Posted by
Ignacio Arganda-Carreras on
Aug 28, 2014; 10:00am
URL: http://imagej.273.s1.nabble.com/Creating-DataSet-after-building-classification-with-Trainable-Weka-Segmentation-tp5009283p5009395.html
OK, I see what you're trying to do now.
TWS is designed for pixel classification, not image classification. For the
latest, you will need to create your own plugin and features. The idea
would be very similar to TWS but you'll need a single final class per image
and features that are image-based.
You can also use existing software such as PiXiT:
http://www.montefiore.ulg.ac.be/~maree/pixit.htmlBest,
ignacio
On Thu, Aug 28, 2014 at 11:34 AM, marcelo_chong <
[hidden email]> wrote:
> Hello Ignacio,
>
> Thanks for the reply again.
>
> I understand now about the instance it create after i load in the 10
> images.
>
> thanks for the explanation.
>
> So i would like to ask, hope you won't mind :P
>
> If I want to use TWS with Fiji to build a training arff dataset with a set
> of images
>
> so i can build up a classification model in weka
>
> Then i want to use it to classify some images, let say Lion and other
> animals.
>
> So am i work on the correct way with TWS now, or i go the wrong direction?
>
> coz now even I load in 10 images and create about 3000 instances for test.
> But I don't know
>
> which image is classify as LION or not LION, coz it is in pixel level.
>
> Sorry a little bit out of the scope.
>
> Thx.
>
>
>
> --
> View this message in context:
>
http://imagej.1557.x6.nabble.com/Creating-DataSet-after-building-classification-with-Trainable-Weka-Segmentation-tp5009283p5009394.html> Sent from the ImageJ mailing list archive at Nabble.com.
>
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--
Ignacio Arganda-Carreras, Ph.D.
Seung's lab, 46-5065
Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology
43 Vassar St.
Cambridge, MA 02139
USA
Phone: (001) 617-324-3747
Website:
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