> detects faces, we would put "face" into this field. Other things that it
> > can detect would result in other keywords.
> >
> > For the color search, I have a few inter-related hurdles. I've got to
> > figure out what form the color data actually takes a
the image. If it
> detects faces, we would put "face" into this field. Other things that it
> can detect would result in other keywords.
>
> For the color search, I have a few inter-related hurdles. I've got to
> figure out what form the color data actually takes an
equired an explanation.)
http://en.wikipedia.org/wiki/Magenta
Dennis Gearon
Signature Warning
EARTH has a Right To Life,
otherwise we all die.
Read 'Hot, Flat, and Crowded'
Laugh at http://www.yert.com/film.php
--- On Thu, 9/16/10, Shawn Heisey wrote:
> From: Shawn Hei
her
things that it can detect would result in other keywords.
For the color search, I have a few inter-related hurdles. I've got to
figure out what form the color data actually takes and how to represent
it in Solr. I need Java code for Solr that can take an input color
value and find simila
From: Shashi Kant
> Subject: Re: Color search for images
> To: solr-user@lucene.apache.org
> Date: Thursday, September 16, 2010, 6:36 AM
> On Thu, Sep 16, 2010 at 3:21 AM,
> Lance Norskog
> wrote:
> > Yes, notice the flowers are all a medium-dark crimson
> red. There are
rning
EARTH has a Right To Life,
otherwise we all die.
Read 'Hot, Flat, and Crowded'
Laugh at http://www.yert.com/film.php
--- On Wed, 9/15/10, Shashi Kant wrote:
> From: Shashi Kant
> Subject: Re: Color search for images
> To: solr-user@lucene.apache.org
> Da
> Lire looks promising, but how hard is it to integrate the content-based
> search into Solr as opposed to Lucene? I myself am not a Java developer. I
> have access to people who are, but their time is scarce.
>
Lire is a nascent effort and based on a cursory overview a while back,
IMHO was an
On Thu, Sep 16, 2010 at 3:21 AM, Lance Norskog wrote:
> Yes, notice the flowers are all a medium-dark crimson red. There are a bunch
> of these image-indexing & search technologies, but there is no (to my
> knowledge) "finished technology"- it's very much an area of research. If you
> want to sear
On 9/15/2010 10:50 AM, Shashi Kant wrote:
Shawn, I have done some research into this, machine-vision especially
on a large scale is a hard problem, not to be entered into lightly. I
would recommend starting with OpenCV - a comprehensive toolkit for
extracting various features such as Color, Edge
Yes, notice the flowers are all a medium-dark crimson red. There are a
bunch of these image-indexing & search technologies, but there is no (to
my knowledge) "finished technology"- it's very much an area of research.
If you want to search the word 'flower' and index data that can find
blobs of
do you mean content based image retrieval or just search images by tag?
if the former, you can try LIRE
2010/9/15 Shawn Heisey :
> My index consists of metadata for a collection of 45 million objects, most
> of which are digital images. The executives have fallen in love with
> Google's color im
There's a project out there called LIRE (I heard about it on this list) that's
supposed to create a lucene-based CIBR index for images. I wonder if this
could be integrated with Solr? Personally I don't really care about the flower
part, I'm more worried about searching whether the flower is r
> I'm sure there's some post doctoral types who could get a graphic shape
> analyzer, color analyzer, to at least say it's a flower.
>
> However, even Google would have to build new datacenters to have the
> horsepower to do that kind of graphic processing.
>
Not necessarily true. Like.com - whi
all die.
Read 'Hot, Flat, and Crowded'
Laugh at http://www.yert.com/film.php
--- On Wed, 9/15/10, Ken Krugler wrote:
> From: Ken Krugler
> Subject: Re: Color search for images
> To: solr-user@lucene.apache.org
> Date: Wednesday, September 15, 2010, 9:41 AM
>
> On
>
> On a related note, I'm curious if anyone has run across a good set of
> algorithms (or hopefully a library) for doing naive image
> classification. I'm looking for something that can classify images
> into something similar to the broad categories that Google image
> search has (Face, Photo, Cl
Shawn, I have done some research into this, machine-vision especially
on a large scale is a hard problem, not to be entered into lightly. I
would recommend starting with OpenCV - a comprehensive toolkit for
extracting various features such as Color, Edge etc from images. Also
there is a project LIR
On Wed, Sep 15, 2010 at 12:41 PM, Ken Krugler
wrote:
>
> On Sep 15, 2010, at 7:59am, Shawn Heisey wrote:
>
>> My index consists of metadata for a collection of 45 million objects, most
>> of which are digital images. The executives have fallen in love with
>> Google's color image search. Here's
On Sep 15, 2010, at 7:59am, Shawn Heisey wrote:
My index consists of metadata for a collection of 45 million
objects, most of which are digital images. The executives have
fallen in love with Google's color image search. Here's a search
for "flower" with a red color filter:
http://www.
