5 (512x512) and SD2. 0 has proclaimed itself as the ultimate image generation model following rigorous testing against competitors. Official list of SDXL resolutions (as defined in SDXL paper). SDXL represents a landmark achievement in high-resolution image synthesis. Issue is that my local images are not even close to those from online. 9 the latest Stable. Most. It’s designed for professional use, and calibrated for high-resolution photorealistic images. 5 and 2. Just like its predecessors, SDXL has the ability to generate image variations using image-to-image prompting, inpainting (reimagining of the selected. The SDXL uses Positional Encoding. SDXL 0. "," "," "," "," Image Dimensions "," "," Stable Diffusion was trained with base dimensions of 512 pixels (SD 1. 9 pour faire court, est la dernière mise à jour de la suite de modèles de génération d'images de Stability AI. We design multiple novel conditioning schemes and train SDXL on multiple. Using the SDXL base model on the txt2img page is no different from using any other models. Of course I'm using quite optimal settings like prompt power at 4-8, generation steps between 90-130 with different samplers. huggingface. My full args for A1111 SDXL are --xformers --autolaunch --medvram --no-half. g. SDXL Base model and Refiner. resolutions = [ # SDXL Base resolution {"width": 1024, "height": 1024}, # SDXL Resolutions, widescreen {"width": 2048, "height": 512}, {"width": 1984, "height": 512}, {"width": 1920, "height": 512}, {"width": 1856, "height": 512}, {"width": 1792, "height": 576}, {"width. Pass that to another base ksampler. I haven't seen anything that makes the case. eg Openpose is not SDXL ready yet, however you could mock up openpose and generate a much faster batch via 1. , a woman in. Resolutions: Standard SDXL resolution💻 How to prompt with reality check xl. 5 models). "Annotator resolution" is used by the preprocessor to scale the image and create a larger, more detailed detectmap at the expense of VRAM or a smaller, less VRAM intensive detectmap at the. Sampling sharpness is developed by Fooocus as a final solution to the problem that SDXL sometimes generates overly smooth images or images with plastic appearance. The SDXL base checkpoint can be used like any regular checkpoint in ComfyUI. Select base SDXL resolution, width and height are returned as INT values which can be connected to latent image inputs or other inputs such as the CLIPTextEncodeSDXL width, height,. SDXL or Stable Diffusion XL is an advanced model developed by Stability AI that allows high-resolution AI image synthesis and enables local machine execution. fix use. 5 however takes much longer to get a good initial image. It is a more flexible and accurate way to control the image generation process. Just like its predecessors, SDXL has the ability to generate image variations using image-to-image prompting, inpainting (reimagining. To learn how to use SDXL for various tasks, how to optimize performance, and other usage examples, take a look at the Stable Diffusion XL guide. 5 with Base or Custom Asset (Fine-tuned) 30: 512x512: DDIM (and any not listed. target_height (actual resolution) Resolutions by Ratio: Similar to Empty Latent by Ratio, but returns integer width and height for use with other nodes. The smallest resolution in our dataset is 1365x2048, but many images go up to resolutions as high as 4622x6753. Unfortunately, using version 1. 0 model. 5 in sd_resolution_set. Its not a binary decision, learn both base SD system and the various GUI'S for their merits. 5 model which was trained on 512×512 size images, the new SDXL 1. json file already contains a set of resolutions considered optimal for training in SDXL. However, you can still change the aspect ratio of your images. The number 1152 must be exactly 1152, not 1152-1, not 1152+1, not 1152-8, not 1152+8. Originally Posted to Hugging Face and shared here with permission from Stability AI. safetensors in general since the 1. We generated each image at 1216 x 896 resolution, using the base model for 20 steps, and the refiner model for 15 steps. Not really. 0 or higher. We present SDXL, a latent diffusion model for text-to-image synthesis. 9 the refiner worked better. 5 model we'd sometimes generate images of heads/feet cropped out because of the autocropping to 512x512 used in training images. 256x512 1:2. (2) Even if you are able to train at this setting, you have to notice that SDXL is 1024x1024 model, and train it with 512 images leads to worse results. 