Wav2Lip for Automatic1111

🖼️ Tool Name:
Wav2Lip for Automatic1111

🔖 Tool Category:
Generative AI & Media Creation — this tool specializes in AI-powered lip-sync video generation enhanced with Stable Diffusion.

✏️ What does this tool offer?
Wav2Lip for Automatic1111 is an extension for the Stable Diffusion WebUI (specifically Automatic1111) that enables high-quality lip-sync video generation. It allows users to input any video and a separate audio file, then uses the Wav2Lip model to sync the speaker’s lips to the audio. The extension enhances visual quality by refining only the mouth region using Stable Diffusion and ControlNet, producing realistic and visually consistent results.

⭐ What does the tool actually deliver based on user experience?
• Converts any silent or mismatched-lip video into a fully synced talking face
• Generates realistic mouth movements based on the audio input
• Enhances the output with AI-powered image-to-video refinements using Stable Diffusion
• Includes support for advanced features like:

• Multi-face handling

• Keyframe control

• Adjustable lip masks

• Zoom, cropping, and subtitle/audio translation options
  • Easily integrates into the Automatic1111 interface with high user satisfaction

🤖 Does it include automation?
Yes — the tool handles all stages of the lip-syncing process automatically:
• Extracts the mouth region and applies lip motion prediction
• Automatically generates enhanced frames using Stable Diffusion
• Entire process from audio-video input to final enhanced output is automated
• Optional ControlNet settings allow for further visual customization

💰 Pricing Model:
Open-source — completely free

🆓 Free Plan Details:
• Fully free under an open-source license (Apache 2.0 or MIT)
• No subscription, watermarking, or limitations
• Requires installation of dependencies such as FFmpeg and Wav2Lip model weights

💳 Paid Plan Details:
• None — there are no premium versions or commercial plans

🧭 Access Method:
• Available as an extension for the Stable Diffusion WebUI (Automatic1111)
• Requires manual installation via GitHub
• Runs locally on GPU-enabled systems with Automatic1111 setup
• Requires downloading pretrained model weights and placing them in the correct directories

🔗 Experience Link:

https://github.com/numz/sd-wav2lip-uhq