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You can increase the conf_thres to a higher value (like 0.01) to work without warning. But modify the conf_thres from 0.001 to above may affect the "actual" evaluation of the final performance.
By the way, it is quite normal for the warning in the early stages of the training, since the network is still learning the characteristics of the classes. As a result, in early-stage, the network "almost-randomly" gives a lot of guesses, since it is not sure about the correct characteristics! After some training epochs (maybe several tens or hundreds, depending on dataset), the network will be more certain about its predictions, and the warning will disappear naturally.
What is "time limit exceeded" in nms? Does it matter if I get this exception ?
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