{"repo":"AndyLone22/MirrorMetrics","free":true,"listed":false,"github":"https://github.com/AndyLone22/MirrorMetrics","clone":"git clone https://github.com/AndyLone22/MirrorMetrics.git","description":"MirrorMetrics: How to evaluate Stable Diffusion LoRAs. A visual diagnostic tool to detect overfitting, check dataset quality, and fix training settings using InsightFace biometrics.","language":"Python","stars":62,"topics":["ai-art","computer-vision","data-visualization","dataset-analysis","insightface","insightface-pytorch","lora-training","metrics","overfitting","python-script"],"license":"MIT","category":"machine-learning","readme_excerpt":"🔬 MirrorMetrics: AI Identity Consistency Analyzer MirrorMetrics is a scientific benchmarking tool for evaluating Face LoRAs (Stable Diffusion fine-tuned models). It uses InsightFace (ArcFace) to perform local biometric analysis and generates a rich, interactive Plotly dashboard — all running entirely on your machine. Why use this tool? (The Problem) Training a LoRA often feels like guessing. You might ask: How do I know if my LoRA is overtrained? Why does my character look rigid? Is my dataset consistent? MirrorMetrics solves this by measuring Identity Consistency , Face Geometry , and Flexibility mathematically. In two quick and easy words You put the dataset you used to train your LoRA in the Reference Images folder and the generated images in the Lora Candidates folder (Create one folder for each LoRA you want to compare. The name of the folder will be used as the name of the LoRA in the dashboard.). You can have more LoRAs from the same training, maybe with different settings, or different steps, for example. Or you could have LoRA trained for entirely different models, that's fine too. Then you run the script and it will generate a dashboard with all the metrics. The way I use it the most at the moment is: - Compare the plots for the dataset, to see if I have some outliers that can skew the results. - Compare the plots for the LoRAs, to see which one is the most consistent with the dataset, especially graph one which shows the general similarity score of the various ima","default_branch":null,"files":null,"tree":[],"storefront":"/r/AndyLone22","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AndyLone22/MirrorMetrics/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}