Enot is a photo-cataloging software designed to avoid most problems of the existing cataloging solutions and ensure fast and simple search of certain photos within a large photo collection. The following is the list of main features introduced by Enot:
Database compatibility and data safety.
This is one of the main reasons why many people don't want to spend time on creating their databases. And it can be understood: you spend hours and days of work to maintain a database within your favorite viewer and one day when you find a better viewer you understand that you cannot convert your database to the new format. You can either keep on using your obsolete viewer or begin to retype your new database from the very beginning. Some databases are so awkwardly engineered that you don't even know how to backup it or migrate its files to another computer.
Enot solution: Enot keeps its database in a simple INI-like text file that can be viewed and edited in any text editor. Most programming languages has complete support of INI files, so even if you're not a programmer, you can hire one to convert your database to any format for a tiny fee. It also should be noted that Enot has an internal converter to the popular XML and HTML formats, but other formats compatibility can be achieved by editing Enot exporting template. To ensure safery Enot keeps two previous versions of the database in addition the the main database file, so it's not a problem to restore old data in case of unintentional changes or hardware malfunction during the saving process.
Good database engine with a poor viewer or a good viewer with poor database support.
We all have a set of favorite programs like e-mail clients, mp3 players and photo viewers and we feel uncomfortable when we have to fulfill everyday tasks in other software. So, when you find powerful photo-database software, you feel that its internal viewer is much worse than the one you usually use to view photos. This makes your work with the database annoying.
Enot solution: Enot has no internal viewer at all! It integrates with your favorite photo viewer. For instance, if you've got used to ACDSee, you search images in Enot and view the found images in ACDSee! This makes your work fast and easy.
Planned photo maintenance.
Suppose you decided to rename your photos or just move them to another folder or even to another computer. Most cataloging software will just fail to understand what's happened: they will think that the old photos were deleted as useless, and some new photos were added. All in all, you will lose all information that was kept for the renamed files.
Enot solution: Enot keeps not only file names, but also CRC32. The latter is almost always unique for files with different content and it's almost impossible to have two photos with the same CRC32 unless you keep duplicates of one and the same file with different file names. To reassign the records of the database to the renamed files, Enot scans your hard drive (or a specific folder) to find files with the same CRC32 that already saved in the database. The experience shows that this method works perfectly well even with the libraries that encounter several thousand photos!
Modification of original photo files.
Some cataloging software is based on keeping data in IPTC or EXIF records right inside original jpeg files. This is not always good: any photographer may have a number of points why he wants to preserve the original photo files untouched, for instance, to keep compatibility with the originating camera or to prevent the speading of personal data when the jpg-files go to other persons. Moreover, such software cannot work with files from read-only locations like CD or DVD discs.
Enot solution: The modification of original files is strictly prohibited. All data is kept in external databases only, although exif and iptc are supported to import data into Enot databases.
One database for all images.
It's clear that if you have photos for your work and your personal photos, you want to distinguish them and keep information about them in different databases. Say, if you are an insurance agent and if you search for 'car' photos in personal collection, you don't want to see the photos of insured cars from your work collection. And it's evident that you won't ever need 'nature' group for your work database, although you use this group in personal database. In home computers, when there are usually two or more users, it's convenient to have one database for every user. For instance, if you look for "friends" keyword in your database, you won't find the photos of your spouse's friends.
Enot solution: Unlimited number of databases for any kinds of needs. The list of search groups is customized separately for every database.
Bad differentiation of information by its content.
This is a well known problem of cataloging software - either too many useless fields to fill out for each file, or just a possibility to add a simple text comment. Thus, if you want to see all photos taken in London, you also get a bunch of pictures that have nothing to do with London just because you added to the comment field something like "the photo was taken a few minutes before Mike went off to London to see his friends".
Enot solution: A comprehensive differentiation of information and no excessive fields - there exist only those fields that can be used to find a certain photo easily and quickly, the rest of information is stored in the lengthless 'Comment' field.
Obsolete idea of categories.
Most cataloging programs that allow you to assign categories to a photo do it in the simplest way possible. Of course, you can have categories like "Friends", "Nature", etc, but what if you want to widen the possibility to find the photos of your friends?
Enot solution. Simple categories are supported by Enot only for those of you who got used to them. The others would likely use Enot groups. This is a tree-like 3D replacement of usual categories. You think of several main groups that are important to you, for example, "Nature", "Cities", "Trips", "People"… and combine them in any possible way, starting from the widest group and ending with the narrowest group. Thus, if you went to trip with your relatives and friends, you can add such groups: "\Trips\People\Friends", "\Trips\People\Relatives". Now, when you want to see all pictures taken in the London trip, you can just search for "\Trips\London", and if you are interested in the photos of your friends and relatives, you search for "\Trips\London\People". Finally, if you need to sort out only the photos of your relatives, taken in London trips, skipping all other photos, you search for "\Trips\London\People\Relatives". There is also search by simple components of the groups; for instance, searching for "People" will give not only "\Trips\People\Friends" and "\Trips\People\Relatives", but also "\Home\People\", "\Celebrations\People\Friends" and such.
Limited time for viewing.
It happened that you found 10 free minutes to recall your trip to London by seeing a slideshow of your photos. You type 'London' in your database engine and find that there are 1000 photos to see. Even if you'll spend 5 seconds for each photo, it will take 1 hour and 23 minutes, you just can't afford it now! Although many powerful cataloging programs allow to assess every photo, it's not really clear what is assessed: quality or personal value of the image. For instance, you can have a blurred photo showing the face of your friend. Yes, this photo is dear to you and sometimes it's interesting to recollect every funny moment of a trip, but its artistic value tends to zero and in most cases you would prefer to see photos of higher quality. At the other hand, you may have a few photos that don't show anything which can call up any vivid recollections but do look as masterpieces that might be interesting to somebody else but you. This example shows that a photo cannot be assessed by only one parameter.
Enot solution: Enot allows you to assess images by two parameters: impression and quality of the photo. The major of the two is impression, it's how dear the photo to you. The deeper the feelings it gives to you are, the better the impression is. The 'slight' impression is assigned to photos that don't give you any thoughts except "I was there". The 'vivid' impression is set to the photos that you want to see again and again. The 'neutral' impression goes to all other photos. Quality of the image is the secondary assessment for home users and the primary one for professional photographers. It allows you to assess the artistic value and the quality of the image. For instance, if a photo shows an atristically photographed tree, its impression may be 'slight', but its quality may be 'high'. And if a blurred and darkened photo shows your body opposite the Sphinx (but it's not really clear that it's you!), its impression may be 'vivid' (because you don't go to Egypt everyday), but the quality looks as 'low' (because you can't recognize even your own face). Returning to our example with viewing 1000 London photos in 10 minutes, now you probably guessed that it's possible to do it if you sort out only 'vivid'-impression photos of 'normal' and 'best' quality.
I'm a snail, doing it one-by-one, expect to finish it in 10 years - please don't distract me...
One question: do the developers of modern photo organizers really think you're going to fill out one and the same piece of data manually for more then 100 images? Hah...
Enot solution: Batch processes for selected images. For example, if 100 photos were taken in London, just check them, type "London" in the "location" field and start the batch process. That's all, no need to type "London" 100 times!
Pathetic search possibilities.
Search by photo name and keywords only cannot give acceptable results - you will always have redundant images that you didn't want to find.
Enot solution: There are a lot of filters available for search now and a few new filters will be added later. For example, what catalog software will find images taken not farther than 20 kilometers away from the place where the selected photo was taken? Enot will do it. There are also filters by location, date range, photo quality, season, etc...