diff --git a/Manifest.toml b/Manifest.toml
index 990bfdaa0182ec5e16aa3c3334342906352bf80b..e16f846d4be150f861b34a059f113ac47eec7797 100644
--- a/Manifest.toml
+++ b/Manifest.toml
@@ -954,11 +954,11 @@ version = "0.3.2"
[[deps.PlanarLarvae]]
deps = ["DelimitedFiles", "HDF5", "JSON3", "LinearAlgebra", "MAT", "Meshes", "OrderedCollections", "Random", "SHA", "StaticArrays", "Statistics", "StatsBase", "StructTypes"]
-git-tree-sha1 = "a6ced965b03efe596835f093d0ffbf1e8d991d50"
-repo-rev = "v0.14a2"
-repo-url = "https://gitlab.pasteur.fr/nyx/planarlarvae.jl"
+git-tree-sha1 = "6b2dc28d56bcef101672cbf2bb784bbd5d88d579"
+repo-rev = "main"
+repo-url = "https://gitlab.pasteur.fr/nyx/PlanarLarvae.jl"
uuid = "c2615984-ef14-4d40-b148-916c85b43307"
-version = "0.14.0-a"
+version = "0.15.0"
[[deps.PlotUtils]]
deps = ["ColorSchemes", "Colors", "Dates", "PrecompileTools", "Printf", "Random", "Reexport", "Statistics"]
diff --git a/Project.toml b/Project.toml
index 915301c48800ec0d4b2eb09ac64597c25d2215ca..a62f34aff4b9a40aba0ee45f68af67d672472fc2 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
name = "LarvaTagger"
uuid = "8b3b36f1-dfed-446e-8561-ea19fe966a4d"
authors = ["François Laurent", "Institut Pasteur"]
-version = "0.16.4"
+version = "0.17"
[deps]
Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
diff --git a/README.md b/README.md
index 84d9df3189dbda6fc4b491ae840ed01b682a835c..73d662204d9a4e11b62e22ca3e060e5207f27ee0 100644
--- a/README.md
+++ b/README.md
@@ -96,6 +96,13 @@ julia> using LarvaTagger; display(larvaeditor("path/to/data/file"))
To exit the interpreter, type `exit()` or press Ctrl+D.
+### macOS
+
+On macOS computers, the 2D larva view often shows up twice as small as expected. To mitigate this undesired behavior,
+`larvatagger open` admits a `--view-factor` option, and `larvaeditor` admits a `viewfactor` argument.
+This option/argument is 2 per default on macOS, 1 on the other platforms.
+Feel free to adjust the value if the 2D view is too small or large.
+
## Automatic tagging
`LarvaTagger.jl` comes with no automatic tagger per default.
@@ -125,6 +132,8 @@ and apply this tagger to a tracking data file:
scripts/larvatagger predict <path/to/backend> <tagger-name> <path/to/data/file>
```
+Among the many optional arguments to the `train` command, an important one is `--iterations`. It allows specifying the training budget. In several applications, higher training scores were achieved increasing the value for this argument. The default for `MaggotUBA-adapter` tagging backend is 1000. `MaggotUBA-adapter` admits either a single value or a comma-separated pair of values. Indeed, `MaggotUBA-adapter` training is performed in two phases: first the classifier stage is trained, with static weights in the pretrained MaggotUBA encoder; second both the classifier and encoder are fine-tuned. A higher training budget for the second fine-tuning stage may significantly increase the training accuracy.
+
Note: since `TaggingBackends==0.10`, argument `--skip-make-dataset` is default behavior; pass `--make-dataset` instead to enforce the former default.