5 models. ) Stability AI. SDXL can render some text, but it greatly depends on the length and complexity of the word. For SD1. SDXL is a cutting-edge diffusion-based text-to-image generative model designed by Stability AI. 8), (perfect hands:1. I highly recommend it. Some users have specific goals and preferences. ; Added ability to stop image generation. Below are the presets I use. Below you can see a full list of aspect ratios and resolutions represented in the training dataset: Stable Diffusion XL Resolutions. Galactic Gemstones in native 4K with SDXL! Just playing around with SDXL again, I thought I’d see how far I can take the resolution without any upscaling and 4K seemed like the reasonable limit. This tutorial is based on the diffusers package, which does not support image-caption datasets for. The model is capable of generating images with complex concepts in various art styles, including photorealism, at quality levels that exceed the best image models available today. According to many references, it's advised to avoid arbitrary resolutions and stick to this initial resolution, as SDXL was trained using this specific resolution. You should NOT generate images with width and height that deviates too much from 512 pixels. There were series of SDXL models released: SDXL beta, SDXL 0. DreamStudio offers a limited free trial quota, after which the account must be recharged. Detailed Explanation about SDXL sizes and where to use each size. So I researched and found another post that suggested downgrading Nvidia drivers to 531. "medium close-up of a beautiful woman in a purple dress dancing in an ancient temple, heavy rain. 5 model which was trained on 512×512 size images, the new SDXL 1. Following the above, you can load a *. 0 base model as of yesterday. Here are the image sizes that are used in DreamStudio, Stability AI’s official image generator: 21:9 – 1536 x 640; 16:9 – 1344 x 768; 3:2 – 1216 x 832; 5:4 – 1152 x 896; 1:1 – 1024 x. json file during node initialization, allowing you to save custom resolution settings in a separate file. Official list of SDXL resolutions (as defined in SDXL paper). Stable Diffusion XL. Part 2 (this post)- we will add SDXL-specific conditioning implementation + test what impact that conditioning has on the generated images. 1 latent. tile diffusion helps, there are couple of upscaler models out there that are good for certain. Le Communiqué de presse sur SDXL 1. One of the common challenges faced in the world of AI-generated images is the inherent limitation of low resolution. 0 particularly excels in vibrant and accurate color rendition, boasting improvements in contrast, lighting, and shadows compared to its predecessor, all in a 1024x1024 resolution. 5 to SDXL cause the latent spaces are different. Proposed. ; Use --cache_text_encoder_outputs option and caching latents. Compact resolution and style selection (thx to runew0lf for hints). 5 for 6 months without any problem. 896 x 1152 - 7:9. Remember to verify the authenticity of the source to ensure the safety and reliability of the download. That way you can create and refine the image without having to constantly swap back and forth between models. 5 model and is released as open-source software. Some models aditionally have versions that require smaller memory footprints, which make them more suitable to be. Those extra parameters allow SDXL to generate images that more accurately adhere to complex. I'm super excited for the upcoming weeks and months on what the wider community will come up with in terms of additional fine tuned models. Support for custom resolutions - you can just type it now in Resolution field, like "1280x640". Before running the scripts, make sure to install the library's training dependencies: . From these examples, it’s clear to see that the quality is now on par with MidJourney. The point is that it didn't have to be this way. SDXL 1. 5/2. 5 and 2. Ouverture de la beta de Stable Diffusion XL. Static Engines can only be configured to match a single resolution and batch size. 0. Two switches, two. Abstract and Figures. Updated 4. If you want to switch back later just replace dev with master . AI_Alt_Art_Neo_2. The beta version of Stability AI’s latest model, SDXL, is now available for preview (Stable Diffusion XL Beta). If you choose to use a lower resolution, such as <code> (256, 256)</code>, the model still generates 1024x1024 images, but they'll look like the low resolution images (simpler. The default resolution of SDXL is 1024x1024. Description: SDXL is a latent diffusion model for text-to-image synthesis. Dynamic engines generally offer slightly. The only important thing is that for optimal performance the resolution should be set to 1024x1024 or other resolutions with the same amount of pixels but a different aspect ratio. 9 en détails. In the 1. ; Updated Comfy. . 