TODO.md

InfiniteTalk Space - Implementation Complete! ✅

Status: READY TO TEST

The inference logic has been fully integrated! The Space now includes:

✅ Completed Integration:

1. ✅ InfiniteTalkPipeline Loading (utils/model_loader.py)

   • Properly initializes wan.InfiniteTalkPipeline
   • Downloads models from HuggingFace Hub
   • Configures for single-GPU ZeroGPU environment

2. ✅ Audio Processing (app.py)

   • loudness_norm() function for audio normalization
   • process_audio() matches reference implementation
   • Proper 16kHz resampling

3. ✅ Audio Embedding Extraction (app.py)

   • Wav2Vec2 feature extraction
   • Hidden state stacking
   • Correct tensor reshaping with einops

4. ✅ Video Generation (app.py)

   • Calls generate_infinitetalk() with proper parameters
   • Handles both image-to-video and video dubbing
   • Uses save_video_ffmpeg() for output

5. ✅ Memory Management

   • GPU cleanup after generation
   • ZeroGPU duration calculation
   • Memory monitoring

Reference Files to Study:

1. temp-infinitetalk/generate_infinitetalk.py - Main inference logic
2. temp-infinitetalk/app.py - Original Gradio implementation
3. wan/multitalk.py - Model inference
4. wan/utils/multitalk_utils.py - Utility functions

Testing Checklist:

• Models download correctly from HuggingFace Hub
• Image input is properly processed
• Video input is properly processed
• Audio features are extracted correctly
• Video generation completes without OOM errors
• Output video has correct lip-sync
• Memory is cleaned up after generation
• Multiple generations work in sequence

Optional Enhancements (Future):

• Add Text-to-Speech (kokoro integration)
• Add multi-person mode support
• Add progress bar for long videos
• Add video preview before generation
• Add batch processing
• Add custom LoRA support
• Add video quality comparison slider

Known Issues:

1. Flash-attn compilation: May fail on some systems
   • Solution: Use pre-built wheels or Dockerfile
2. Model download time: First run takes 2-3 minutes
   • Expected behavior with 15GB+ models
3. ZeroGPU timeout: Long videos may exceed quota
   • Solution: Implement chunking or recommend shorter inputs

Deployment Notes:

See DEPLOYMENT.md for step-by-step deployment instructions.