To run `larvatagger predict` in parallel on multiple data files using the same tagger, append the `--data-isolation` argument to avoid data conflicts.
diff --git a/recipes/Dockerfile b/recipes/Dockerfile
index a8feb6caef384265c5615b8f83897b4133b24440..3c516f31810aef33875d8fe4b079669760bebb02 100644
--- a/recipes/Dockerfile
+++ b/recipes/Dockerfile
@@ -79,7 +79,7 @@ RUN if [ -z $TAGGINGBACKENDS_BRANCH ]; then \
&& rm -rf .git \
&& poetry install --only main \
&& poetry add "pynvml==11.4.1" \
- && if [ "$(echo $BACKEND | cut -d/ -f2)" = "main" ] || [ "$(echo $BACKEND | cut -d/ -f2)" = "dev" ] || [ "$(echo $BACKEND | cut -d/ -f2)" = "debug" ]; then \
+ && if [ "$(echo $BACKEND | cut -d/ -f2)" = "main" ] || [ "$(echo $BACKEND | cut -d/ -f2)" = "dev" ]; then \
julia -e 'using Pkg; Pkg.add("JSON3")' \
&& scripts/make_models.jl default; \
fi \
@@ -88,3 +88,15 @@ RUN if [ -z $TAGGINGBACKENDS_BRANCH ]; then \
COPY recipes/checkgpu /bin/
+
+FROM backend AS confusion
+
+ARG PYTHON_ENV=/app/MaggotUBA
+
+RUN test -d $PYTHON_ENV \
+ && cd $PYTHON_ENV \
+ && poetry add "scikit-learn==1.3.0" \
+ && rm -rf ~/.cache
+
+ADD https://gitlab.pasteur.fr/nyx/TaggingBackends/-/raw/dev/scripts/confusion.py?ref_type=heads&inline=false /bin/confusion.py
+
diff --git a/recipes/README.md b/recipes/README.md
index 99c3b8945187075c7e5a48070add3f6879e6f7ef..79be90e707a866ee1f8d1ebf945bf74ee65c8719 100644
--- a/recipes/README.md
+++ b/recipes/README.md
@@ -171,7 +171,7 @@ docker pull flaur/larvatagger
```
Beware that images that ship with backends are relatively large files (>5GB on disk).
-If you are not interested in automatic tagging, use the `flaur/larvatagger:0.16.2-standalone` image instead.
+If you are not interested in automatic tagging, use the `flaur/larvatagger:0.17-standalone` image instead.
### Upgrading
diff --git a/scripts/larvatagger b/scripts/larvatagger
index 4c7779ab51cb86d2beac1f77e6875cf3c835b8b0..d9a475be6a19e7f2cab8feccfc1feea31bd87bf4 100755
--- a/scripts/larvatagger
+++ b/scripts/larvatagger
@@ -29,36 +29,40 @@ import|merge|train|predict|--version|-V)
LarvaTagger
Usage:
- larvatagger open <file-path> [--backends=<path>] [--port=<number>] [--quiet] [--viewer] [--browser] [--manual-label=<label>] [--segment=<t0,t1>]
+ larvatagger open <file-path> [--backends=<path>] [--port=<number>] [--quiet] [--viewer] [--browser] [--view-factor=<real>] [--manual-label=<label>]
larvatagger import <input-path> [<output-file>] [--id=<id>] [--framerate=<fps>] [--pixelsize=<μm>] [--overrides=<comma-separated-list>] [--default-label=<label>] [--manual-label=<label>] [--decode] [--copy-labels]
- 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>]
- larvatagger train <backend-path> <data-path> <model-instance> --fine-tune=<instance> [--balancing-strategy=<strategy>] [--manual-label=<label>] [--iterations=<N>] [--seed=<seed>]
- larvatagger predict <backend-path> <model-instance> <data-path> [--output=<filename>] [--make-dataset] [--skip-make-dataset] [--data-isolation]
+ 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
Options:
- -h --help Show this screen.
- -V --version Show version.
- -q --quiet Do not show instructions.
- --id=<id> Run or assay ID, e.g. `date_time`.
- --framerate=<fps> Camera frame rate, in frames per second.
- --pixelsize=<μm> Camera pixel size, in micrometers.
- --backends=<path> Path to backend repository.
- --port=<number> Port number the server listens to.
- --viewer Disable editing capabilities.
- --browser Automatically open a browser tab at the served location.
- --make-dataset Perform the make_dataset stage prior to proceeding to predict_model.
- --skip-make-dataset Skip the make_dataset stage (default behavior since TaggingBackends==0.10).
- --data-isolation Isolate the backend data directories for parallel tagging of multiple data files.
- --sample-size=<N> Sample only N track segments from the data repository.
- --layers=<N> (MaggotUBA) Number of layers of the classifier.
