controlnet-scribble-sdxl-1.0

Maintainer: xinsir

Total Score

162

Last updated 6/27/2024

💬

PropertyValue
Run this modelRun on HuggingFace
API specView on HuggingFace
Github linkNo Github link provided
Paper linkNo paper link provided

Create account to get full access

or

If you already have an account, we'll log you in

Model overview

The controlnet-scribble-sdxl-1.0 model is a powerful ControlNet that can generate high-resolution images comparable to Midjourney. Developed by xinsir, this model supports any line type and width, allowing users to generate visually appealing images from simple sketches. The model was trained on a large dataset of over 10 million high-quality, carefully captioned images, and employs techniques like data augmentation, multiple loss functions, and multi-resolution training to achieve its impressive performance.

Compared to the controlnet-canny-sdxl-1.0 model, the controlnet-scribble-sdxl-1.0 model has a higher aesthetic score and can generate more visually appealing images if prompted properly. Its control ability is also strong, allowing users to modify the generated images to their liking.

Model inputs and outputs

Inputs

  • Scribble: A hand-drawn monochrome image with white outlines on a black background, representing the desired image to be generated.

Outputs

  • High-resolution image: The generated image based on the input scribble, visually comparable to Midjourney outputs.

Capabilities

The controlnet-scribble-sdxl-1.0 model can generate high-quality, visually appealing images from simple scribble inputs. It outperforms the controlnet-canny-sdxl-1.0 model in terms of aesthetic score and control ability, making it a powerful tool for image generation.

What can I use it for?

The controlnet-scribble-sdxl-1.0 model can be used for a variety of creative projects, such as:

  • Concept art and visual development for games, films, or illustrations
  • Rapid prototyping and ideation for product design
  • Generating unique and visually striking images for social media, marketing, or personal use

The model's ability to generate images from simple scribbles makes it a versatile tool for both professional and amateur artists, allowing them to quickly explore and refine their ideas.

Things to try

One interesting aspect of the controlnet-scribble-sdxl-1.0 model is its ability to generate images from a wide range of scribble inputs, from simple line drawings to more complex, gestural sketches. Try experimenting with different types of scribbles and observe how the model responds, adjusting the prompts and other parameters to fine-tune the generated outputs.

Additionally, you can explore combining the controlnet-scribble-sdxl-1.0 model with other ControlNet models, such as the controlnet-canny-sdxl-1.0 or controlnet-depth models, to see how the different conditioning inputs can be leveraged to create even more complex and compelling images.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

Related Models

📊

controlnet-canny-sdxl-1.0

xinsir

Total Score

110

The controlnet-canny-sdxl-1.0 model, developed by xinsir, is a powerful ControlNet model trained to generate high-resolution images visually comparable to Midjourney. The model was trained on a large dataset of over 10 million carefully filtered and captioned images, and incorporates techniques like data augmentation, multiple loss functions, and multi-resolution training. This model outperforms other open-source Canny-based ControlNet models like diffusers/controlnet-canny-sdxl-1.0 and TheMistoAI/MistoLine. Model inputs and outputs Inputs Canny edge maps**: The model takes Canny edge maps as input, which are generated from the source image. Canny edge detection is a popular technique for extracting the outlines and boundaries of objects in an image. Outputs High-resolution, visually comparable images**: The model outputs high-quality, detailed images that are visually similar to those generated by Midjourney, a popular AI art generation tool. Capabilities The controlnet-canny-sdxl-1.0 model can generate stunning, photorealistic images with intricate details and vibrant colors. The examples provided show the model's ability to create detailed portraits, elaborate fantasy scenes, and even food items like pizzas. The model's performance is particularly impressive given that it was trained on a single stage, without the need for multiple training steps. What can I use it for? This model can be a powerful tool for a variety of applications, such as: Digital art and illustration**: The model can be used to create high-quality, professional-looking digital artwork and illustrations, with a level of detail and realism that rivals human-created work. Product visualization**: The model could be used to generate photorealistic images of products, helping businesses showcase their offerings more effectively. Architectural and interior design**: The model's ability to create detailed, realistic scenes could be useful for visualizing architectural designs or interior spaces. Things to try One interesting aspect of the controlnet-canny-sdxl-1.0 model is its ability to generate images based on a provided Canny edge map. This opens up the possibility of using the model in a more interactive, iterative creative process, where users can refine and manipulate the edge maps to guide the model's output. Additionally, combining this model with other ControlNet checkpoints, such as those for depth, normals, or segmentation, could lead to even more powerful and flexible image generation capabilities.

