diff --git a/scripts/larvatagger b/scripts/larvatagger
index 6425ae80dbe56a837c0f0ef315db5f771cf6dd1d..d9a475be6a19e7f2cab8feccfc1feea31bd87bf4 100755
--- a/scripts/larvatagger
+++ b/scripts/larvatagger
@@ -34,6 +34,7 @@ Usage:
larvatagger train <backend-path> <data-path> <model-instance> [--pretrained-model=<instance>] [--labels=<comma-separated-list>] [--sample-size=<N>] [--balancing-strategy=<strategy>] [--class-weights=<csv>] [--manual-label=<label>] [--layers=<N>] [--iterations=<N>] [--seed=<seed>] [--debug]
larvatagger train <backend-path> <data-path> <model-instance> --fine-tune=<instance> [--balancing-strategy=<strategy>] [--manual-label=<label>] [--iterations=<N>] [--seed=<seed>] [--debug]
larvatagger predict <backend-path> <model-instance> <data-path> [--output=<filename>] [--make-dataset] [--skip-make-dataset] [--data-isolation] [--debug]
+ larvatagger predict <backend-path> <model-instance> <data-path> --embeddings [--data-isolation] [--debug]
larvatagger merge <input-path> <input-file> [<output-file>] [--manual-label=<label>] [--decode]
larvatagger -V | --version
larvatagger -h | --help
@@ -59,6 +60,7 @@ Options:
--seed=<seed> Seed for the backend's random number generators.
--segment=<t0,t1> Start and end times (included, comma-separated) for cropping and including tracks.
--debug Lower the logging level to DEBUG.
+ --embeddings (MaggotUBA) Call the backend to generate embeddings instead of labels.
--decode Do not encode the labels into integer indices.
--copy-labels Replicate discrete behavior data from the input file.
--default-label=<label> Label all untagged data as <label>.
diff --git a/src/Taggers.jl b/src/Taggers.jl
index 38f57c2e1683e57a49b83f3da2c3bf66744e678c..f75bb50625b14544dbda737e13752865f20c4d0d 100644
--- a/src/Taggers.jl
+++ b/src/Taggers.jl
@@ -2,7 +2,7 @@ module Taggers
import PlanarLarvae.Formats, PlanarLarvae.Dataloaders
-export Tagger, isbackend, resetmodel, resetdata, train, predict, finetune
+export Tagger, isbackend, resetmodel, resetdata, train, predict, finetune, embed
struct Tagger
backend_dir::String
@@ -247,4 +247,14 @@ function finetune(tagger::Tagger; original_instance=nothing, kwargs...)
return ret
end
+function embed(tagger::Tagger; kwargs...)
+ args = ["--model-instance", tagger.model_instance]
+ if !isnothing(tagger.sandbox)
+ push!(args, "--sandbox")
+ push!(args, tagger.sandbox)
+ end
+ parsekwargs!(args, kwargs)
+ run(Cmd(`poetry run tagging-backend embed $(args)`; dir=tagger.backend_dir))
+end
+
end # module
diff --git a/src/cli.jl b/src/cli.jl
index ed85b62563a56cc43b110c207bdd43b6577c9f42..c0a25fbc05090bc4e0ee55eb5c23388c8b7e62d6 100644
--- a/src/cli.jl
+++ b/src/cli.jl
@@ -14,6 +14,7 @@ Usage:
larvatagger.jl train <backend-path> <data-path> <model-instance> [--pretrained-model=<instance>] [--labels=<comma-separated-list>] [--sample-size=<N>] [--balancing-strategy=<strategy>] [--class-weights=<csv>] [--manual-label=<label>] [--layers=<N>] [--iterations=<N>] [--seed=<seed>] [--debug]
larvatagger.jl train <backend-path> <data-path> <model-instance> --fine-tune=<instance> [--balancing-strategy=<strategy>] [--manual-label=<label>] [--iterations=<N>] [--seed=<seed>] [--debug]
larvatagger.jl predict <backend-path> <model-instance> <data-path> [--output=<filename>] [--make-dataset] [--skip-make-dataset] [--data-isolation] [--debug]
+ larvatagger.jl predict <backend-path> <model-instance> <data-path> --embeddings [--data-isolation] [--debug]
larvatagger.jl merge <input-path> <input-file> [<output-file>] [--manual-label=<label>] [--decode]
larvatagger.jl -V | --version
larvatagger.jl -h | --help
@@ -39,6 +40,7 @@ Options:
--seed=<seed> Seed for the backend's random number generators.