- --iterations=<N> (MaggotUBA) Number of training iterations (can be two integers separated by a comma).
- --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.
- --decode Do not encode the labels into integer indices.
- --copy-labels Replicate discrete behavior data from the input file.
+ -h --help Show this screen.
+ -V --version Show version.
+ -q --quiet Do not show instructions.
+ --id=<id> Run or assay ID, e.g. `date_time`.
+ --framerate=<fps> Camera frame rate, in frames per second.
+ --pixelsize=<μm> Camera pixel size, in micrometers.
+ --backends=<path> Path to backend repository.
+ --port=<number> Port number the server listens to.
+ --viewer Disable editing capabilities.
+ --browser Automatically open a browser tab at the served location.
+ --view-factor=<real> Scaling factor for the larva views; default is 2 on macOS, 1 elsewhere.
+ --make-dataset Perform the make_dataset stage prior to proceeding to predict_model.
+ --skip-make-dataset Skip the make_dataset stage (default behavior since TaggingBackends==0.10).
+ --data-isolation Isolate the backend data directories for parallel tagging of multiple data files.
+ --sample-size=<N> Sample only N track segments from the data repository.
+ --layers=<N> (MaggotUBA) Number of layers of the classifier.
+ --iterations=<N> (MaggotUBA) Number of training iterations (can be two integers separated by a comma).
+ --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>.
--manual-label=<label> Secondary label for manually labelled data [default: edited].
--labels=<comma-separated-list> Comma-separated list of behavior tags/labels.
diff --git a/scripts/larvatagger.sh b/scripts/larvatagger.sh
index 885c5dc78adde2425b413ce922d42558a509ad0b..3222537602cecfdee7015b6f0c38f64c21d026b6 100755
--- a/scripts/larvatagger.sh
+++ b/scripts/larvatagger.sh
@@ -2,7 +2,7 @@
for _ in $(seq $#); do
case $1 in
- open|import|merge|train|predict|-V|--version|--more-help|reverse-mapping)
+ open|import|merge|train|predict|-V|--version|--more-help|reverse-mapping|confusion)
cmd=$1
shift
break
@@ -29,6 +29,10 @@ for _ in $(seq $#); do
if [ "$1" = "--no-cache" ]; then
# --no-cache is default for build since 0.16.1
no_cache=1
+ elif [ "$1" = "--target" ]; then
+ DOCKER_ARGS="${DOCKER_ARGS}$1 "
+ shift
+ target=1
fi
# note: if DOCKER_ARGS is externally defined, it must end with an explicit space
DOCKER_ARGS="${DOCKER_ARGS}$1 "
@@ -95,7 +99,9 @@ done
if [ -z "$no_cache" ] && [ -z "$cache" ]; then
DOCKER_ARGS="--no-cache $DOCKER_ARGS"
fi
+if [ -z "$target" ]; then
DOCKER_ARGS="--target $TARGET $DOCKER_ARGS"
+fi
if [ -z "$DOCKERFILE" ]; then
DOCKERFILE=recipes/Dockerfile
fi
@@ -296,6 +302,22 @@ tagger="20230311"
DOCKER_RUN="$docker run $DOCKER_ARGS$RUN_ARGS -it --entrypoint julia \"$LARVATAGGER_IMAGE\" \"/app/$backend/scripts/revert_label_mapping.jl\" \"/data/$output_labels\" \"/data/$unmapped_labels\" \"/data/$edited_labels\" \"/app/$backend/models/$tagger/clf_config.json\""
echo $DOCKER_RUN
eval $DOCKER_RUN
+;;
+
+ confusion)
+
+parentdir=$(cd "$1"; pwd -P)
+shift
+
+RUN_ARGS="$RUN_ARGS -v \"$parentdir\":/data"
+
+# wherever taggingbackends (python) is installed
+backend=MaggotUBA
+
+DOCKER_RUN="$docker run $DOCKER_ARGS$RUN_ARGS -it -w /app/$backend --entrypoint='[\"poetry\", \"run\", \"python\"]' \"$LARVATAGGER_IMAGE\" /bin/confusion.py"
+echo "The confusion.py script is shipped only in images built with argument --target confusion"
+echo $DOCKER_RUN
+eval $DOCKER_RUN
;;
--more-help)
@@ -324,16 +346,37 @@ $docker pull ${DOCKER_ARGS}flaur/larvatagger:latest
*)
cat << EOT
+Wrapper script to operate larvatagger.jl in a Docker image.
