> > Hi, I use only 1 GPU(GXT 1080Ti 11GB) for training this model. Limited by memory of GPU, I set the batchsize=4 instead of 16 in your code. And I trained the model only on Market-1501 dataset instead of 10 datasets. The result is mAP = 0.385818, r1 precision = 0.627969 much lower than your paper said. So there are two problems.

[ajwl-pmli]

Hi, I use only 1 GPU(GXT 1080Ti 11GB) for training this model. Limited by memory of GPU, I set the batchsize=4 instead of 16 in your code. And I trained the model only on Market-1501 dataset instead of 10 datasets. The result is mAP = 0.385818, r1 precision = 0.627969 much lower than your paper said. So there are two problems.

1. How many GPUs you used in this experiment? I wonder whether the batchsize mostly influence the accuracy.
2. If I can't get the whole 10 datasets and only use 1 dataset for training and testing, how much will the result fall? Thank you for your wonderful work. Looking forward to your response.

Hi, the setting of mine is the same as yours, but the results are so bad--R1=0.355 ,mAP= 0.2111. I think your result is reasonable and could you tell me what evaluation code you use?

I use the matlab code offered by market-1501 dataset website. And finally the highest result I got was mAP=0.686, r1=85.6. I have no idea about how to get close to the authors' result.

Hello, I use the matlab code offered by market-1501 dataset website too, but it report error: Incorrect use of *, internal matrix dimensions must be consistent , Did you make any changes to the evaluation code? Thanks very much for reply!