24.01.2020, 07:59
(Dieser Beitrag wurde zuletzt bearbeitet: 24.01.2020, 08:01 von Peter Gallagher.)
I updated to 2.0 but am disappointed by it's keywording performance. I don't need elaborate keywords (one or two usually) but Excire 2.0 seems to miss the obvious. My LR catalog has several dozen images of paintings from galleries, usually in a frame on the gallery wall. None of them is anything but a plain representation of the actual painting. When I re-initialized my database for Excire 2.0 it attached the "Painting" keyword to just 5 of all of these images. There is no obvious reason why.
In fact, several of the images that Excire 2.0 failed to classify with the "Painting" keyword in its database had a keyword 'painting' in the keyword field of my LR database!
I want to re-train the search engine to attribute the Painting keyword to the other paintings. A couple of years ago (or more) you indicated on this forum that you would provide re-training options for Excire. But nothing seems to have been done about this.
How can I remedy this deficiency in my Excire 2.0 database? I suspect I'll find other similar examples of wrong or deficient keyword attribution.
In fact, several of the images that Excire 2.0 failed to classify with the "Painting" keyword in its database had a keyword 'painting' in the keyword field of my LR database!
I want to re-train the search engine to attribute the Painting keyword to the other paintings. A couple of years ago (or more) you indicated on this forum that you would provide re-training options for Excire. But nothing seems to have been done about this.
How can I remedy this deficiency in my Excire 2.0 database? I suspect I'll find other similar examples of wrong or deficient keyword attribution.