corrected calculation of xc parameter

nms.py

@@ -101,14 +101,14 @@ def non_max_suppresion_v8(prediction, conf_thres=0.25, iou_thres=0.45, classes=N
 
     nc = prediction.shape[2] - 4  # number of classes
     # xc = prediction[..., 4] > conf_thres  # candidates
-    xc = []
-    for xi, x in enumerate(prediction):  # image index, image inference
-        conf = np.amax(x[:, 4:], axis=1, keepdims=True)
-        if np.any(conf > conf_thres):
-            xc.append(True)
-        else:
-            xc.append(False)
-    # xc = np.amax(prediction[..., 4:], axis=2, keepdims=True) > conf_thres
+    # xc = []
+    # for xi, x in enumerate(prediction):  # image index, image inference
+    #     conf = np.amax(x[:, 4:], axis=1, keepdims=True)
+    #     if np.any(conf > conf_thres):
+    #         xc.append(True)
+    #     else:
+    #         xc.append(False)
+    xc = np.amax(prediction[..., 4:], axis=2) > conf_thres
 
     # Checks
     assert 0 <= conf_thres <= 1, f'Invalid Confidence threshold {conf_thres}, valid values are between 0.0 and 1.0'