+
Usage: $0 build [--stable] [--with-default-backend] [--with-backend <backend>]
$0 open <filepath> [...]
$0 import <filepath> [<outputfilename>] [...]
$0 train <datarepository> <taggername> [--backend <name>] [...]
$0 predict <datafile> [--backend <name>] [--model-instance <taggername>] [...]
+ $0 confusion <datarepository>
$0 merge <filepath> [<outputfilename>] [...]
+ $0 reverse-mapping <filepath> <filename> <outputfilename>
$0 --more-help
$0 --version
$0 --update
-See --more-help for more information about additional options [...] to larvatagger.jl
+
+Note the arguments are very similar to those of larvatagger.jl, except with the train
+command. Indeed, the backend is MaggotUBA-adapter per default, if included in the image.
+
+The build, confusion and reverse-mapping commands are specific to the present script and
+do not interface with larvatagger.jl.
+
+The confusion command crawls the data repository (first argument) in search for
+groundtruth.label and predicted.label files, and generates a confusion.csv file wherever
+both label files are found.
+
+The reverse-mapping command takes two sibling label files, the first one with mapped labels,
+the second one with unmapped labels. It generates a third label file with demapped labels
+from the first file. This is useful when the first file diverges from the second one by some
+manual editions, on top of label mapping.
+
+See --more-help for more information about additional arguments for the other commands from
+larvatagger.jl.
EOT
;;
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 ab9a0341feff42dd394f059febff75c9314090e4..c0a25fbc05090bc4e0ee55eb5c23388c8b7e62d6 100644
--- a/src/cli.jl
+++ b/src/cli.jl
@@ -9,39 +9,47 @@ using .Toolkit
usage = """Larva Tagger.
Usage:
- larvatagger.jl open <file-path> [--backends=<path>] [--port=<number>] [--quiet] [--viewer] [--browser] [--manual-label=<label>]
- larvatagger.jl import <input-path> [<output-file>] [--id=<id>] [--framerate=<fps>] [--pixelsize=<μm>] [--overrides=<comma-separated-list>] [--default-label=<label>] [--manual-label=<label>] [--decode]
- 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>]
- larvatagger.jl predict <backend-path> <model-instance> <data-path> [--output=<filename>] [--make-dataset] [--skip-make-dataset] [--data-isolation]
+ larvatagger.jl open <file-path> [--backends=<path>] [--port=<number>] [--quiet] [--viewer] [--browser] [--view-factor=<real>] [--manual-label=<label>]
+ larvatagger.jl import <input-path> [<output-file>] [--id=<id>] [--framerate=<fps>] [--pixelsize=<μm>] [--overrides=<comma-separated-list>] [--default-label=<label>] [--manual-label=<label>] [--decode] [--copy-labels]
+ 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
Options:
- -h --help Show this screen.
- -V --version Show version.
- -q --quiet Do not show instructions.
- --id=<id> Run or assay ID, e.g. `date_time`.
- --framerate=<fps> Camera frame rate, in frames per second.
- --pixelsize=<μm> Camera pixel size, in micrometers.
- --backends=<path> Path to backend repository.
- --port=<number> Port number the server listens to.
- --viewer Disable editing capabilities.
- --browser Automatically open a browser tab at the served location.
- --make-dataset Perform the make_dataset stage prior to proceeding to predict_model.
- --skip-make-dataset Skip the make_dataset stage (default behavior since TaggingBackends==0.10).
- --data-isolation Isolate the backend data directories for parallel tagging of multiple data files.
- --sample-size=<N> Sample only N track segments from the data repository.
- --layers=<N> (MaggotUBA) Number of layers of the classifier.
- --iterations=<N> (MaggotUBA) Number of training iterations (can be two integers separated by a comma).
- --seed=<seed> Seed for the backend's random number generators.
- --decode Do not encode the labels into integer indices.
+ -h --help Show this screen.
+ -V --version Show version.
