Compares each photo with the names of the key's results and ranks the
results by how well they match, so a photo can be checked against the
species the key covers. This works best with a model trained on names of
organisms, such as BioCLIP 2 (visionModel(name = "bioclip-2")): it
recognises a species from its scientific name without being shown any
examples. Only the key's own species are considered, which makes the
answers much more reliable than asking the model to name a species out of
all those it knows.
Arguments
- key
A dimoose key.
- model
- paths
Image files, or an
imageSet()(itspathcolumn is embedded and itsidcolumn names the rows).- top
How many of the best-matching results to return per photo.
- prompt
The text each name is put into, with
%swhere the name goes. The default is the one BioCLIP was trained with.
Value
A data frame with top rows per image: image (its id), rank,
Taxon, probability and similarity (cosine similarity).
Details
Each result is described by its scientific name when it is written as
"Common name (Genus species)", and by the whole result otherwise. The
probabilities are a softmax over all the key's results with the
temperature CLIP models are trained with (cosine similarity times 100).
See also
identifyPhotos() for one answer per photo, at the genus or
family when the species is uncertain.
Examples
if (FALSE) { # \dontrun{
model <- visionModel(name = "bioclip-2")
suggestSpecies(montanaKey(), model, "my-photo.jpg")
} # }