Read more

Updated Invalid Date

👨‍🏫

anime-painter

xinsir

Total Score

66

The anime-painter model is a powerful AI model developed by xinsir that can generate high-quality anime-style illustrations from simple sketches or scribbles. This model is built upon the ControlNet-scribble-sdxl-1.0 architecture, which has been trained with advanced techniques and a high-quality dataset to achieve state-of-the-art performance. One of the key features of this model is its ability to work with a wide range of line types and widths, allowing users with little to no drawing experience to create beautiful anime-inspired art. The model's prompts can be as simple as a child's doodle or as detailed as a list of Danbooru tags, and it will still generate visually appealing images. Model inputs and outputs Inputs Sketches or scribbles of varying complexity and line quality Danbooru tags to describe the desired content and style of the image Outputs High-quality anime-style illustrations that closely match the provided input sketch or tags Capabilities The anime-painter model excels at generating aesthetically pleasing anime-style images that adhere closely to the provided prompts. Its performance has been evaluated to be better than the original ControlNet-scribble-sdxl-1.0 model, with improvements in areas such as aesthetic score, prompt following ability, and image deformity rate. What can I use it for? The anime-painter model is an excellent tool for those who want to create anime-inspired art but lack the drawing skills or experience. It can be used for a variety of purposes, such as: Generating character designs for personal or commercial projects Creating illustrations for web content, social media, or merchandise Exploring and expanding one's creative imagination through simple sketches or Danbooru tags Things to try To get the most out of the anime-painter model, users should experiment with a variety of input prompts, combining simple sketches with detailed Danbooru tags to see how the model responds. Additionally, tweaking the level of detail in the prompts can help users achieve their desired aesthetic and style.

Read more

Updated Invalid Date

📊

controlnet-openpose-sdxl-1.0

xinsir

Total Score

129

The controlnet-openpose-sdxl-1.0 model is a powerful ControlNet model developed by xinsir that can generate high-resolution images visually comparable to Midjourney. The model was trained on a large dataset of over 10 million carefully filtered and annotated images. It uses useful data augmentation techniques and multi-resolution training to enhance the model's performance. The similar controlnet-canny-sdxl-1.0 and controlnet-scribble-sdxl-1.0 models also show impressive results, with the scribble model being more general and better at generating visually appealing images, while the canny model is stronger at controlling local regions of the generated image. Model inputs and outputs Inputs Image**: The model takes a image as input, which is used as a conditioning signal to guide the image generation process. Prompt**: The model accepts a text prompt that describes the desired output image. Outputs Generated image**: The model outputs a high-resolution image that is visually comparable to Midjourney, based on the provided prompt and conditioning image. Capabilities The controlnet-openpose-sdxl-1.0 model can generate a wide variety of images, from detailed and realistic scenes to fantastical and imaginative concepts. The examples provided show the model's ability to generate images of people, animals, objects, and scenes with a high level of detail and visual appeal. What can I use it for? The controlnet-openpose-sdxl-1.0 model can be used for a variety of creative and practical applications, such as: Art and design**: The model can be used to generate concept art, illustrations, and other visually striking images for use in various media, such as books, games, and films. Product visualization**: The model can be used to create realistic and visually appealing product images for e-commerce, marketing, and other business applications. Educational and scientific visualizations**: The model can be used to generate images that help explain complex concepts or visualize data in an engaging and intuitive way. Things to try One interesting thing to try with the controlnet-openpose-sdxl-1.0 model is to experiment with different types of conditioning images, such as human pose estimation, line art, or even simple scribbles. The model's ability to adapt to a wide range of conditioning signals can lead to unexpected and creative results, allowing users to explore new artistic possibilities. Additionally, users can try combining the controlnet-openpose-sdxl-1.0 model with other AI-powered tools, such as text-to-image generation or image editing software, to create even more sophisticated and compelling visual content.

Read more

Updated Invalid Date

🏷️

sd-controlnet-scribble

lllyasviel

Total Score

50

The sd-controlnet-scribble model is part of the ControlNet family of AI models developed by Lvmin Zhang and Maneesh Agrawala. ControlNet is a neural network structure that can control diffusion models like Stable Diffusion by adding extra conditioning inputs. This specific checkpoint is conditioned on scribble images, which are hand-drawn monochrome images with white outlines on a black background. Similar ControlNet models include the sd-controlnet-canny model, which is conditioned on canny edge detection, and the sd-controlnet-seg model, which is conditioned on image segmentation. These models offer different ways to guide and control the output of the Stable Diffusion text-to-image generation model. Model inputs and outputs Inputs Scribble image**: A hand-drawn monochrome image with white outlines on a black background. Text prompt**: A natural language description of the desired image. Outputs Generated image**: The text-to-image generation output, guided and controlled by the provided scribble image. Capabilities The sd-controlnet-scribble model can generate images based on a text prompt while using the provided scribble image as a guiding condition. This can be useful for tasks like illustrating a concept, creating stylized artwork, or generating images with a specific artistic style. What can I use it for? The sd-controlnet-scribble model can be used for a variety of creative applications, such as: Generating illustrations or concept art based on a written description Creating stylized or abstract images inspired by hand-drawn scribbles Complementing text-based storytelling with visuals Experimenting with different artistic styles and techniques Things to try One interesting aspect of the sd-controlnet-scribble model is its ability to generate images that closely match the style and composition of the input scribble. You can try providing scribbles with different levels of detail, complexity, and abstraction to see how the model responds and how the generated images vary. Additionally, you can experiment with combining the scribble condition with different text prompts to explore the interplay between the guiding visual input and the language-based instructions. This can lead to unexpected and creative results, expanding the potential use cases for the model.

Read more

Updated Invalid Date