5 models for refining and upscaling. The workflow also has TXT2IMG, IMG2IMG, up to 3x IP Adapter, 2x Revision, predefined (and editable) styles, optional up-scaling, Control Net Canny, Control Net Depth, Lora, selection of recommended SDXL resolutions, adjusting input images to the closest SDXL resolution, etc. 5 LoRAs I trained on this dataset had pretty bad-looking sample images, too, but the LoRA worked decently considering my dataset is still small. To use the Stability. json - use resolutions-example. According to many references, it's advised to avoid arbitrary resolutions and stick to this initial resolution, as SDXL was trained using this specific resolution. Compared to previous versions of Stable Diffusion, SDXL leverages a three times larger. 9. 9) The SDXL series also offers various. 5. A very nice feature is defining presets. Also memory requirements—especially for model training—are disastrous for owners of older cards with less VRAM (this issue will disappear soon as better cards will resurface on second hand. As the newest evolution of Stable Diffusion, it’s blowing its predecessors out of the water and producing images that are competitive with black-box. 9 espcially if you have an 8gb card. SDXL was trained on a lot of 1024x1024 images so this shouldn't happen on the recommended resolutions. 1024x1024 gives the best results. It is convenient to use these presets to switch between image sizes. What is the SDXL model The SDXL model is the official upgrade to the v1. Stable Diffusion 2. 1 (768x768): SDXL Resolution Cheat Sheet and SDXL Multi-Aspect Training. If the training images exceed the resolution specified here, they will be scaled down to this resolution. 16GB VRAM can guarantee you comfortable 1024×1024 image generation using the SDXL model with the refiner. The training is based on image-caption pairs datasets using SDXL 1. People who say "all resolutions around 1024 are good" do not understand what is Positional Encoding. Additionally, it accurately reproduces hands, which was a flaw in earlier AI-generated images. 5)This capability, once restricted to high-end graphics studios, is now accessible to artists, designers, and enthusiasts alike. Replicate was ready from day one with a hosted version of SDXL that you can run from the web or using our cloud API. That's all this node does: Select one of the officially supported resolutions and switch between horizontal and vertical aspect ratios. For those eager to dive deeper into the specifications and testing of this model, the SDXL team will soon release a research blog providing comprehensive insights. Control Nets are compatible with SDXL, but you’ll have to download the SDXL-specific models. 0 is an open-source diffusion model, the long waited upgrade to Stable Diffusion v2. SDXL can generate images in different styles just by picking a parameter. . The default resolution of SDXL is 1024x1024. Unlike other models that require extensive instructions to produce. timchenw • 5 yr. Compared to other leading models, SDXL shows a notable bump up in quality overall. mo pixels, mo problems — Stability AI releases Stable Diffusion XL, its next-gen image synthesis model New SDXL 1. You may want to try switching to the sd_xl_base_1. Not the fastest but decent. Docker image for Stable Diffusion WebUI with ControlNet, After Detailer, Dreambooth, Deforum and roop extensions, as well as Kohya_ss and ComfyUI. It's similar to how 1. Specific Goals and Preferences: Not everyone is aiming to create MidJourney-like images. ago RangerRocket09 SDXL and low resolution images Question | Help Hey there. Overall, SDXL 1. The number 1152 must be exactly 1152, not 1152-1, not 1152+1, not 1152-8, not 1152+8. Thanks. Example SDXL 1. SDXL 0. 9: The weights of SDXL-0. Use the following size settings to generate the initial image. when fine-tuning SDXL at 256x256 it consumes about 57GiB of VRAM at a batch size of 4. We present SDXL, a latent diffusion model for text-to-image synthesis. License: SDXL 0. So I won't really know how terrible it is till it's done and I can test it the way SDXL prefers to generate images. 9 runs on consumer hardware but can generate "improved image and composition detail," the company said. For frontends that don't support chaining models like this, or for faster speeds/lower VRAM usage, the SDXL base model alone can still achieve good results: The refiner has only been trained to denoise small noise levels, so. 0 is miles ahead of SDXL0. Stable Diffusion XL (SDXL) is a powerful text-to-image generation model that iterates on the previous Stable Diffusion models in three key ways: the UNet is 3x larger and SDXL combines a second text encoder (OpenCLIP ViT-bigG/14) with the original text encoder to significantly increase the number of parameters. SDXL 1. SDXL v0. The new version generates high-resolution graphics while using less processing power and requiring fewer text inputs. 