@@ -84,13 +84,12 @@ class DetectionMetrics(Metric):
         Apply NMS and match all the predictions and targets of a given batch, and update the metric state accordingly.
 
         :param preds :        Raw output of the model, the format might change from one model to another, but has to fit
-                                the input format of the post_prediction_callback
-        :param target:        Targets for all images of shape (total_num_targets, 6)
-                                format:  (index, x, y, w, h, label) where x,y,w,h are in range [0,1]
+                                the input format of the post_prediction_callback (cx,cy,wh)
+        :param target:        Targets for all images of shape (total_num_targets, 6) LABEL_CXCYWH
+                                format:  (index, label, cx, cy, w, h)
         :param device:        Device to run on
         :param inputs:        Input image tensor of shape (batch_size, n_img, height, width)
-        :param crowd_targets: Crowd targets for all images of shape (total_num_targets, 6)
-                                 format:  (index, x, y, w, h, label) where x,y,w,h are in range [0,1]
+        :param crowd_targets: Crowd targets for all images of shape (total_num_targets, 6), LABEL_CXCYWH
         """
         self.iou_thresholds = self.iou_thresholds.to(device)
         _, _, height, width = inputs.shape