| IndexTTS-Rust/ (Complete Directory Structure) |
| │ |
| ├── indextts/ # Main Python package (194 files) |
| │ │ |
| │ ├── __init__.py # Package initialization |
| │ ├── cli.py # Command-line interface (64 lines) |
| │ ├── infer.py # Original inference (v1) - 690 lines |
| │ ├── infer_v2.py # Main inference v2 - 739 lines ⭐⭐⭐ |
| │ │ |
| │ ├── gpt/ # GPT-based TTS model (9 files, 16,953 lines) |
| │ │ ├── __init__.py |
| │ │ ├── model.py # Original UnifiedVoice (713L) |
| │ │ ├── model_v2.py # UnifiedVoice v2 ⭐⭐⭐ (747L) |
| │ │ ├── conformer_encoder.py # Conformer encoder ⭐⭐ (520L) |
| │ │ ├── perceiver.py # Perceiver resampler (317L) |
| │ │ ├── conformer_encoder.py # Conformer components |
| │ │ ├── transformers_gpt2.py # GPT2 implementation (1,878L) |
| │ │ ├── transformers_generation_utils.py # Generation utilities (4,747L) |
| │ │ ├── transformers_beam_search.py # Beam search (1,013L) |
| │ │ └── transformers_modeling_utils.py # Model utilities (5,525L) |
| │ │ |
| │ ├── BigVGAN/ # Neural Vocoder (6+ files, ~1000+ lines) |
| │ │ ├── __init__.py |
| │ │ ├── models.py # BigVGAN architecture ⭐⭐⭐ |
| │ │ ├── ECAPA_TDNN.py # Speaker encoder |
| │ │ ├── activations.py # Snake, SnakeBeta activations |
| │ │ ├── utils.py # Helper functions |
| │ │ │ |
| │ │ ├── alias_free_activation/ # CUDA kernel variants |
| │ │ │ ├── cuda/ |
| │ │ │ │ ├── activation1d.py # CUDA kernel loader |
| │ │ │ │ └── load.py |
| │ │ │ └── torch/ |
| │ │ │ ├── act.py # PyTorch activation |
| │ │ │ ├── filter.py # Anti-aliasing filter |
| │ │ │ └── resample.py # Resampling |
| │ │ │ |
| │ │ ├── alias_free_torch/ # PyTorch-only fallback |
| │ │ │ ├── act.py |
| │ │ │ ├── filter.py |
| │ │ │ └── resample.py |
| │ │ │ |
| │ │ └── nnet/ # Network modules |
| │ │ ├── linear.py |
| │ │ ├── normalization.py |
| │ │ └── CNN.py |
| │ │ |
| │ ├── s2mel/ # Semantic-to-Mel Models (~500+ lines) |
| │ │ ├── modules/ # Core modules (10+ files) |
| │ │ │ ├── audio.py # Mel-spectrogram computation ⭐ |
| │ │ │ ├── commons.py # Common utilities (21KB) |
| │ │ │ ├── layers.py # NN layers (13KB) |
| │ │ │ ├── length_regulator.py # Duration modeling |
| │ │ │ ├── flow_matching.py # Continuous flow matching |
| │ │ │ ├── diffusion_transformer.py # Diffusion model |
| │ │ │ ├── rmvpe.py # Pitch extraction (22KB) |
| │ │ │ ├── quantize.py # Quantization |
| │ │ │ ├── encodec.py # EnCodec codec |
| │ │ │ ├── wavenet.py # WaveNet implementation |
| │ │ │ │ |
| │ │ │ ├── bigvgan/ # BigVGAN vocoder |
| │ │ │ │ ├── modules.py |
| │ │ │ │ ├── config.json |
| │ │ │ │ ├── bigvgan.py |
| │ │ │ │ ├── alias_free_activation/ # Variants |
| │ │ │ │ └── models.py |
| │ │ │ │ |
| │ │ │ ├── vocos/ # Vocos codec |
| │ │ │ ├── hifigan/ # HiFiGAN vocoder |
| │ │ │ ├── openvoice/ # OpenVoice components (11 files) |
| │ │ │ ├── campplus/ # CAMPPlus speaker encoder |
