Commit History

  1. feat: add Wav2Vec2Config and Wav2Vec2MusicClassifier imports for audio classification

    8a75b81
  2. feat: define families dictionary for candidate classifiers in _build_candidate_families function

    1d86705
  3. feat: enhance candidate selection with class ratio and calibrated SVC for improved model performance

    57f19bf
  4. feat: implement optimal threshold calculation for binary predictions in train function

    058eadc
  5. feat: add CalibratedClassifierCV and roc_curve imports for enhanced model evaluation

    27cd744
  6. feat: add temporary file patterns to .gitignore for dashboard images

    5c69e00
  7. feat: implement custom unpickler for TorchSklearnWrapper to support model deserialization

    ef35e36

  1. feat: add TorchSklearnWrapper import for model deserialization support

    026a187
  2. feat: enhance model compatibility and input handling for deep learning wrappers

    4324aed

  1. feat: add TorchSklearnWrapper for PyTorch model compatibility with sklearn and enhance final model training process

    bb33480

  1. feat: enhance Windows compatibility for asyncio with warning suppression

    c7e5d79
  2. feat: add Gradio import handling and Windows compatibility for asyncio

    306211a
  3. Add Gradio dependency to requirements.txt with version constraints

    20fe6c3
  4. feat: train all models on full data and save their paths

    94ed8e9
  5. Refactor code structure for improved readability and maintainability

    c0f3b71
  6. feat: update gauge and bars temperature images for improved visualization

    4c67eef
  7. feat: update local demo for AURIS AI music detection with enhanced dashboard and model comparison

    c4ee459
  8. Add gauge temperature image generated by Matplotlib⁠

    00d7f18
  9. feat: add local demo for AURIS AI music detection with Gradio interface

    4e0bd69
  10. feat: update duration limit for audio analysis to 1 minute for improved detection

    d20e581
  11. feat: implement mixed precision training and gradient accumulation in training loop

    076d979
  12. feat: adjust confidence range in analysis result and optimize parallel processing for feature extraction, vocal analysis, and CLAP detection

    8e5e154
  13. feat: enhance score fusion confidence range and adjust CLAP weight for improved accuracy

    e18d9f7
  14. feat: adjust confidence calculation in score fusion to improve agreement handling

    ba5cc97
  15. feat: update model parameters for Random Forest, Gradient Boosting, XGBoost, and LightGBM to enhance performance

    e68824c
  16. feat: adjust Random Forest parameters for improved model performance

    905436c
  17. feat: optimize Gradient Boosting and XGBoost parameters for improved model performance

    0d5b4e8
  18. feat: refactor training history figure generation to use GradientBoostingClassifier and improve metric tracking

    1c2de42
  19. feat: update model parameters and fix data leakage by removing duration_sec and sample_rate from features

    bb6655d
  20. feat: add deep learning classifier comparison script for AURIS with multiple architectures

    b8d143b
  21. feat: update excluded columns in feature statistics computation to prevent data leakage

    edc551d
  22. feat: exclude additional metadata columns from feature loading to prevent data leakage

    4b87da0

  1. feat: update output directory for generated figures to docs/academic/figures

    983f3ef
  2. feat: add deep-learning figure generation script for enhanced model evaluation

    917199d
  3. feat: enhance calibration figure with Brier score and update prediction functions

    255af12
  4. feat: update ROC and Precision-Recall curve functions to include best model visualization

    ca749ec
  5. feat: implement cross-validated predictions caching and update confusion matrix function

    0ea8f54
  6. feat: add additional imports for model evaluation and cross-validation

    853f480
  7. feat: add figure generation script for training results visualization

    94e94a1
  8. feat: enhance analysis result with estimated bitrate and XAI verdict integration

    9e93437
  9. feat: add XAI inference for explainable predictions in analysis results

    21d9516
  10. feat: add XAI explanation models for enhanced interpretability in analysis results

    45def97
  11. feat: integrate XAI service for enhanced explainability in analysis

    3f5c3a0
  12. fix: rename variable for clarity in compute_stats function

    7e3e9a6
  13. feat: add feature statistics computation from training CSV for enhanced analysis

    575dde4
  14. feat: add XAI inference service for explainable predictions with detailed feature contributions

    ac52af9
  15. feat: implement resume functionality in batch feature extraction to skip processed samples

    8f111ee

  1. feat: enhance visualization pipeline with additional figures and manifest support

    b06ac73
  2. feat: add dataset statistics and class balance visualizations to enhance analysis capabilities

    a04f1c8
  3. feat: refactor worker function for batch feature extraction to support multiprocessing

    2a59987