Sketch recognition, JPG to MAT file about teed HOT 9 CLOSED

Hi @sixgod696 thanks for using our proposal. Sorry, I may not be able to answer this question. Ww haven't come across this question before. We just replaced the edge map in the original paper with the edge map generated by TEED, and the code was not changed.
I understand, thanks for the reply.

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I used my edge diagram to carry out the sketch recognition project mentioned in the paper, and in order to convert the obtained edge diagram into a suitable MAT file, I wrote a jpg to MAT file script, but the prediction effect was very poor, how did you solve it in the first place?Looking forward to your reply！
I have solved this problem, I would like to ask what is the test data size of QMUL-shoe and QMUL-chair you use? Looking forward to your reply

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Excuse me, I have another additional question, that is, my score in top 1 is very low, but my score in top 10 is relatively good. What may be the reason for this? Looking forward to your reply!

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Hi @sixgod696 thanks for using our proposal.
Sorry, I may not be able to answer this question. Ww haven't come across this question before. We just replaced the edge map in the original paper with the edge map generated by TEED, and the code was not changed.

from teed.

Hi @sixgod696 ，I encountered some problems in the training process, can you tell me your training parameters ? Thanks very much ! Looking forward to your reply !

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Hi @sixgod696 ，I encountered some problems in the training process, can you tell me your training parameters ? Thanks very much ! Looking forward to your reply !
I've modified some parts of the network, and I'm not sure which part of your code have the problem.Maybe you can show your error log.

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Hi @sixgod696 ，I encountered some problems in the training process, can you tell me your training parameters ? Thanks very much ! Looking forward to your reply !
I've modified some parts of the network, and I'm not sure which part of you are having the problem.

Thank you for your reply！
The first image is the prediction result obtained by using the weight file obtained by my own training, and the second is the prediction result obtained by using the weight file in the source code.The difference is very big, but I don 't know where the problem is.

from teed.

Hi @sixgod696 ，I encountered some problems in the training process, can you tell me your training parameters ? Thanks very much ! Looking forward to your reply !
I've modified some parts of the network, and I'm not sure which part of you are having the problem.

Thank you for your reply！ The first image is the prediction result obtained by using the weight file obtained by my own training, and the second is the prediction result obtained by using the weight file in the source code.The difference is very big, but I don 't know where the problem is.
I have also encountered this problem. You may not have preprocessed the BIPED data set. There is preprocessing code in the BIPED project. After processing, the pictures will increase from hundreds to thousands, so the training time will be normal.

from teed.

Hi @sixgod696 ，I encountered some problems in the training process, can you tell me your training parameters ? Thanks very much ! Looking forward to your reply !
I've modified some parts of the network, and I'm not sure which part of you are having the problem.

Thank you for your reply！ The first image is the prediction result obtained by using the weight file obtained by my own training, and the second is the prediction result obtained by using the weight file in the source code.The difference is very big, but I don 't know where the problem is.
I have also encountered this problem. You may not have preprocessed the BIPED data set. There is preprocessing code in the BIPED project. After processing, the pictures will increase from hundreds to thousands, so the training time will be normal.

Because I did not expand the data set to lead to this problem. I did not pay attention to this problem. Thank you very much for taking your time to answer my question, thank you very much ! Wish you have a good day.

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