Using DCP to detect sequential image "Sets"
Posted: Thu Jun 18, 2026 5:07 am
I’m using DC v.4.01. I have an image Directory with numerous folders containing well over 150,000 images spread out between them. I’ve been using DC for years and it’s been quite useful for detecting and removing hundreds and even thousands of duplicates that have accumulated over time after constantly adding new images to the Directory.
However, in addition to duplicates I also have another tedious challenge when working with such a massive number of files: Finding image “sets” – meaning, sequential images containing the same individual, object or scape that are part of a “set”, which can be from a few images, to dozens.
When doing a DC scan using anything except “exact match” DC usually detects several images that may appear to be DUPS but are actually part of a set. I mark those separately and use the MOVE feature to move them to another folder titled “sets” where I then go and compile the sets.
The problem is that it’s inconsistent and DC will place images that are actually part of a set into different groups, so by the time I get to Group#244 I might see an image I recognize as being the same person and probably part of a set, but by then I can’t remember what earlier Group it was in. DC also can’t seem to detect all the images which are part of that set so there are always some missing which I end up finding later when sorting manually.
Is there some trick or filter that could be used for the detection of sets containing sequential images?
I created a test folder where I put numerous sets plus hundreds of randoms and I’ve tried every option and/or filter I could think of but with no success. I would think that using the “Same Created Date” and/or the “Same Modified Date” would give accurate or at least better results on the test sets because each image in the set has the same unique date as the rest of the images in the entire set. Other filters/settings don’t seem to work because not all images have metatag/metadata or other unique identifiers.
No matter how I run the scans DC will only detect maybe 4-5 images out of a set containing 15-20 and even then it will put them in different Groups rather than one single Group.
Any recommendations on settings or filters that might yield more accurate or at least better results?
However, in addition to duplicates I also have another tedious challenge when working with such a massive number of files: Finding image “sets” – meaning, sequential images containing the same individual, object or scape that are part of a “set”, which can be from a few images, to dozens.
When doing a DC scan using anything except “exact match” DC usually detects several images that may appear to be DUPS but are actually part of a set. I mark those separately and use the MOVE feature to move them to another folder titled “sets” where I then go and compile the sets.
The problem is that it’s inconsistent and DC will place images that are actually part of a set into different groups, so by the time I get to Group#244 I might see an image I recognize as being the same person and probably part of a set, but by then I can’t remember what earlier Group it was in. DC also can’t seem to detect all the images which are part of that set so there are always some missing which I end up finding later when sorting manually.
Is there some trick or filter that could be used for the detection of sets containing sequential images?
I created a test folder where I put numerous sets plus hundreds of randoms and I’ve tried every option and/or filter I could think of but with no success. I would think that using the “Same Created Date” and/or the “Same Modified Date” would give accurate or at least better results on the test sets because each image in the set has the same unique date as the rest of the images in the entire set. Other filters/settings don’t seem to work because not all images have metatag/metadata or other unique identifiers.
No matter how I run the scans DC will only detect maybe 4-5 images out of a set containing 15-20 and even then it will put them in different Groups rather than one single Group.
Any recommendations on settings or filters that might yield more accurate or at least better results?