+ -q --quiet Do not show instructions.
+ --id=<id> Run or assay ID, e.g. `date_time`.
+ --framerate=<fps> Camera frame rate, in frames per second.
+ --pixelsize=<μm> Camera pixel size, in micrometers.
+ --backends=<path> Path to backend repository.
+ --port=<number> Port number the server listens to.
+ --viewer Disable editing capabilities.
+ --browser Automatically open a browser tab at the served location.
+ --view-factor=<real> Scaling factor for the larva views; default is 2 on macOS, 1 elsewhere.
+ --make-dataset Perform the make_dataset stage prior to proceeding to predict_model.
+ --skip-make-dataset Skip the make_dataset stage (default behavior since TaggingBackends==0.10).
+ --data-isolation Isolate the backend data directories for parallel tagging of multiple data files.
+ --sample-size=<N> Sample only N track segments from the data repository.
+ --layers=<N> (MaggotUBA) Number of layers of the classifier.
+ --iterations=<N> (MaggotUBA) Number of training iterations (can be two integers separated by a comma).
+ --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>.
--manual-label=<label> Secondary label for manually labelled data [default: edited].
--labels=<comma-separated-list> Comma-separated list of behavior tags/labels.
--class-weights=<csv> Comma-separated list of floats.
--pretrained-model=<instance> Name of the pretrained encoder (from `pretrained_models` registry).
--balancing-strategy=<strategy> Any of `auto`, `maggotuba`, `none` [default: auto].
+ --fine-tune=<instance> Load and fine-tune an already trained model.
--overrides=<comma-separated-list> Comma-separated list of key:value pairs.
-o <filename> --output=<filename> Predicted labels filename.
diff --git a/src/cli_open.jl b/src/cli_open.jl
index 023b432a6a9c20d9bfb4657c44b6cabcf268ee97..d62d3740648b993fe875adc55966d5bc49f32709 100644
--- a/src/cli_open.jl
+++ b/src/cli_open.jl
@@ -9,7 +9,7 @@ export main
usage = """LarvaTagger.jl - launch the server-based GUI.
Usage:
- larvatagger-gui.jl <file-path> [--backends=<path>] [--port=<number>] [--quiet] [--viewer] [--browser] [--manual-label=<label>]
+ larvatagger-gui.jl <file-path> [--backends=<path>] [--port=<number>] [--quiet] [--viewer] [--browser] [--view-factor=<real>] [--manual-label=<label>]
larvatagger-gui.jl -h | --help
Options:
@@ -19,6 +19,7 @@ Options:
--port=<number> Port number the server listens to.
--viewer Disable editing capabilities.
--browser Automatically open a browser tab at the served location.
+ --view-factor=<real> Scaling factor for the larva views; default is 2 on macOS, 1 elsewhere.
--manual-label=<label> Secondary label for manually labelled data [default: edited].
Backends defined in LarvaTagger project root directory are automatically found. Other
@@ -50,10 +51,18 @@ function main(args=ARGS; exit_on_error=false)
@error "File not found; did you specify a file path?" infile
exit()
end
+
+ kwargs = Dict{Symbol, Any}()
+ viewfactor = parsed_args["--view-factor"]
+ if !isnothing(viewfactor)
+ kwargs[:viewfactor] = parse(Float64, viewfactor)
+ elseif Sys.isapple()
+ kwargs[:viewfactor] = 2
+ end
+
if parsed_args["--viewer"]
- app = larvaviewer(infile)
+ app = larvaviewer(infile; kwargs...)
else
- kwargs = Dict{Symbol, Any}()
backends = parsed_args["--backends"]
if !isnothing(backends)
kwargs[:backend_directory] = backends
diff --git a/src/cli_toolkit.jl b/src/cli_toolkit.jl
index 82a00be34159ba3519c59d0131a40f663ff5c5b0..5614735f43da6693ad420b0a416c32c74792c9b3 100644
--- a/src/cli_toolkit.jl
+++ b/src/cli_toolkit.jl
@@ -16,9 +16,10 @@ usage = """Larva Tagger.
