Show HN: BNNR – a closed-loop pipeline for improving vision models
Category: ai-ml
Tags: computer-vision, model-improvement, explainable-ai, pytorch, training-pipeline
Score: 7.0/10 (Innovation: 7, Technical: 7, Documentation: 8, Utility: 6)
BNNR is a PyTorch toolkit that creates a closed-loop pipeline for improving vision models by integrating training, XAI-based explanation, intelligent augmentation testing, and structured reporting. It's interesting because it uses explainability (like GradCAM) not just for visualization but to drive targeted augmentations (ICD/AICD) that test hypotheses about model behavior, moving beyond manual trial-and-error.
Target audience: data engineers, ml engineers, researchers
Repository: https://github.com/bnnr-team/bnnr · Python · MIT · 5 stars
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