yscv-eval 0.1.7

Evaluation metrics (mAP, MOTA, HOTA) and dataset adapters
Documentation

yscv-eval

Evaluation metrics for classification, detection, and tracking. Dataset adapters for COCO, Pascal VOC, and CSV.

use yscv_eval::*;

let ap = average_precision(&predictions, &ground_truths, 0.5);
let report = classification_report(&predicted_labels, &true_labels);
println!("{}", report);

Metrics

Task Metrics
Classification accuracy, precision, recall, F1, confusion matrix, Cohen's kappa, ROC AUC
Detection mAP, AP@IoU, precision-recall curve
Tracking MOTA, MOTP, HOTA, IDF1, ID switches
Image quality PSNR, SSIM, MSE

Dataset Adapters

  • COCO: JSON annotation loading
  • Pascal VOC: XML annotation parsing
  • CSV: generic label file reader
  • Camera diagnostics: capture quality reports

Tests

95 tests covering metric correctness, edge cases, dataset parsing.