Setting other activations to zero

[lgsaber]

Hi~ Thank you for developing such a nice visualization tool. Just a small question regrading the test_deconv.py you provided as the demo. If I recall correctly it was said in Matthew's paper (http://www.matthewzeiler.com/pubs/arxive2013/eccv2014.pdf) that this deconvnet could only be used to visualize a single activation in a certain feature map, and thus we have to set the other activations to zero. While the following lines in test_deconv.py

feat = net.blobs['pool5'].data
feat[0][feat[0] < 150] = 0

seems to set only the activations smaller than 150 to zero, and I wonder if this might contradict with the original idea of the paper?
Thank you!

[piergiaj]

I think this would be open to interpretation of the idea and results. I see no reason why this cannot be used to for multiple features. For example, if you start with only 1 activation in pool5, this will become several activation in a lower layer, such as pool2, and those will all be used to create the image. He never stated that this would only work using 1 activation, I think the paper may have just reported results using 1 activation (though it has been a while since I've read the paper, I could be wrong).