CCS/TDA2: Adaboost train

Thanks for you reply. Add the opts.nPos can't solve the problem.

I use opts.pPyramid.pChns.pFastMode.enabled=1; %default: 0

Adaboost early stopping,train log as follows

Sampling windows completed=100.0% [elapsed=35.4s / remaining~=0.0s]
Sampled 30000 windows from 2048 images.
Done sampling windows (time=37s).
Extracting features... done (time=14s).
Training AdaBoost: nWeak= 32 nFtrs=2560 pos=10150 neg=30000
i= 16 alpha=5.000 err=0.000 loss=9.03e-34
stopping early
Done training err=0.0000 fp=0.0000 fn=0.0000 (t=0.3s).
Done training stage 0 (time=119s).
---------------------------------------------------------------------------
Training stage 1

Sampling windows completed=100.0% [elapsed=123.8s / remaining~=0.0s]
Sampled 10000 windows from 10176 images.
Done sampling windows (time=126s).
Extracting features... done (time=13s).
Training AdaBoost: nWeak=128 nFtrs=2560 pos=10150 neg=30000
i= 16 alpha=5.000 err=0.000 loss=1.80e-35
stopping early


But if used opts.pPyramid.pChns.pFastMode.enabled=0; %default: 0
Adaboost train OK.

On the pFastMode.enabled = 1, The adaboost train easy to appear with early stopping on my training sample. How do I handle this situation?(I check the code in chnsCompute.m,it use cellSum to deal with channel feature,Maye be caused it?)

I am not sure about the reason for this issue as I have not faced this with the datasets that I have tried.

Question 1: As I understand, this issue happens only if your positive samples are more than 10000. Can you try to manually select a smaller set of positive samples, so that this issue is not there? Is this an acceptable solution.

Question 2: As I understand, you are able to train properly if you set:
opts.pPyramid.pChns.pFastMode.enabled=0;
Have you tried using the output descriptor (trained with this modification) in TDA2x object detection?