I'm on roll. Just pushed my latest project, KQueryBrowser, to github. KQB is a database query tool for KDE that uses qt-webkit to format the query results nicely. And yes, I know the name is highly unoriginal and follows that annoying K<something> pattern, but at least it's descriptive.
The motivation for this yet another query tool was simply that I did not like any of the other query tools. The command like clients are nice, but awkward when browsing through very large tables. MySQL query browser was great, but was replaced by MySQL Workbench, which is way too cumbersome when I just want to run some SELECTs. Pgadmin suffers from the same problem. And most of the graphical tools use GTK, which makes them look ugly or (in the case of MySQL workbench) simply broken on KDE.
So here's KQB. Looks pretty on KDE, works with multiple databases and lets you get straight to writing queries.
Sunday, November 27, 2011
Sunday, November 6, 2011
Piqs
I just created a new repository on github for yet another hobby project I've been working on: piqs. It's a lightweight image gallery program with advanced tagging capabilities.
It's an experiment in alternative categorization; rather than sorting images into albums/folders, they are all shown in a single flat view, but that view can be filtered with tag queries. Of course, lots of gallery software have tagging capabilities nowadays, but piqs takes it a bit further. You can set up tag aliases and implication rules and something I don't think I've seen elsewhere: tag namespaces. For example, the tag string "[cat, orange], [dog, yellow], backyard" might be applied to a photo of an orange cat and a black dog taken in the backyard. The search string "cat, orange" will return all pictures with a cat and something orange, but the more specific "[cat, orange]" will return pictures of orange cats only. Further, boolean operators are supported: "cat, !dog" will return pictures with cats, but not dogs. "cat, (!dog|[dog,black])" will return pictures with cats and no dogs, unless the dog is black.
This sort of tagging only really starts to pay off once the image collection starts getting very large, so I've tried to design piqs to support huge galleries. So far, I've tried it with about 50000 untagged images and it hasn't choked yet. To help tag every image comprehensively, piqs can infer new tags based on a set of rules. E.g. the rules "cat --> mammal, carnivore", "mammal --> animal" will automatically add the tags "animal", "carnivore" and "mammal" to a picture tagged with "cat".
It's an experiment in alternative categorization; rather than sorting images into albums/folders, they are all shown in a single flat view, but that view can be filtered with tag queries. Of course, lots of gallery software have tagging capabilities nowadays, but piqs takes it a bit further. You can set up tag aliases and implication rules and something I don't think I've seen elsewhere: tag namespaces. For example, the tag string "[cat, orange], [dog, yellow], backyard" might be applied to a photo of an orange cat and a black dog taken in the backyard. The search string "cat, orange" will return all pictures with a cat and something orange, but the more specific "[cat, orange]" will return pictures of orange cats only. Further, boolean operators are supported: "cat, !dog" will return pictures with cats, but not dogs. "cat, (!dog|[dog,black])" will return pictures with cats and no dogs, unless the dog is black.
This sort of tagging only really starts to pay off once the image collection starts getting very large, so I've tried to design piqs to support huge galleries. So far, I've tried it with about 50000 untagged images and it hasn't choked yet. To help tag every image comprehensively, piqs can infer new tags based on a set of rules. E.g. the rules "cat --> mammal, carnivore", "mammal --> animal" will automatically add the tags "animal", "carnivore" and "mammal" to a picture tagged with "cat".
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