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TODO.md
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# InfiniteTalk Space -
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##
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The
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###
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# Replace with actual inference code from generate_infinitetalk.py
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# Key steps:
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# 1. Load/prepare input frames
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# 2. Extract and process audio features
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# 3. Run diffusion model with audio conditioning
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# 4. Post-process and save video
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```
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#### 4. Audio Feature Extraction
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Ensure the audio feature extraction matches InfiniteTalk's requirements:
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- Check if Wav2Vec2 preprocessing is correct
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- Verify audio normalization parameters
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- Confirm sample rate (16kHz)
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#### 5. Video Assembly
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Implement the video assembly logic:
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- Frame generation loop
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- Streaming/chunking for long videos
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- FFmpeg video encoding
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- Audio merging
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### Reference Files to Study:
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# InfiniteTalk Space - Implementation Complete! ✅
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## Status: READY TO TEST
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The inference logic has been fully integrated! The Space now includes:
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### ✅ Completed Integration:
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1. **✅ InfiniteTalkPipeline Loading** ([utils/model_loader.py](utils/model_loader.py:107))
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- Properly initializes `wan.InfiniteTalkPipeline`
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- Downloads models from HuggingFace Hub
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- Configures for single-GPU ZeroGPU environment
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2. **✅ Audio Processing** ([app.py](app.py:81))
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- `loudness_norm()` function for audio normalization
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- `process_audio()` matches reference implementation
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- Proper 16kHz resampling
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3. **✅ Audio Embedding Extraction** ([app.py](app.py:218))
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- Wav2Vec2 feature extraction
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- Hidden state stacking
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- Correct tensor reshaping with einops
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4. **✅ Video Generation** ([app.py](app.py:267))
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- Calls `generate_infinitetalk()` with proper parameters
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- Handles both image-to-video and video dubbing
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- Uses `save_video_ffmpeg()` for output
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5. **✅ Memory Management**
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- GPU cleanup after generation
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- ZeroGPU duration calculation
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- Memory monitoring
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### Reference Files to Study:
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