Usage:
larvatagger-toolkit.jl import <input-path> [<output-file>] [--id=<id>] [--framerate=<fps>] [--pixelsize=<μm>] [--overrides=<comma-separated-list>] [--default-label=<label>] [--manual-label=<label>] [--decode] [--copy-labels] [--segment=<t0,t1>]
- 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>]
- larvatagger-toolkit.jl train <backend-path> <data-path> <model-instance> --fine-tune=<instance> [--balancing-strategy=<strategy>] [--manual-label=<label>] [--iterations=<N>] [--seed=<seed>]
- larvatagger-toolkit.jl predict <backend-path> <model-instance> <data-path> [--output=<filename>] [--make-dataset] [--skip-make-dataset] [--data-isolation]
+ 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
@@ -37,6 +38,8 @@ Options:
--iterations=<N> Number of training iterations (integer or comma-separated list of integers).
--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>.
@@ -161,6 +164,8 @@ function main(args=ARGS; exit_on_error=true)
isnothing(iterations) || (kwargs[:iterations] = iterations)
seed = parsed_args["--seed"]
isnothing(seed) || (kwargs[:seed] = seed)
+ debug = parsed_args["--debug"]
+ isnothing(debug) || (kwargs[:debug] = debug)
#
finetune_model = parsed_args["--fine-tune"]
if isnothing(finetune_model) # standard train
@@ -185,6 +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)
@@ -213,8 +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"])
+ 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
diff --git a/src/editor.jl b/src/editor.jl
index 07e96b2c76233577df9e2c6e260d88d670d0116b..61c33882a40150683a38145aa3c2ab10f7f9e8c2 100644
--- a/src/editor.jl
+++ b/src/editor.jl
@@ -32,7 +32,8 @@ projectdir = dirname(Base.active_project())
function larvaeditor(path=nothing;
allow_multiple_tags::Union{Nothing, Bool}=nothing,
backend_directory::AbstractString=projectdir,
- manualtag::Union{Nothing, String, Symbol}="edited")
+ manualtag::Union{Nothing, String, Symbol}="edited",
+ kwargs...)
# to (re-)load a file, the app is reloaded with the filepath as sole information
# from previous session
@@ -48,7 +49,8 @@ function larvaeditor(path=nothing;
editor = EditorView(larvaviewer(controller;
editabletags=true,
- multipletags=allow_multiple_tags),
+ multipletags=allow_multiple_tags,
+ kwargs...),
larvafilter(controller),
tagfilter(controller; manualtag=manualtag),
metadataeditor(controller),
diff --git a/src/files.jl b/src/files.jl
index bde0c9c763a295ed54564ac2790c1143c96661da..ac616586b19d9fde077cc3b1eb3ae5568ae7933f 100644
--- a/src/files.jl
+++ b/src/files.jl
@@ -206,6 +206,10 @@ function loadfile(path)
if file isa Formats.FIMTrack
times = PlanarLarvae.times(data)
tracks = [LarvaModel(track, times) for track in values(getrun(file))]
+ elseif file isa Formats.MaggotUBA
+ times = PlanarLarvae.times(data)
+ tracks = Formats.astimeseries(getrun(file); labels2tags=true)
+ tracks = [LarvaModel(id, ts, times) for (id, ts) in tracks]
else
times = PlanarLarvae.times(gettimeseries(file))
tracks = [LarvaModel(id, ts, times) for (id, ts) in pairs(gettimeseries(file))]
@@ -409,7 +413,7 @@ function explicit_editions_needed(controller, editiontag)
if file isa Formats.JSONLabels
Formats.load!(file)
return haskey(file.run.attributes, :labels)
- elseif file isa Formats.Trxmat
+ elseif file isa Formats.Trxmat || file isa MaggotUBA
return true
else
return false
diff --git a/src/models.jl b/src/models.jl
index 965fd4e325f7517e0dff96adebba3a0e6c8855fb..2c537415dc328090bbf2133ac7e5b982be09c88c 100644
--- a/src/models.jl
+++ b/src/models.jl
@@ -109,9 +109,9 @@ end
function getusertags(larva, timestep; lut=nothing)
usertags = larva.usertags[]
tags = UserTags()
- try
+ if haskey(usertags, timestep)
tags = usertags[timestep]
- catch
+ else
firststep = larva.alignedsteps[1]
firststep <= timestep || return tags
relstep = timestep - firststep + 1
@@ -250,7 +250,6 @@ function LarvaModel(track::Track, times::Vector{PlanarLarvae.Time})
missingsteps = ones(Bool, steps[end])
missingsteps[steps] .= false
missingsteps = findall(missingsteps)
- # this method may be dead code; the warning below has never been emitted
isempty(missingsteps) || @warn "Time steps are missing" id=convert(Int, track.id) missingsteps
path = coordinates.(larvatrack(track[:spine]))
usertags = Observable(Dict{TimeStep, UserTags}())
@@ -262,7 +261,28 @@ function LarvaModel(track::Track, times::Vector{PlanarLarvae.Time})
usertags)
end
-Meshes.boundingbox(larva::LarvaModel) = Meshes.boundingbox([outline(state) for (_,state) in larva.fullstates])
+"""
+ outline_or_spine(state)
+ outline_or_spine(pointtype, state)
+
+Return outline data if available, spine data otherwise.
