The results were too different

[xiaoweihappy123]

Hello, could you please provide a detailed command line? The result of my running on two partial datasets is only over 50, which is far different from the result on GitHub.

[xjhjinhui]

@xiaoweihappy123 Me too.My result is
Single Query: [cmc1: 45.07%], [cmc5: 66.80%], [cmc10: 76.07%] mAP = 0.50221015378 Done, 3.83s
I guess if my mAP calculation method is wrong.I wonder what is the latest result of your code and how is it solved?Looking forward to your reply!Thanks!

[xiaoweihappy123]

Search the author's latest paper for things that need to change.

[xjhjinhui]

@xiaoweihappy123 Could you please tell me the paper's title?Thanks a lot!

[xiaoweihappy123]

recognizing partial biometric patterns

[hh23333]

@xjhjinhui @xiaoweihappy123 I also only got 49.73 rank1 accuracy on Parital-reID dataset and 57.14 rank1 on Partial-iLIDS. Have you ever explored any setting or solution to get the performance that the author reported in paper and readme file. looking forward to your reply! Thanks!

[CodeToPoem]

Did you ever try to set spatial_train True in command line for improving perfromance?

command line is just like this:
python script/experiment/train.py --dataset market1501 --partial_dataset Partial_REID --spatial_train True --total_epochs 400
@hh23333 @xiaoweihappy123 @xjhjinhui