AndyLone22/MirrorMetrics

MirrorMetrics: How to evaluate Stable Diffusion LoRAs. A visual diagnostic tool to detect overfitting, check dataset quality, and fix training settings using InsightFace biometrics.

39
/ 100
Emerging

This tool helps AI artists and researchers evaluate how well their Stable Diffusion Face LoRAs maintain a consistent character identity. You input the reference images used for training and the images generated by your LoRA, and it outputs an interactive dashboard and detailed reports. This allows you to visually and numerically understand if your LoRA is overtrained, if your dataset has inconsistencies, or why generated faces might look rigid or off-model.

Use this if you train Stable Diffusion models (LoRAs) specifically for generating consistent character faces and need a scientific way to benchmark their performance, identify overfitting, or check the quality of your training data.

Not ideal if you are working with non-face image generation, general style transfer, or if you only need a quick qualitative assessment without deep biometric analysis.

AI Art Character Generation Generative AI Model Evaluation Image Synthesis
No Package No Dependents
Maintenance 10 / 25
Adoption 8 / 25
Maturity 11 / 25
Community 10 / 25

How are scores calculated?

Stars

48

Forks

5

Language

Python

License

MIT

Last pushed

Feb 21, 2026

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/AndyLone22/MirrorMetrics"

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