Fingerprint FQA

A Python library for comprehensive Fingerprint Quality Assessment (FQA). This library consolidates logic for FDA, LCS, OCL, OFL, RVU, MU, MMB, ROI OMCS, DFIQI, and LFIQ features, providing a unified extract_all_metrics_single_image interface.

Installation

You can install this library in editable mode from the source code:

cd fingerprint_fqa
pip install -e .

Usage

from fingerprint_fqa import extract_all_metrics_single_image
from fingerprint_fqa import predict_quality_score_from_dict

img_path = "path/to/fingerprint.jpg"

# Extract all features
features = extract_all_metrics_single_image(img_path)
print("Extracted Features:", features)

# Predict score if you have models available
# Ensure that weights_dir is correctly set to your joblib models
# rf_score, xgb_score = predict_quality_score_from_dict(features, weights_dir="path/to/weights")