--segment=<t0,t1> Start and end times (included, comma-separated) for cropping and including tracks.
--debug Lower the logging level to DEBUG.
+ --embeddings (MaggotUBA) Call the backend to generate embeddings instead of labels.
--decode Do not encode the labels into integer indices.
--copy-labels Replicate discrete behavior data from the input file.
--default-label=<label> Label all untagged data as <label>.
diff --git a/src/cli_toolkit.jl b/src/cli_toolkit.jl
index 109cde44e83fc88ae9b780d7bd439bd66cbe9963..5614735f43da6693ad420b0a416c32c74792c9b3 100644
--- a/src/cli_toolkit.jl
+++ b/src/cli_toolkit.jl
@@ -19,6 +19,7 @@ Usage:
larvatagger-toolkit.jl train <backend-path> <data-path> <model-instance> [--pretrained-model=<instance>] [--labels=<comma-separated-list>] [--sample-size=<N>] [--balancing-strategy=<strategy>] [--class-weights=<csv>] [--manual-label=<label>] [--layers=<N>] [--iterations=<N>] [--seed=<seed>] [--debug]
larvatagger-toolkit.jl train <backend-path> <data-path> <model-instance> --fine-tune=<instance> [--balancing-strategy=<strategy>] [--manual-label=<label>] [--iterations=<N>] [--seed=<seed>] [--debug]
larvatagger-toolkit.jl predict <backend-path> <model-instance> <data-path> [--output=<filename>] [--make-dataset] [--skip-make-dataset] [--data-isolation] [--debug]
+ larvatagger-toolkit.jl predict <backend-path> <model-instance> <data-path> --embeddings [--data-isolation] [--debug]
larvatagger-toolkit.jl merge <input-path> <input-file> [<output-file>] [--manual-label=<label>] [--decode]
larvatagger-toolkit.jl -V | --version
larvatagger-toolkit.jl -h | --help
@@ -38,6 +39,7 @@ Options:
--seed=<seed> Seed for the backend's random number generators.
--segment=<t0,t1> Start and end times (included, comma-separated) for cropping and including tracks.
--debug Lower the logging level to DEBUG.
+ --embeddings (MaggotUBA) Call the backend to generate embeddings instead of labels.
--decode Do not encode the labels into integer indices.
--copy-labels Replicate discrete behavior data from the input file.
--default-label=<label> Label all untagged data as <label>.
@@ -188,6 +190,7 @@ function main(args=ARGS; exit_on_error=true)
data_path = parsed_args["<data-path>"]
data_isolation = parsed_args["--data-isolation"]
output_filename = parsed_args["--output"]
+ embeddings = parsed_args["--embeddings"]
#
datapath = abspath(data_path)
destination = if isfile(datapath)
@@ -216,8 +219,13 @@ function main(args=ARGS; exit_on_error=true)
end
resetdata(tagger)
Taggers.push(tagger, datapath)
- predict(tagger; skip_make_dataset=parsed_args["--skip-make-dataset"],
- make_dataset=parsed_args["--make-dataset"], debug=parsed_args["--debug"])
+ if embeddings
+ embed(tagger; skip_make_dataset=parsed_args["--skip-make-dataset"],
+ make_dataset=parsed_args["--make-dataset"], debug=parsed_args["--debug"])
+ else
+ predict(tagger; skip_make_dataset=parsed_args["--skip-make-dataset"],
+ make_dataset=parsed_args["--make-dataset"], debug=parsed_args["--debug"])
+ end
Taggers.pull(tagger, destination)
end
end