code/eval_model.py

#!/usr/bin/env python3
"""Evaluate one or more face-detector weights (.pt / .onnx) on the converted WIDER FACE val split.

Usage: python eval_model.py export/face_yolo11n.pt export/face_yolo11n_fp32.onnx export/face_yolo11n_fp16.onnx
"""
import argparse

from ultralytics import YOLO


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("models", nargs="+")
    ap.add_argument("--data", default="dataset/data.yaml")
    ap.add_argument("--imgsz", type=int, default=640)
    ap.add_argument("--workers", type=int, default=4)
    a = ap.parse_args()
    for path in a.models:
        r = YOLO(path, task="detect").val(data=a.data, imgsz=a.imgsz, batch=1, device=0,
                                          workers=a.workers, plots=False, verbose=False)
        print(f"RES {path}: mAP50={r.box.map50:.4f} mAP50-95={r.box.map:.4f} P={r.box.mp:.3f} R={r.box.mr:.3f} "
              f"| {r.speed['preprocess']:.2f}+{r.speed['inference']:.2f}+{r.speed['postprocess']:.2f} ms/img",
              flush=True)


if __name__ == "__main__":
    main()