket that the model is wearing then we will generate new clothing for the model to wear in this case a beautiful fancy gown shiny with pink highlights or a bright purple and pink wool jacket with orange highlights and highly detailed the images above maintain the original pose but these models can also suggest new poses in this case moving the arm down to the side as seen in this example a glowing neon jacket purple and pink diversity of materials is demonstrated as well with a leather jacket with gold studs and also with a shiny translucent coat neon inpainting can also replace background elements either by simply removing them and filling in the background or generating new backgrounds that did not exist in the original image start with masking out the poles in the background to generate a new background apply a mask to and generate new scenes in this case a futuristic cityscape with flying cars as you can see inpainting is quite powerful for editing images quickly and generating new scenes dynamically in the future expect the capabilities of these tools to be even more efficient without requiring the user to edit a mask by simply describing the desired edits i e replace the background with a futuristic cityscape the image will automatically be edited with no mouse clicks or keystrokes needed 2 outpainting outpainting enables users to extend their creativity by continuing an image beyond its original borders adding visual elements in the same style or taking a story in new directions simply by using natural language description starting with a real world image or a generated image you can extend that image beyond the original borders until you have a larger coherent scene real world image outpainting start by uploading an image and selecting a region on the outside border where you would like to extend the image similar to inpainting you then generate prompts that generate coherent scenes that extend the original image generated image inpainting works in much the same way start by generating a scene that will serve as the seed outside scenes lend themselves to more expansive outpainting so we will start with central park looking at the skyline with people on the grass in impressionist style now add in a man playing frisbee with his dog note that the prompt does not specify that the skyline should remain consistent with the original image the model automatically maintains and extends the background style so you can focus on adding the elements you want to see finally we will add in a family having a picnic and we have our finished image outpainting requires an extra layer of prompt refinement in order to generate coherent scenes but enables you to quickly create large images that would take significantly longer to create with traditional methods outpainting enables impressive amounts of creativity and the ability to build large scale scenes that remain coherent in theme and style similar to inpainting there is room to improve this capability by making it even simpler to generate the desired scenes by providing a single prompt and getting the exact image you are looking for 3 diffusion for video generation as we have seen generating static images is exciting and offers many practical applications several recently announced models take the capabilities of diffusion models and extend them to create videos these capabilities have not yet made it to the hands of a broader audience but will be coming very soon meta s make a video is a new ai system that lets people turn text prompts into brief high quality video clips google s imagen video generates approximately 5 second videos in a similar fashion 4 diffusion model image curation sites curation sites like lexica art provide highly curated collections of generated images and the prompts that were used to create them millions of images are indexed so there is a good chance that the image that you originally thought you would have to generate already exists and is just a quick search away searches are low latency you don t need to wait for one to two minutes for a diffusion model to generate images and you get the images nearly instantly this is great for experimenting or searching for types of images or exploring prompts lexica is also a great way to learn how to prompt to get the results you are looking for include a couple of examples here diffusion models practical applications for today and tomorrow the obvious application for diffusion models is to be integrated into design tools to empower artists to be even more creative and efficient in fact the first wave of these tools has already been announced including microsoft designer which integrates dall e 2 into its tooling there are significant opportunities in the retail and ecommerce space with generative designs for products fully generated catalogs alternate angle generation and much more product design will be empowered with powerful new design tools that will enhance their creativity and provide the capability to see what products look like in the context of homes offices and other scenes with advancements in 3d diffusion full 3d renders of products can be created with a prompt taking this to the extreme these 3d renders can then be printed as a 3d model and come to life in the real world marketing will be transformed as ad creative can be dynamically generated providing massive efficiency gains and the ability to test different creatives will increase the effectiveness of ads the entertainment industry will begin incorporating diffusion models into special effects tooling which will enable faster and more cost effective productions this will lead to more creative and wild entertainment concepts that are limited today due to the high costs of production similarly augmented and virtual reality experiences will be improved with the near real time content generation capabilities of the models users will be able to alter their world at will with just the sound of their voice a new generation of tooling is being developed around these models which will unlock a wide range of capabilities conclusion the vast capabilities of diffusion models are inspiring and we don t yet know the true extent of their limitations foundation models are bound to expand their capabilities over time and progress is accelerating rapidly as these models improve the way humanity interacts with machines will change fundamentally as roon stated in his blog text is the universal interface soon prompting may not look like engineering at all but a simple dialogue with the machine the opportunities for advancing our society art and business are plentiful but technology needs to be embraced quickly to see these benefits businesses need to take advantage of this new functionality or risk falling dramatically behind we look forward to a future where humans are a prompt away from creating anything we can imagine unlocking unlimited productivity and creativity the best time to get started on this journey is now and we hope that this guide serves as a stong foundation for that journey start building better ai today book a demo scale ai s logo products scale data engine scale genai platform scale donovan solutions enterprise insurance healthcare us public sector global public sector company about careers security terms privacy modern slavery statement resources blog contact us events documentation data partnerships guides data labeling ml model training diffusion models guide to ai for ecommerce computer vision applications large lan...