3 (I found 0. "medium close-up of a beautiful woman in a purple dress dancing in an ancient temple, heavy rain. 5 (512x512) and SD2. August 21, 2023 · 11 min. Until models in SDXL can be trained with the SAME level of freedom for pron type output, SDXL will remain a haven for the froufrou artsy types. model_id: sdxl. For example: 896x1152 or 1536x640 are good resolutions. For Interfaces/Frontends ComfyUI (with various addons) and SD. 0, anyone can now create almost any image easily and. 43 MRE ; Added support for Control-LoRA: Depth. Big shoutout to CrystalClearXL for the inspiration. A non-overtrained model should work at CFG 7 just fine. SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis. Make sure to load the Lora. (6) Hands are a big issue, albeit different than in earlier SD versions. This powerful text-to-image generative model can take a textual description—say, a golden sunset over a tranquil lake—and render it into a. . Your LoRA will be heavily influenced by the base model, so you should use one that produces the style of images that you would like to create. Klash_Brandy_Koot • 3 days ago. resolution — The resolution for input images, all the images in the train/validation datasets will be resized to this. 5 billion-parameter base model. 0 outshines its predecessors and is a frontrunner among the current state-of-the-art image generators. 0: a semi-technical introduction/summary for beginners (lots of other info about SDXL there): . Gradient checkpointing enabled, adam8b, constant scheduler, 24 dim and. Yes the model is nice, and has some improvements over 1. SDXL for A1111 Extension - with BASE and REFINER Model support!!! This Extension is super easy to install and use. In ComfyUI this can be accomplished with the output of one KSampler node (using SDXL base) leading directly into the input of another KSampler node (using. fix) 11:04 Hires. This script can be used to generate images with SDXL, including LoRA, Textual Inversion and ControlNet-LLLite. This substantial increase in processing power enables SDXL 0. Cette version a pu bénéficier de deux mois d’essais et du. Description: SDXL is a latent diffusion model for text-to-image synthesis. 6B parameters vs SD 2. But why tho. The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant time, depending on your internet. g. 0 is engineered to perform effectively on consumer GPUs with 8GB VRAM or commonly available cloud instances. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. 6 billion, compared with 0. Stable Diffusion XL SDXL 1. 1's 860M parameters. However in SDXL, I'm getting weird situations where torsos and necks are elongated. The only important thing is that for optimal performance the resolution should be set to 1024x1024 or other resolutions with the same amount of pixels but a different aspect ratio. ; Added Canny and Depth model selection. ago. But that's not even the point. They are just not aware of the fact that SDXL is using Positional Encoding. " Note the vastly better quality, much lesser color infection, more detailed backgrounds, better lighting depth. 8 million steps, we’ve put in the work. With 4 times more pixels, the AI has more room to play with, resulting in better composition and. I always use 3 as it looks more realistic in every model the only problem is that to make proper letters with SDXL you need higher CFG. when you increase SDXL's training resolution to 1024px, it then consumes 74GiB of VRAM. stability-ai / sdxl A text-to-image generative AI model that creates beautiful images Public; 20. ; Added support for generate forever mode (ported from SD web UI). Unlike the previous SD 1. The release went mostly under-the-radar because the generative image AI buzz has cooled. 0 version. 2. panchovix. BEHOLD o (￣ ￣)d AnimateDiff video tutorial: IPAdapter (Image Prompts), LoRA, and Embeddings. If you find my work useful / helpful, please consider supporting it – even $1 would be nice :). Style Aspect ratio Negative prompt Version PRO. 5 stuff like ControlNet, ADetailer, Roop and trained models that aren't afraid to draw a nipple to go back to using. Disclaimer: Even though train_instruct_pix2pix_sdxl. 9)" Enhancing the Resolution of AI-Generated Images. If you choose to use a lower resolution, such as <code> (256, 256)</code>, the model still generates 1024x1024 images, but they'll look like the low resolution images (simpler patterns, blurring) in the dataset. bat and start to enjoy a new world of crazy resolutions without lossing speed at low resolutions. We design. this is at a mere batch size of 8. The codebase starts from an odd mixture of Stable Diffusion web UI and ComfyUI. 5 in every aspect other than resolution. "1920x1080" for original_resolution and "-1" for aspect would give an aspect ratio of 16/9, or ~1. Set the resolution to 1024x1024 or one of the supported resolutions ( - 1024 x 1024, 1152 x 896, 896 x 1152, 1216 x 832, 832 x 1216, 1344 x 768, 768 x 1344, 1536 x 640, 640 x 1536. 