Comments (2)
@deepukr007 hello,
Great question! By default, Non-Maximum Suppression (NMS) is not applied during the training phase (nms=False
). NMS is typically used during the prediction or inference stage to refine the detection bounding boxes by removing overlaps and retaining only the most probable boxes.
When nms=False
in the configuration, it doesn't impact the model training but affects how detections are handled during prediction. If you need NMS during inference, you'd set nms=True
in your configuration or explicitly enable it when you run predictions.
Hope that clears things up! 😊 If you have any more questions, feel free to ask.
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