FaceSwap-WebUI

Extract face frames from the dubbed actor.

Train a model on the original lead actor's face.

Apply the swap to the dubbed footage.

Use XSeg to mask out foreground microphone stands or clothing.

Render final 10-bit color depth video for finishing.

Find high-resolution reference photos of the historical figure.

Train a 'Heavy' model using the high-res references as the source.

Extract grainy frames from the archival target.

Perform a conversion to 'project' the high-res details onto the old footage.

Apply GAN refinement for skin texture.

Create a synthetic 'Master Avatar' face.

Record the training session with a volunteer employee.

Run the automated FaceSwap-WebUI batch converter.

Replace the employee's face with the synthetic avatar.

Distribute the video globally with zero PII risk.

Capture multi-angle footage of the lead actor.

Train a Villain-class model for 100k+ iterations.

Track the stunt performer's face in the action sequence.

Execute conversion with motion-blur compensation enabled.

Finalize via Temporal Smoothing.

Gather dataset of character frames from source media.

Extract own face as the target.

Train a model to map character features to own facial movements.

Convert footage using 'Seamless' blending.

Export for social media sharing.

Swap one identity onto 1000 different source videos of varying expressions.

Use the output as a consistent identity dataset for emotion analysis.

Automate the process via the CLI script interface.

Train model on new spokesperson.

Batch convert old archive videos.

Maintain background and environment while changing the identity.

Update audio via separate AI voice-cloning tools.