Re: [Rtftr-devel] Detection improvement

[Abhishek D. <the...@gm...>]

Hi Anjan,
The results look good. I think you need not bother about training now. You
can perform training during the time when we restart our work after exams
(end of Feb. 2009). By that time, the loadshedding will probably decrease.
We can also share batteries if required. My home has also started seeing
normal loadshedding schedules now (I think that the vip house has been
equipped with generators). So I cannot help.

Meanwhile, you can experiment on the technique of using both cores for
processing. If you have any other plans that will help, we can go for that.

bye

On Sat, Jan 10, 2009 at 6:51 PM, Anjan <roc...@gm...> wrote:

> Hi all,
> The adaboost algorithm is improving :) . The image attached is the
> detection after training upto 3 stages. The false detections are reduced
> when the stages are increased.
>
> Result:
> Stages: 3
> Test Image size: 316x102
> Detection Time:  0.36087 secs (hopefully ok for real-time)
>
>
> Now, i'm sure that the adaboost algorithm training in large scale is ready,
> after which the detection rate and false detection will be as expected. But
> the problem is with the training, which takes a lot of time (at least a
> week). The loadshedding is such a pain in the ass. What do you guys suggest
> for that. I'll be looking for how the multi-processing can be done to speed
> up the training. I have found that some part of my code can be performed by
> multi-processing, but i've not tried it yet. In Open MP we can have multiple
> thread, but in my test i found that all those threads run in the same core.
> Further research is needed.
> What's your view on where can we start the training.
>
> --
> Anjan Nepal
>
> GPO Box 11458
> Registered Linux User #395963
>
>
>
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-- 
Abhishek
http://adutta.np.googlepages.com