mo-di-diffusion on Hugging Face vs Drag Your GAN

Compare mo-di-diffusion on Hugging Face vs Drag Your GAN and see which AI Image Generation Model tool is better when we compare features, reviews, pricing, alternatives, upvotes, etc.

Which one is better? mo-di-diffusion on Hugging Face or Drag Your GAN?

When we compare mo-di-diffusion on Hugging Face with Drag Your GAN, which are both AI-powered image generation model tools, The community has spoken, Drag Your GAN leads with more upvotes. The number of upvotes for Drag Your GAN stands at 8, and for mo-di-diffusion on Hugging Face it's 6.

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mo-di-diffusion on Hugging Face

mo-di-diffusion on Hugging Face

What is mo-di-diffusion on Hugging Face?

Discover the world of artificial intelligence and image generation with nitrosocke/mo-di-diffusion, an advanced model designed to bring your creative visions to life. Housed within the innovative ecosystem of Hugging Face, this fine-tuned Stable Diffusion 1.5 tool is your gateway to producing captivating visual content. Leveraging screenshots from a renowned animation studio, the model provides a distinctive 'modern disney style' that adds a magical twist to your generated images. Whether you're creating videogame characters, animal motifs, or enchanting landscapes, mo-di-diffusion transforms simple text prompts into stunning pieces of art. Offering both a sophisticated API and user-friendly interfaces, Hugging Face ensures seamless access to this creative powerhouse. Dive into the simplicity of AI-driven image generation where your imagination meets open-source technology – the perfect solution for artists, developers, and content creators.

Drag Your GAN

Drag Your GAN

What is Drag Your GAN?

In the realm of synthesizing visual content to meet users' needs, achieving precise control over pose, shape, expression, and layout of generated objects is essential. Traditional approaches to controlling generative adversarial networks (GANs) have relied on manual annotations during training or prior 3D models, often lacking the flexibility, precision, and versatility required for diverse applications.

In our research, we explore an innovative and relatively uncharted method for GAN control – the ability to "drag" specific image points to precisely reach user-defined target points in an interactive manner (as illustrated in Fig.1). This approach has led to the development of DragGAN, a novel framework comprising two core components:

Feature-Based Motion Supervision: This component guides handle points within the image toward their intended target positions through feature-based motion supervision.

Point Tracking: Leveraging discriminative GAN features, our new point tracking technique continuously localizes the position of handle points.

DragGAN empowers users to deform images with remarkable precision, enabling manipulation of the pose, shape, expression, and layout across diverse categories such as animals, cars, humans, landscapes, and more. These manipulations take place within the learned generative image manifold of a GAN, resulting in realistic outputs, even in complex scenarios like generating occluded content and deforming shapes while adhering to the object's rigidity.

Our comprehensive evaluations, encompassing both qualitative and quantitative comparisons, highlight DragGAN's superiority over existing methods in tasks related to image manipulation and point tracking. Additionally, we demonstrate its capabilities in manipulating real-world images through GAN inversion, showcasing its potential for various practical applications in the realm of visual content synthesis and control.

mo-di-diffusion on Hugging Face Upvotes

6

Drag Your GAN Upvotes

8🏆

mo-di-diffusion on Hugging Face Top Features

  • Fine-Tuned AI Model: Utilize a specialized Stable Diffusion model trained with unique animation studio art.

  • Custom Styles: Easily incorporate a 'modern disney style' into your images with targeted text prompts.

  • Accessible Tools: Integrate with the model via Diffusers library or explore with Gradio Web UI and Colab notebooks.

  • Open Access License: Use the model with the assurance of CreativeML's OpenRAIL-M licensing.

  • Export Capabilities: Flexibility to export the model to various formats including ONNX MPS and FLAX/JAX.

Drag Your GAN Top Features

No top features listed

mo-di-diffusion on Hugging Face Category

    Image Generation Model

Drag Your GAN Category

    Image Generation Model

mo-di-diffusion on Hugging Face Pricing Type

    Freemium

Drag Your GAN Pricing Type

    Free

mo-di-diffusion on Hugging Face Tags

Creative AI
Image Generation
Open Source
Modern Disney Style
AI Art

Drag Your GAN Tags

GANs
Feature-based motion supervision
Point tracking
Image synthesis
Visual content manipulation
Image deformations
Realistic outputs
Machine learning research
Computer vision
Image processing
GAN inversion
By Rishit