Check `conf_thres` and `iou_thres` prior to use (#10515)

utils/general.py

@@ -898,6 +898,9 @@ def non_max_suppression(
          list of detections, on (n,6) tensor per image [xyxy, conf, cls]
     """
 
+    # Checks
+    assert 0 <= conf_thres <= 1, f'Invalid Confidence threshold {conf_thres}, valid values are between 0.0 and 1.0'
+    assert 0 <= iou_thres <= 1, f'Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0'
     if isinstance(prediction, (list, tuple)):  # YOLOv5 model in validation model, output = (inference_out, loss_out)
         prediction = prediction[0]  # select only inference output
 
@@ -909,10 +912,6 @@ def non_max_suppression(
     nc = prediction.shape[2] - nm - 5  # number of classes
     xc = prediction[..., 4] > conf_thres  # candidates
 
-    # Checks
-    assert 0 <= conf_thres <= 1, f'Invalid Confidence threshold {conf_thres}, valid values are between 0.0 and 1.0'
-    assert 0 <= iou_thres <= 1, f'Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0'
-
     # Settings
     # min_wh = 2  # (pixels) minimum box width and height
     max_wh = 7680  # (pixels) maximum box width and height