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Hello, I'm wandering that the optimizaiton process between the experiment with and without the auxiliary loss. In step 1, Is there a big or small gap during optimazing the model.

Traceback (most recent call last): File "setup.py", line 66, in setup( File "/home/qian/anaconda3/envs/LabelEnc/lib/python3.8/site-packages/setuptools/__init__.py", line 153, in setup return distutils.core.setup(**attrs) File "/home/qian/anaconda3/envs/LabelEnc/lib/python3.8/distutils/core.py", line 148, in setup dist.run_commands() File "/home/qian/anaconda3/envs/LabelEnc/lib/python3.8/distutils/dist.py", line 966,...

Is it necessary to set 5 stages in this function? I mean if 3, 4, 6 stages can work ================================================================= class LabelEncodingFunction(nn.Module): def __init__(self, in_channels): super(LabelEncodingFunction, self).__init__() self.stage1 = nn.Conv2d(in_channels,...

Hi authors, love your work. can you please share some hints on how to implement the loss to yolov5 backbone ?

I use the labelenc in a custom model. In training step1 the autoencoder loss are not going down。in my opinion,the autoencoder loss should be in sync with detection loss since...