![]() This will allow your cursor to quickly navigate the cursor forward and backward within Terminal text by pressing option+f or option+b. One, suggestion is to make sure “Use Option as Meta key” is checked. In the Terminal app Preferences, there are many options for how you want the Terminal to look: what color scheme do you want? what type of cursor? should it blink? It is worth spending some time here and trying different effects. Along with setting in the OS, the bashrc helps determine how your command line interface (CLI) or Terminal app looks and acts. This will assume familiarity with github repos and homebrew taps.Ī bashrc file is shell script that Bash runs whenever it is started. There are other things you can do to display these, e.g.National Museum of African American History and Culture (NMAAHC) It's possible that the sort utility can't deal with the size of the list (you can work around this by using grep '^' output |sort >output-1 and grep -v '^' output |sort >output-2, then cat output-1 output-2 > output.sorted or thereabouts you may need more than two passes). Just pipe it into your output file and sort it later. If you have a really large list of images, do not run this through sort. ![]() Something like this exif_hash.sh (sorry, slashdot eats whitespace so this is not indented):Įcho "`exiftool |grep -ve 20.: -e 19.: -e File -e Directory |md5sum` $image"įind -typef -print0 |xargs -0 exif_hash.sh |sort > output Remove the items that refer to timestamp, file name, path, etc. I would write a script that runs exiftool on each file you want to test. Apparently there's also a findimagedupes tool available, see comments above (I wrote this before seeing that and had assumed apt-cache search had already been exhausted). Geeqie has a find-similar command, but it's only so good (image search is hard!). It will not find near-matches unless they have the same exif data. This will help find exact matches by exif data. 20140123_DCIM ) to begin with, and upload it to its final resting place on my main file server immediately, so I know all other copies I encounter on other household machines are redundant. That said, I've never had to use any of this stuff, because my habit was to rename my camera image dumps to a timestamped directory (e.g. I bet if you throw Picasa at your combined images directory, it might have some kind of "similar image" detection too, particularly since its sorts everything by exif timestamp. Resulting in substantial savings in disk storage and disk writes. #Bash duplicate md5 finder PcIdentical filesĪcross multiple backups of the same or different PC are stored only once * Clever pooling scheme minimizes disk storage and disk I/O. High-performance, enterprise-grade system for backing up PCsīackupPC is disk based and not tape based. Local and network or kioslave protocol folders.īackuppc : (just in case this was related to your intended use case for some reason) Itĭiscovers duplicate, newer or missing files and empty folders. Komparator is an application that searches and synchronizes two directories. * dead menu entries (.desktop files pointing to non-existing executables) * broken executables (executables with missing libraries) ![]() ![]() Search for files basing on several criterias you can seek for: KleanSweep allows you to reclaim disk space by finding unneeded files. On common image types,įindimagedupes seems to be around 98% accurate. This allows you to compare two images or a whole tree of images andĭetermine if any are similar or identical. #Bash duplicate md5 finder how toYeah, this Ask Slashdot should really be about teaching people how to search for packages in aptitude or whatever your package manager is.įinds visually similar or duplicate imagesįindimagedupes is a commandline utility which performs a rough "visual diff" to If the hashes are small enough to all live in memory (or enough of them that you can intelligently juggle your comparisons without having to wait on the disk too much), then you'll be fine for tens of thousands of pictures.īut photographers can take thousands of pictures per shoot, hundreds of You have to read all the images and generate the hashes, but that's Theta(n).Ĭomparing one hash to every other has is Theta(n^2). O(n^2) vs O(2^n) is a huge difference eve for very small datasets (hundreds of pictures). ![]() It's akin to running compression on a filesystem: read speed is an order of magnitude slower than the compression. I doubt the difference between O(2^n) and O(n^2) would make a huge impact anyway: the biggest bottleneck is going to be disk read and seek time, not comparing fingerprints. Fingerprints are then compared using an algorithm that looks like O(n^2). It creates a 16x16 thumbnail of each image (it's a little more complicated than that - read more on the manpage ), and uses this as a fingerprint. It's actually pretty nifty how findimagedupes works. Why do I have this sneaking suspicion it runs in exponential time, varying as the size of the data set. ![]()
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