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How about peleeNet training from scratch? #30
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@MrWhiteHomeman I am trying to do it, response to you later |
Here is a link 链接: https://pan.baidu.com/s/1vZONIe2pBkxjo-s5wP3zAg 密码: 3ip6.
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@ujsyehao It is so nice of you for your reply !!! I have another question about the code, in the feature_extractor.py ,the 30th line, why are there two 'stage4_tb/ext/pm2/res/relu' in the Pelee.mbox_source_layers? Can you give me some advices? Thank you!!! |
You can use (http://ethereon.github.io/netscope/#/editor) to view peleenet-ssd network structure, you will find stage4_tb/ext/pm2/res layer is used twice to generate ext/pm1_mbox_loc layer and ext/pm2_mbox_loc layer(conf layer/priorbox layer is also the case). |
mobile-net ssd also follows this design pattern, I will update later. |
@ujsyehao Hello,I have a question about the batchsize, in this paper , the batch-size is 32, if I change the batch-size to 64, will I get a better result about testing ? I would appreciate it if you could give me some advices. |
No, batch size can affect training time and has no direct relation with model performance. |
@ujsyehao So,I always have a question about batchsize, if the batch size is too big, will it have a bad result? And I know the DetNet(旷世科技) , it set the batch size to 256, and get a greatest result... |
You can look it |
Could you please share the prototxt again? The link [链接: https://pan.baidu.com/s/1vZONIe2pBkxjo-s5wP3zAg 密码: 3ip6.] failed now. |
@ujsyehao |
@foralliance model performance 依赖于模型本身,batch size只是一个超参而已,如果你修改了batch size,再选定其它合适的超参比如base_lr,它最终的效果是一样的,一般而言,使用一个大batch只是训练的更快,更容易出结果,并不会从根本上决定模型的性能 |
@foralliance 我看了这个回答,默认accum_batch_size固定,对于无BN层/BN层参数固定情况下,batch size不影响模型性能这个观点我是认同的 |
各位大佬好,你们谁晓得Pelee训练目标检测 + 车道线,谢谢各位 |
I think peleenet is similar to DSOD, how about peleeNet training from scratch, does it work???
I appreciate it if you can give me some advices!!!
Thank u!!!
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