stut-it Martin Stut - Information Technology Tailored to You
By Martin Stut, 2009-01-17
I'm no longer experimenting with this one, because I put it into continuous "production" use. When I was looking for a solution in early 2008, Jbrout was the only piece of software I found that fit my needs of managing the flood of picture my digital camera is producing:
Jbrout is implemented in Python, a nice programming language that has runtime environments available for all major platforms.
It reads and writes the JPG comment fields of the picture file itself, so there are no external databases to synchronize. If you lose the few metadata files Jbrout keeps, you can just re-import the picture directory (subdirectories are automatically included) and the index and the tag list is rebuilt automatically. The only thing you would lose is the categorization of tags - something I'm not even sure it is particularly useful, let alone required. I use tag categories, but start finding them irritating.
Tags are stored as IPTC tags. I've heard, that this standard is becoming obsolete, but I did not find any useable free software handling the new XMP standard. So I decided to stay with IPTC. When free XMP applications will come up, I hope they will have an option to import IPTC tags.
Getting started is as easy as it could be: install the software (platform dependent, but easy enough) and import the directories (called albums in Jbrout) where you have already stored the pictures. You can have several albums in completely separate branches of your directory tree; all are accessible through a common index.
If there are already tags in the pictures, these tags are imported into the tag list. You can easily add new tags to the tag list.
Tagging images is straightforward: select the images to tag (even all the 800 pictures from Japan were o.k. to select in one go) and drag the tag (e.g. "Japan") onto one of the selected images. Depending on CPU and disk speed and the number of selected pictures, it might take a while until all pictures have got their tag.
Here are ballpark figures of the extremes I have encountered: The slowest, about 1 picture tag per second, was to a samba share on my 120 MHz P1 server (retired in May 2008) with a 40 GB IDE disk (bought in December 2001) over 54 Mbps WLAN. The fastest, about 10-20 picture tags per second, was locally on my 1.6 GHz P4 workhorse desktop with a new 500 GB IDE disk.
The search options are really cute. You can select single or multiple tags, time ranges etc., so if you got your tag system right, you can really find the buried gems in your picture collection.