16. 0 emerges as the world’s best open image generation model, poised. Granted, it covers only a handful of all officially supported SDXL resolutions, but they're the ones I like the most. Stable Diffusion XL has brought significant advancements to text-to-image and generative AI images in general, outperforming or matching Midjourney in many aspects. For comparison, Juggernaut is at 600k. Like SD 1. I run it following their docs and the sample validation images look great but I’m struggling to use it outside of the diffusers code. 9 models in ComfyUI and Vlad's SDnext. 92 seconds on an A100: Cut the number of steps from 50 to 20 with minimal impact on results quality. 0. It will work. b. 12700k cpu For sdxl, I can generate some 512x512 pic but when I try to do 1024x1024, immediately out of memory. . . json - use resolutions-example. When creating images with Stable Diffusion, one important consideration is the image size or resolution. Enlarged 128x128 latent space (vs SD1. The original dataset is hosted in the ControlNet repo. Support for custom resolutions list (loaded from resolutions. Added support for custom resolutions and custom resolutions list. 🟠 generation resolution directly derived from the quality of the dataset. strict_bucketing matches your gen size to one of the bucket sizes explicitly given in the SDXL report (or to those recommended by the ComfyUI developer). Resolution: 1024 x 1024; CFG Scale: 11; SDXL base model only image. For best results, keep height and width at 1024 x 1024 or use resolutions that have the same total number of pixels as 1024*1024 (1048576 pixels) Here are some examples: 896 x 1152; 1536 x 640 SDXL is often referred to as having a 1024x1024 preferred resolutions. Bien que les résolutions et ratios ci-dessus soient recommandés, vous pouvez également essayer d'autres variations. py script shows how to implement the training procedure and adapt it for Stable Diffusion XL. 5. 🟠 the community gathered around the creators of Midjourney. SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis. A Faster and better training recipe: In our previous version, training directly at a resolution of 1024x1024 proved to be highly inefficient. SDXL does support resolutions for higher total pixel values, however res. Better Tools for Animation in SD 1. sdxl-recommended-res-calc. Step 5: Recommended Settings for SDXL. Important To make full use of SDXL, you'll need to load in both models, run the base model starting from an empty latent image, and then run the refiner on the base model's output to improve detail. Developed by Stability AI, SDXL 1. The new version generates high-resolution graphics while using less processing power and requiring fewer text inputs. Most of the time it looks worse than SD2. 0 release allows hi-res AI image synthesis that can run on a local machine. 9 models in ComfyUI and Vlad's SDnext. 0 as the base model. upon loading up sdxl based 1. One of the common challenges faced in the world of AI-generated images is the inherent limitation of low resolution. orgI had a similar experience when playing with the leaked SDXL 0. py implements the InstructPix2Pix training procedure while being faithful to the original implementation we have only tested it on a small-scale. 5 to get their lora's working again, sometimes requiring the models to be retrained from scratch. json - use resolutions-example. 7gb without generating anything. 5, having found the prototype your looking for then img-to-img with SDXL for its superior resolution and finish. You can change the point at which that handover happens, we default to 0. 5, SDXL is flexing some serious muscle—generating images nearly 50% larger in resolution vs its predecessor without breaking a sweat. I recommend any of the DPM++ samplers, especially the DPM++ with Karras samplers. A custom node for Stable Diffusion ComfyUI to enable easy selection of image resolutions for SDXL SD15 SD21. In addition to this, with the release of SDXL, StabilityAI have confirmed that they expect LoRA's to be the most popular way of enhancing images on top of the SDXL v1. But what about portrait or landscape ratios? Hopefully 1024 width or height won't be the required minimum, or it would involve a lot of VRAM consumption. When setting resolution you have to do multiples of 64 which make it notoriously difficult to find proper 16:9 resolutions. This is by far the best workflow I have come across. My goal is to create a darker, grittier model. . What makes it exceptional is its acute attention to detail – vibrant colors, accurate contrast, impeccable lighting, and realistic shadows, all rendered in a native 1024×1024 resolution. UPDATE 1: this is SDXL 1. The default is "512,512". but I'm just too used to having all that great 1. SDXL 1. 