Fix incorrect metrics when nothing is detected (#19362)

Signed-off-by: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/models/yolo/detect/val.py

@@ -186,7 +186,7 @@ class DetectionValidator(BaseValidator):
         self.nt_per_class = np.bincount(stats["target_cls"].astype(int), minlength=self.nc)
         self.nt_per_image = np.bincount(stats["target_img"].astype(int), minlength=self.nc)
         stats.pop("target_img", None)
-        if len(stats) and stats["tp"].any():
+        if len(stats):
             self.metrics.process(**stats)
         return self.metrics.results_dict
 

ultralytics/utils/metrics.py

@@ -604,7 +604,7 @@ def ap_per_class(
             if j == 0:
                 prec_values.append(np.interp(x, mrec, mpre))  # precision at mAP@0.5
 
-    prec_values = np.array(prec_values)  # (nc, 1000)
+    prec_values = np.array(prec_values) if prec_values else np.zeros((1, 1000))  # (nc, 1000)
 
     # Compute F1 (harmonic mean of precision and recall)
     f1_curve = 2 * p_curve * r_curve / (p_curve + r_curve + eps)