Leffa : Controllable character image generation model

Leffa

AI design tools Image generation #Image Generation #Virtual Fitting #Pose Transfer #Diffusion Models #Model Agnosticism Standard Picks Open Source

Overview :

Leffa is a unified framework for controllable character image generation that allows for precise control over character appearance (e.g., virtual fitting) and pose (e.g., pose transfer). The model minimizes detail distortion and maintains high image quality by guiding target queries to relevant areas in the reference images during training. Key advantages of Leffa include model agnosticism, enabling performance enhancement of other diffusion models.

Target Users :

Target audience includes researchers and developers in the image generation field, especially those requiring precise control over character images for applications such as virtual fitting and pose estimation. Leffa is highly suitable for users looking to innovate and research in these areas due to its high-quality image generation and pose control capabilities.

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Use Cases

Using Leffa for virtual fitting, users can upload their own images, and the model will generate images with various clothing options.

In film production, Leffa can be used to generate character images in specific poses, reducing the cost and time of actual filming.

In fashion design, designers can utilize Leffa to preview how clothing designs appear on different models.

Features

- Appearance control (virtual fitting): Generates character images based on reference images with precise control over appearance.

- Pose control (pose transfer): Transfers one pose to another for accurate pose control.

- Reduces detail distortion: Minimizes distortion of details from reference images while maintaining high image quality.

- Model agnosticism: The loss function of Leffa can enhance the performance of other diffusion models.

- High-quality image generation: Achieved through a diffusion baseline, producing images of superior quality.

- Visual result comparison: Leffa significantly reduces detail distortion while generating high-quality images compared to other methods.

- Community discussion: Provides a forum for user interaction and feedback.

- Code and model evaluation: Supplies code for model evaluation, facilitating performance testing.

How to Use

1. Create and activate the conda environment: Use the conda command to create an environment named 'leffa' and activate it.

2. Install dependencies: In the Leffa directory, use pip to install the dependencies listed in requirements.txt.

3. Run the Gradio application: Enter 'python app.py' in the terminal to launch Leffa's Gradio application.

4. Upload reference images: On the Gradio application interface, upload reference images for controlling character appearance or pose.

5. Select control options: Choose between appearance control or pose control as needed.

6. Generate images: Click the generate button, and Leffa will create new character images based on the uploaded reference images and selected control options.

7. Download or share results: The generated images can be downloaded or shared for further applications or research.