5 had. Model Description: This is a model that can be used to generate and modify images based on text prompts. 9) The SDXL series also offers various functionalities extending beyond basic text prompting. WebUIのモデルリストからSDXLを選択し、生成解像度を1024に設定、SettingsにVAEを設定していた場合はNoneに設定します。. During processing it all looks good. (As a sample, we have prepared a resolution set for SD1. But SDXL. darkside1977 • 2 mo. 1 NSFW - not demonstrated Will be adopted and improved by community - that's an admission XL sucks. With native 1024×1024 resolution, the generated images are detailed and visually stunning. SDXL represents a landmark achievement in high-resolution image synthesis. 5 I added the (masterpiece) and (best quality) modifiers to each prompt, and with SDXL I added the offset lora of . 5 Billion parameters, SDXL is almost 4 times larger than the original Stable Diffusion model, which only had 890 Million parameters. To associate your repository with the sdxl topic, visit your repo's landing page and select "manage topics. select the SDXL base model from the dropdown. 0 model to your device. SDXL 1. 9: The base model was trained on a variety of aspect ratios on images with resolution 1024^2. ago. With 3. Start Training. 9 uses two CLIP models, including the largest OpenCLIP model to date. The SDXL base checkpoint can be used like any regular checkpoint in ComfyUI. He puts out marvelous Comfyui stuff but with a paid Patreon. 0, an open model representing the next evolutionary step in text-to-image generation models. The purpose of DreamShaper has always been to make "a better Stable Diffusion", a model capable of doing everything on its own, to weave dreams. This is just a simple comparison of SDXL1. 9, which generates significantly improved image and composition details over its predecessor. 9 and Stable Diffusion 1. It can handle dimensions outside this range, but doesn't do well much smaller than 768x768 in my experience. It’s significantly better than previous Stable Diffusion models at realism. Dhanshree Shripad Shenwai. It takes just under 2 minutes to render an image and starts to lag my PC when it begins decoding it. Using ComfyUI with SDXL can be daunting at first if you have to come up with your own workflow. 1024x1024 is just the resolution it was designed for, so it'll also be the resolution which achieves the best results. Compared to previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone: The increase of model parameters is mainly due to more attention blocks and. SDXL artifacting after processing? I've only been using SD1. Stable Diffusion XL, également connu sous le nom de SDXL, est un modèle de pointe pour la génération d'images par intelligence artificielle créé par Stability AI. Stable Diffusion’s native resolution is 512×512 pixels for v1 models. Tap into a larger ecosystem of custom models, LoRAs and ControlNet features to better target the. 8M runs GitHub Paper License Demo API Examples README Train Versions (39ed52f2) Examples. I made a handy cheat sheet and Python script for us to calculate ratios that fit this guideline. The base model uses OpenCLIP-ViT/G and CLIP-ViT/L for text encoding whereas the refiner model only uses the OpenCLIP model. 0 is latest AI SOTA text 2 image model which gives ultra realistic images in higher resolutions of 1024. It’ll be faster than 12GB VRAM, and if you generate in batches, it’ll be even better. In my PC, yes ComfyUI + SDXL also doesn't play well with 16GB of system RAM, especialy when crank it to produce more than 1024x1024 in one run. Sped up SDXL generation from 4 mins to 25 seconds! r/StableDiffusion • Massive SDNext update. 0), one quickly realizes that the key to unlocking its vast potential lies in the art of crafting the perfect prompt. All prompts share the same seed. The below settings for width and height are optimal for use on SDXL 1. 5 is Haveall, download Safetensors file and put into ComfyUImodelscheckpointsSDXL and ComfyUImodelscheckpointsSD15 )SDXL Report (official) Summary: The document discusses the advancements and limitations of the Stable Diffusion (SDXL) model for text-to-image synthesis. Skeleton man going on an adventure in the foggy hills of Ireland wearing a cape. Compact resolution and style selection (thx to runew0lf for hints). eg Openpose is not SDXL ready yet, however you could mock up openpose and generate a much faster batch via 1. some stupid scripting workaround to fix the buggy implementation and to make sure it redirects you to the actual full resolution original images (which are PNGs in this case), otherwise it. The input images are shrunk to 768x to save VRAM, and SDXL handles that with grace (it's trained to support dynamic resolutions!). Compact resolution and style selection (thx to runew0lf for hints).