Closed PlumedSerpent closed 5 years ago
The euler angles can be calculated in the preprocess procedure ,but w_n is not suitable ,it is different in each batch,it should be kepping updating during trianing.
The euler angles can be calculated in the preprocess procedure ,but w_n is not suitable ,it is different in each batch,it should be kepping updating during trianing.
I re-implement PFLD in pytorch, and I do the pre-processing procedure just as you said. But I found a confusing result, it seems the Euler predict branch doesn't contribute to the accuracy. In detail, I got 5.7% NME w/o the Euler prediction and weight_attributes loss in WFLW dataset. (btw, I trained 2k epochs, which may be too much in my thought.) In your experiments, did you observe the improvement brought by the weight term in loss function?
The euler angles can be calculated in the preprocess procedure ,but w_n is not suitable ,it is different in each batch,it should be kepping updating during trianing.
I re-implement PFLD in pytorch, and I do the pre-processing procedure just as you said. But I found a confusing result, it seems the Euler predict branch doesn't contribute to the accuracy. In detail, I got 5.7% NME w/o the Euler prediction and weight_attributes loss in WFLW dataset. (btw, I trained 2k epochs, which may be too much in my thought.) In your experiments, did you observe the improvement brought by the weight term in loss function?
I did not compare the results with ones without euler angles prediction , but if you have taken the euler angles prediction loss as a part of total losses,it should have influence on the common part of whole model .It is clean that multi-loss is also efficient to improve the model performence.
The euler angles can be calculated in the preprocess procedure ,but w_n is not suitable ,it is different in each batch,it should be kepping updating during trianing. I re-implement PFLD in pytorch, and I do the pre-processing procedure just as you said. But I found a confusing result, it seems the Euler predict branch doesn't contribute to the accuracy. In detail, I got 5.7% NME w/o the Euler prediction and weight_attributes loss in WFLW dataset. (btw, I trained 2k epochs, which may be too much in my thought.) In your experiments, did you observe the improvement brought by the weight term in loss function?
I did not compare the results with ones without euler angles prediction , but if you have taken the euler angles prediction loss as a part of total losses,it should have influence on the common part of whole model .It is clean that multi-loss is also efficient to improve the model performence.
OK, thanks for your reply, I'll try more experiments. Because I have been clear about the data pre-processing problem, I just close this issue.
The euler angles can be calculated in the preprocess procedure ,but w_n is not suitable ,it is different in each batch,it should be kepping updating during trianing.
I re-implement PFLD in pytorch, and I do the pre-processing procedure just as you said. But I found a confusing result, it seems the Euler predict branch doesn't contribute to the accuracy. In detail, I got 5.7% NME w/o the Euler prediction and weight_attributes loss in WFLW dataset. (btw, I trained 2k epochs, which may be too much in my thought.) In your experiments, did you observe the improvement brought by the weight term in loss function?
I try to re-implement PFLD in pytorch but the accuracy is worse than this tf-version. What about your model? Sorry to bother you but may I share your pytorch code?
@guoqiangqi 看您的代码里eular angle 不会直接读出的gd的[203:206]三位吗,这三个值不就是eular 角度?为什么上面还提到了额外的计算?
这是更新后的代码,在图像读入时计算的euler angles。
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From: xubin19939 Date: 2019-08-15 11:06 To: guoqiangqi/PFLD CC: Guoqiang QI; Mention Subject: Re: [guoqiangqi/PFLD] Are Euler Angle GT and W_n pre-defined? (#12) @guoqiangqi 看您的代码里eular angle 不会直接读出的gd的[203:206]三位吗,这三个值不就是eular 角度?为什么上面还提到了额外的计算? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or mute the thread.
According to my understanding, it seems we can calculate the Euler Angle GT and w_n of all samples, and return them in dataset iterators. Right?