#SANet_CROWD_COUNTINg
implement by using pytorch
And the result are virtually same with my tensorflow implementation BIGKnight/SANet_implementation.
However, this version are more close to the paper's net structure.(except I put the BN or IN behind the relu instead of before it. and it seemed in fact the BN layer did not ameliorate the net ability)
I still can not reach the result as the paper said(in fact, far worse than that). To be honest, I somewhat doubt the results showed in the paper.
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epoch frequency
Hello, bother you. Excuse me, how many epochs did you train during the experiment? I trained 300 times, but neither mae nor mse dropped，The last mae and mse are more than seventy. I also used shanghaipartB to train
请问请问下，你做这个实验时训练了多少个epoch ，为什么我训练个300个epoch，mse和mae还是很大，我用的上也shanghaipart
请问gt是什么格式处理的
代码中没有使用shanghaitechB的mat格式gt，请问是怎么保存的gt数据
Can you upload the checkpoint file
hi, Yezhen Wang. It's very very nice of you to release the SANet code, because I sent e-mails to the authors to ask if they can release the code, but they said for some reason they cannot.
Can you upload the checkpoint file or add a link to download, as I also want to do some study about this work. Just like what you write in predict.py
"/home/zzn/PycharmProjects/SANet_pytoch/checkpoints/model_mae_b.pkl"
Besides, the network of SANet is so much like the Inception network
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