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Model and Parameters For LSP Dataset #23
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Hi @ktak199 I just did the same thing today and I also saw that the error was much higher than in the case of FLIC. I guess we should check more in detail what parameters are used in the original paper (https://arxiv.org/pdf/1312.4659v3.pdf). I'm now training with MPII using the same default parameters as with FLIC, to see what happens, but I'll retake the training/testing with LSP afterwards. I'll tell you if I get better results after tuning the parameters. Please, let me know too if you are luckier after tuning the parameters too. |
Hi @lunzueta Thank you! Ok, I'll also try and tell you! |
Hi @ktak199. I've tested this time with MPII and the default parameters. The tests have less error in general than in the case of LSP, but they still are quite bad compared to FLIC. So, I guess that in both cases specific parameters should be used. During the training I observed that in both cases it tended to overfitting quite quickly. |
Hi @lunzueta. One way against overfittin may be tuning dropout parameters. http://stats.stackexchange.com/questions/109976/in-convolutional-neural-networks-how-to-prevent-the-overfitting |
@lunzueta I'm testing with the following parameter. |
Hi @ktak199. Yes, you are right about σ, I said it wrong. I've continued doing some more tests changing the parameters (crop vs no-crop, local contrast vs no-local-contrast, etc), but I'm not getting... let's say... "normal" results with LSP. The result I normally get in the tests is a very small avatar (compared to the actual body size) in the middle of the image. I'm a bit stuck with this too. Now, I was just trying to do this same training using the caffe branch instead the master branch, to see if this could be something related to the deep learning framework. I'll let you know. Good luck with your tests too, I hope we can get something closer to the expected results. |
Hi @lunzueta |
@lunzueta |
Thanks for sharing this @yutuofish2. I see you are training for more than 600 epochs. I wonder how many should be a good number, but I see that your training looks much better than what I was getting. |
@ktak199 |
This time I trained a model with LSP, just changing the optimizer to 'MomentumSGD', and maintaining the rest of parameters the same way. I got the following results, which still aren't good enough: |
Sorry for inconvenience, there are some fatal bugs maybe in data processing part. I'm trying to find them now and will update if I could fix them and confirm the training can be done correctly. So please wait or try to find bugs and send PRs. Thanks. |
Thank you very much for taking care of this issue @mitmul. I'm learning a lot from all this :-) |
Thank you so much @mitmul ! |
Could the problem be, in the case of LSP, that there are some joint positions with negative values (expressing that they are occluded) and these make the training get crazy? I say this because I've retrained with FLIC for a few epochs and it looked to be converging normally. The only difference I see are those negative values. |
I tried with FLIC dataset. |
Hi guys. Based on the code provided in the caffe branch, I've done some tests with MPII (I attach the caffe net and solver files I've used for that), and after training for some hundred of epochs it seems to give some responses that make more sense (not always the same mean pose as shown above). In order to generate the LMDB format data, I used the same functions provided in this code (cropping, etc), but without applying the local contrast (because this wasn't possible to reproduce in Caffe), so I don't think that the failure is there. The AlexNet architecture defined in Chainer format also seems to be correct. So, taking this into account, where could the failure be? (I still couldn't find it) |
Hi @lunzueta @yutuofish2 may I ask which python program you use to plot the images with joints positions on them? The only one I can find is evaluate_flic.py but it still doesn't seem right. |
I trained lsp dataset with default parameters.
The test error is large.
Do you have appropriate model or parameters for lsp dataset ?
Thanks!
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