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AUGLY
Multimodal data augmentation library for audio, image, text, and video
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ABOUT
AI models trained on clean, curated datasets often fail in production when faced with noisy, distorted, or modified inputs across different modalities. Building separate augmentation pipelines for each data type requires significant engineering effort and domain expertise. AugLy provides a unified library with over 100 augmentations spanning audio, image, text, and video, enabling teams to stress-test and improve model robustness with realistic data variations from a single toolkit.
INSTALL
pip install auglyINTEGRATION GUIDE
1. Apply text paraphrasing, spelling errors, and insertions to stress-test NLP models
2. Augment image datasets with overlays, blur, and color transforms for vision model training
3. Simulate audio noise, pitch shifts, and speed changes for speech recognition robustness
4. Create video training variations with frame drops, resolution changes, and time stretches
5. Benchmark model robustness by measuring accuracy degradation across augmented test sets
TAGS
data-augmentationmultimodalaudioimagetextvideoopen-source