FaceChain

Preview：

Introduce：

FaceChain is a deep learning tool chain powered by ModelScope that can generate your digital twin from at least 1 portrait photo and generate a personal portrait in different Settings (multiple styles supported). Users can train the digital twin and generate photos through FaceChain’s Python scripts, the familiar Gradio interface, or the sd webui. Key benefits of FaceChain include its ability to generate personalized portraits, support for multiple styles, and an easy-to-use interface.

Stakeholders:

Usage Scenario Examples:

• Use FaceChain to generate personal portraits and use them for personal branding.
• Create a virtual fitting experience for users on an e-commerce site.
• Generate unique art portraits on social media.

The features of the tool:

• Generate a personal digital twin: Generate a digital twin of the user from at least 1 portrait photo.
• Multiple styles supported: Users can create personal portraits in a variety of styles.
• Python Scripting support: Python scripting is provided to train and generate digital twins.
• Gradio interface: Simplify model training and generation with the Gradio interface.
• sd webui support: Allows users to directly experience FaceChain on the sd webui.
• Virtual fitting module: New function to enhance user experience.
• Super resolution support: provides multiple resolution options to enhance image detail.

Steps for Use:

• Step 1: Visit FaceChain’s GitHub page and clone the project locally.
• Step 2: Set up the environment according to the installation guide, including the Python version, PyTorch version, and CUDA version.
• Step 3: Install the necessary dependencies, such as Gradio, controlnet_aux, etc.
• Step 4: Run alili.liy to launch the application service and upload at least one picture with a clear face to start training.
• Step 5: After the training is complete, use the generated model to generate the digital twin.
• Step 6: Under the ‘Image Exlierience’ TAB click ‘Start Inference’ to generate personal digital images.

Tool’s Tabs: Deep learning, digital twins