| │ │ │ │ └── DTDNN.py # DTDNN architecture |
| │ │ │ └── gpt_fast/ # Fast GPT inference |
| │ │ │ |
| │ │ ├── dac/ # DAC codec |
| │ │ │ ├── model/ |
| │ │ │ ├── nn/ |
| │ │ │ └── utils/ |
| │ │ │ |
| │ │ └── (other s2mel implementations) |
| │ │ |
| │ ├── utils/ # Text & Feature Utils (12+ files, ~500L) |
| │ │ ├── __init__.py |
| │ │ ├── front.py # TextNormalizer, TextTokenizer ⭐⭐⭐ (700L) |
| │ │ ├── maskgct_utils.py # Semantic codec builders (250L) |
| │ │ ├── arch_util.py # AttentionBlock, utilities |
| │ │ ├── checkpoint.py # Model loading |
| │ │ ├── xtransformers.py # Transformer utils (1,600L) |
| │ │ ├── feature_extractors.py # MelSpectrogramFeatures |
| │ │ ├── common.py # Common functions |
| │ │ ├── text_utils.py # Text utilities |
| │ │ ├── typical_sampling.py # TypicalLogitsWarper sampling |
| │ │ ├── utils.py # General utils |
| │ │ ├── webui_utils.py # Web UI helpers |
| │ │ ├── tagger_cache/ # Text normalization cache |
| │ │ │ |
| │ │ └── maskgct/ # MaskGCT codec (100+ files, 10KB+) |
| │ │ └── models/ |
| │ │ ├── codec/ # Multiple codec implementations |
| │ │ │ ├── amphion_codec/ # Amphion codec |
| │ │ │ │ ├── codec.py |
| │ │ │ │ ├── vocos.py |
| │ │ │ │ └── quantize/ # Quantization |
| │ │ │ │ ├── vector_quantize.py |
| │ │ │ │ ├── residual_vq.py |
| │ │ │ │ ├── factorized_vector_quantize.py |
| │ │ │ │ └── lookup_free_quantize.py |
| │ │ │ │ |
| │ │ │ ├── facodec/ # FACodec variant |
| │ │ │ │ ├── facodec_inference.py |
| │ │ │ │ ├── modules/ |
| │ │ │ │ │ ├── commons.py |
| │ │ │ │ │ ├── attentions.py |
| │ │ │ │ │ ├── layers.py |
| │ │ │ │ │ ├── quantize.py |
| │ │ │ │ │ ├── wavenet.py |
| │ │ │ │ │ ├── style_encoder.py |
| │ │ │ │ │ ├── gradient_reversal.py |
| │ │ │ │ │ └── JDC/ (pitch detection) |
| │ │ │ │ └── alias_free_torch/ # Anti-aliasing |
| │ │ │ │ |
| │ │ │ ├── speechtokenizer/ # Speech Tokenizer codec |
| │ │ │ │ ├── model.py |
| │ │ │ │ └── modules/ |
| │ │ │ │ ├── seanet.py |
| │ │ │ │ ├── lstm.py |
| │ │ │ │ ├── norm.py |
| │ │ │ │ ├── conv.py |
| │ │ │ │ └── quantization/ |
| │ │ │ │ |
| │ │ │ ├── ns3_codec/ # NS3 codec variant |
| │ │ │ ├── vevo/ # VEVo codec |
| │ │ │ ├── kmeans/ # KMeans codec |
| │ │ │ ├── melvqgan/ # MelVQ-GAN codec |
| │ │ │ │ |
| │ │ │ ├── codec_inference.py |
| │ │ │ ├── codec_sampler.py |
| │ │ │ ├── codec_trainer.py |
| │ │ │ └── codec_dataset.py |
| │ │ │ |
| │ │ └── tts/ |
| │ │ └── maskgct/ |
| │ │ ├── maskgct_s2a.py # Semantic-to-acoustic |
| │ │ └── ckpt/ |
| │ │ |
| │ └── vqvae/ # Vector Quantized VAE |
| │ ├── xtts_dvae.py # Discrete VAE (currently disabled) |
| │ └── (other VAE components) |
| │ |
| ├── examples/ # Sample Data & Test Cases |
| │ ├── cases.jsonl # Example test cases |
| │ ├── voice_*.wav # Sample voice prompts (12 files) |
| │ ├── emo_*.wav # Emotion reference samples (2 files) |
