Comments (10)
@ruinmessi 1 more thing weird is that when I used the weights that I had trained, if I set the threshold score in range (0, 1) as usual, no predictions were shown. But when I set it 10000 smaller, the results appeared.
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Sorry, I have no idea about your dataset and training setting. As the img you showed is quite simple, I suggest you use a ''shallow'' model, like SSD, RFBNet for this task. They are more friendly for single gpu training, and the performance may be not too bad.
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@ruinmessi I know that my dataset is quite simple but the results I got from your model are not good. I had used Centernet before and I want to have a comparison between 2 models in some simple dataset first.
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@ruinmessi And tried to train the network again with coco 2014 valid, and it still detects very well. So I think this network is not good at detecting small objects as the fact that yolo itself is not good at handling that problem.
I also saw that in yolo_head you defined 9 anchors.
Do those anchors size effect the network when is trained for detecting small objects ?
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@trungpham2606 I need your test.py code for detecting the single picture,can you send it to me at my email [email protected] ,thank you
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@wyj18502986957 yeah, sure bro.
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@trungpham2606 I also need that test.py code, can you send it to me at my email [email protected]
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@trungpham2606 , @wyj18502986957 I want detecting my dataset,can you send the test.py code to me .my email is [email protected]. thanks
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@trungpham2606 What's the effect of centernet?
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@wushilian what do you mean "effect" ?
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Related Issues (20)
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