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I'm currently coding up a new normalized Haar wavelet decomposer/sorter/coefficient generator for use in the image detector, due to the fact that rq's doesn't really work.
The algorithm that was being tested was the multiresolution image query as described in Jacobs et. al. (http://grail.cs.washington.edu/projects/query/). The fuzziness of the search didn't even come into play here---those two above posts had the -exact- same wavelet coefficients. All 120 of them.
rq wasn't kidding when he said the storage requirements were considerable. The coefficient table with 8600 posts will contain over a million rows (120 rows/image).
My query code also needs a lot of work: I'm looking at about 15 seconds to match one image out of eight thousand. Jacobs et al did it in half a second on a database of 20,000 images. In 1995.
That being said, no, I really don't want to use an imported algorithm not least because:
a) if I don't understand it, I won't be able to fix it b) I'm a kernel-side C programmer, so I should be able to make it fast and small enough to be usable on a near-interactive basis.
viiv, I also took a look at imgseek. Their web-based demo turned up some pretty crappy results (e.g., a similar image search for snowflakes turns up... grass and other random things, but certainly not snowflakes). Plus it's GPL'd, while danbooru is intentionally BSD-licensed. I don't want to get into any tainted code issues.
Things to look forward to (assuming I have enough time to finish):
The ability to see possible dupes as you upload
The ability to search for portions of images:
--> You can search for a certain artist's eyes --> Or, perhaps, panty styles etc.
If anybody's got a handy reference for wavelet theory that isn't filled with math junk way over the top of my head (I really don't need a comparison to Fourier transforms, and a coverage of the continuous wavelet transform is immaterial) I'd really, really appreciate it.
cyanoacry
E.g., according to the algorithm in the tree right now, http://moe.imouto.org/post/show/628 and http://moe.imouto.org/post/show/3443 are identical. This needs some work.
The algorithm that was being tested was the multiresolution image query as described in Jacobs et. al. (http://grail.cs.washington.edu/projects/query/). The fuzziness of the search didn't even come into play here---those two above posts had the -exact- same wavelet coefficients. All 120 of them.
rq wasn't kidding when he said the storage requirements were considerable. The coefficient table with 8600 posts will contain over a million rows (120 rows/image).
My query code also needs a lot of work: I'm looking at about 15 seconds to match one image out of eight thousand. Jacobs et al did it in half a second on a database of 20,000 images. In 1995.
That being said, no, I really don't want to use an imported algorithm not least because:
a) if I don't understand it, I won't be able to fix it
b) I'm a kernel-side C programmer, so I should be able to make it fast and small enough to be usable on a near-interactive basis.
viiv, I also took a look at imgseek. Their web-based demo turned up some pretty crappy results (e.g., a similar image search for snowflakes turns up... grass and other random things, but certainly not snowflakes). Plus it's GPL'd, while danbooru is intentionally BSD-licensed. I don't want to get into any tainted code issues.
Things to look forward to (assuming I have enough time to finish):
- The ability to see possible dupes as you upload
- The ability to search for portions of images:
--> You can search for a certain artist's eyes--> Or, perhaps, panty styles etc.
If anybody's got a handy reference for wavelet theory that isn't filled with math junk way over the top of my head (I really don't need a comparison to Fourier transforms, and a coverage of the continuous wavelet transform is immaterial) I'd really, really appreciate it.
So far I've been working off of this article:
http://www.spelman.edu/~colm/wav.pdf
Normalized Haar wavelets are the easiest due to the averaging-and-differencing method you can use to implement them.
If anybody's got tips/experience in this field, I'd love to hear it!