| │ └── sample_prompt.wav # Default prompt (implied) |
| │ |
| ├── tests/ # Test Suite |
| │ ├── regression_test.py # Main regression tests ⭐ |
| │ └── padding_test.py # Padding/batch tests |
| │ |
| ├── tools/ # Utility Scripts & i18n |
| │ ├── download_files.py # Model downloading from HF |
| │ └── i18n/ # Internationalization |
| │ ├── i18n.py # Translation system |
| │ ├── scan_i18n.py # i18n scanner |
| │ └── locale/ |
| │ ├── en_US.json # English translations |
| │ └── zh_CN.json # Chinese translations |
| │ |
| ├── archive/ # Historical Docs |
| │ └── README_INDEXTTS_1_5.md # IndexTTS 1.5 documentation |
| │ |
| ├── webui.py # Gradio Web UI ⭐⭐⭐ (18KB) |
| ├── cli.py # Command-line interface |
| ├── requirements.txt # Python dependencies |
| ├── MANIFEST.in # Package manifest |
| ├── .gitignore # Git ignore rules |
| ├── .gitattributes # Git attributes |
| └── LICENSE # Apache 2.0 License |
|
|
| ═══════════════════════════════════════════════════════════════════════════════ |
| KEY FILES BY IMPORTANCE: |
| ═══════════════════════════════════════════════════════════════════════════════ |
|
|
| ⭐⭐⭐ CRITICAL (Core Logic - MUST Convert First) |
| 1. indextts/infer_v2.py - Main inference pipeline (739L) |
| 2. indextts/gpt/model_v2.py - UnifiedVoice GPT model (747L) |
| 3. indextts/utils/front.py - Text processing (700L) |
| 4. indextts/BigVGAN/models.py - Vocoder (1000+L) |
| 5. indextts/s2mel/modules/audio.py - Mel-spectrogram (83L, critical DSP) |
|
|
| ⭐⭐ HIGH PRIORITY (Major Components) |
| 1. indextts/gpt/conformer_encoder.py - Conformer blocks (520L) |
| 2. indextts/gpt/perceiver.py - Perceiver attention (317L) |
| 3. indextts/utils/maskgct_utils.py - Codec builders (250L) |
| 4. indextts/s2mel/modules/commons.py - Common utilities (21KB) |
|
|
| ⭐ MEDIUM PRIORITY (Utilities & Optimization) |
| 1. indextts/utils/xtransformers.py - Transformer utils (1,600L) |
| 2. indextts/BigVGAN/activations.py - Activation functions |
| 3. indextts/s2mel/modules/rmvpe.py - Pitch extraction (22KB) |
|
|
| OPTIONAL (Web UI, Tools) |
| 1. webui.py - Gradio interface |
| 2. tools/download_files.py - Model downloading |
|
|
| ═══════════════════════════════════════════════════════════════════════════════ |
| TOTAL STATISTICS: |
| ═══════════════════════════════════════════════════════════════════════════════ |
| Total Python Files: 194 |
| Total Lines of Code: ~25,000+ |
| GPT Module: 16,953 lines |
| MaskGCT Codecs: ~10,000+ lines |
| S2Mel Models: ~2,000+ lines |
| BigVGAN: ~1,000+ lines |
| Utils: ~500 lines |
| Tests: ~100 lines |
|
|
| Models Supported: 6 major HuggingFace models |
| Languages: Chinese (full), English (full), Mixed |
| Emotion Dimensions: 8-dimensional emotion control |
| Audio Sample Rate: 22,050 Hz (primary) |
| Max Text Tokens: 120 |
| Max Mel Tokens: 250 |
| Mel Spectrogram Bins: 80 |
|
|