My index consists of metadata for a collection of 45 million objects,
most of which are digital images. The executives have fallen in love
with Google's color image search. Here's a search for "flower" with a
red color filter:
http://www.google.com/images?q=flower&tbs=isch:1,ic:specific,isc
: I used the same field name (color), not 10 different names (c0 - c9).
ah .. got it. then what you are probably seeing is because of length
normalization, if you use omitNorms="true" then it shouldn't matter.
(i don't know why i suggested a seperate field for each 10% block ... i'm
sure i ha
>
> can you you explain exactly how you are indexing the data and what your
> query looks like?
>
I used the same field name (color), not 10 different names (c0 - c9).
So the index fields look like (50% #00, 20% #99):
color: #00
color: #00
color: #00
color: #00
color: #000
: extraction algorithm, etc.) So, for a product with 50% of #00, and 20%
: of #99, I'll have to fill the remaining three fields with some dummy
: values. Otherwise, Lucene seems to score it higher than products that also
: have 50% of #00, but more than 20% of some other colors. Since
Thanks for all the replies. I think creating 10 fields and feeding each
field with a color's value for 10% from that color is a reasonable approach,
and easy to implement too. One problem though, is that not all products have
a total of 100% colors (due to various reasons including our color
extrac
On 28-Sep-07, at 6:31 AM, Grant Ingersoll wrote:
Another option would be to extend Solr (and donate back) to
incorporate Lucene's payload functionality, in which case you could
associate the percentile of the color as a payload and use the
BoostingTermQuery... :-) If you're interested in
: useful to search products by color. A product image can have up to 5 colors
: (from a color space of about 100 colors), so we can implement it easily with
: Solr's facet search (thanks all who've developed Solr).
:
: The problem arises when we try to sort the results by the color relevancy.
: W
This discussion is incredibly interesting to me! We solved this
simply by indexing the color names, and faceting on that. Not a very
elegant solution, to be sure - but it works. If people search for a
"green running shoe" they get -green- running shoes.
I would be very very interested in ha
--Renaud
>
>
> -Original Message-
> From: Steven Rowe [mailto:[EMAIL PROTECTED]
> Sent: Friday, September 28, 2007 7:14 AM
> To: solr-user@lucene.apache.org
> Subject: Re: Color search
>
> Hi Guangwei,
>
> When you index your products, you could have a
riday, September 28, 2007 7:14 AM
To: solr-user@lucene.apache.org
Subject: Re: Color search
Hi Guangwei,
When you index your products, you could have a single color field, and
include duplicates of each color component proportional to its weight.
For example, if you decide to use 10% increments, for your
Hi Guangwei,
When you index your products, you could have a single color field, and
include duplicates of each color component proportional to its weight.
For example, if you decide to use 10% increments, for your black dress
with 70% of black, 20% of gray, 10% of brown, you would index the
follo
Another option would be to extend Solr (and donate back) to
incorporate Lucene's payload functionality, in which case you could
associate the percentile of the color as a payload and use the
BoostingTermQuery... :-) If you're interested in this, a discussion
on solr-dev is probably warrant
If it were just a couple of colors, you could have a separate field
for each color and then index the percent in that field.
black:70
grey:20
and then you could use a function query to influence the score (or you
could sort by the color percent).
However, this doesn't scale well to a large index
Hi,
We're running an e-commerce site that provides product search. We've been
able to extract colors from product images, and we think it'd be cool and
useful to search products by color. A product image can have up to 5 colors
(from a color space of about 100 colors), so we can implement it easil
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