+"""
+function outline_or_spine(state)
+ if haskey(state, :outline)
+ outline(state)
+ else
+ spine(state)
+ end
+end
+function outline_or_spine(T, state)
+ if haskey(state, :outline)
+ outline(T, state)
+ else
+ spine(T, state)
+ end
+end
+
+Meshes.boundingbox(larva::LarvaModel) = Meshes.boundingbox([outline_or_spine(state) for (_,state) in larva.fullstates])
Meshes.boundingbox(larvae::Vector{LarvaModel}) = Meshes.boundingbox(map(Meshes.boundingbox, larvae))
function downsampler(; step::Int=20)
diff --git a/src/players.jl b/src/players.jl
index f805cf91b922e61d7bd765e922ab158bfcfc035b..ff1f5fd5ae8ed5fa98a213c2aee584ace3fc1903 100644
--- a/src/players.jl
+++ b/src/players.jl
@@ -158,6 +158,7 @@ function timecontroller(times::Vector{Float64}; speed=1.0)
stepmin = Observable(1)
stepmax = Observable(nsteps)
boundreached = Observable(true)
+ initialized = Ref(false) # useful for skipping a "Time bound reached" message at startup
#
on(timestep) do step
min, max = stepmin[], stepmax[]
@@ -177,7 +178,8 @@ function timecontroller(times::Vector{Float64}; speed=1.0)
end
end
on(boundreached) do b
- b && @info "Time bound reached"
+ b && initialized[] && @info "Time bound reached"
+ initialized[] = true
end
on(stepmin) do bound
0 < bound || throw(DomainError("stepmin < 1"))
diff --git a/src/plots.jl b/src/plots.jl
index c5b21a867310f223a32dd1829202ae6012cfda38..0364c82020fdb99104df2c9c5f37025810f5b481 100644
--- a/src/plots.jl
+++ b/src/plots.jl
@@ -13,7 +13,7 @@ end
#
-const CompatLarvaID = Int16
+const CompatLarvaID = Int32
const ActiveLarva = Union{Nothing, CompatLarvaID}
function withalpha(outline_color, alpha_value)
@@ -82,7 +82,7 @@ function StatefulLarva(larva::LarvaModel,
_, color = gettag(tag_lut, larva, larva.alignedsteps[1], fallback_color)
# key observables
- shape_outline = Observable(outline(Makie.Point2f, state))
+ shape_outline = Observable(outline_or_spine(Makie.Point2f, state))
shape_color = Observable(html_color(color))
visibility = Observable(false)
@@ -96,7 +96,7 @@ function StatefulLarva(larva::LarvaModel,
end
step -= count(larva.missingsteps .< step)
_, state = timeseries[step]
- shape_outline.val = outline(Makie.Point2f, state)
+ shape_outline.val = outline_or_spine(Makie.Point2f, state)
#
_, color = gettag(tag_lut, larva, timestep, fallback_color)
shape_color.val = html_color(color)
@@ -148,7 +148,7 @@ function SingleLarvaView(larvae::Vector{LarvaModel}, controller; editabletags::B
visible = Observable(false)
path = Observable(larva.path)
pathtree = map(KDTree, path)
- shape_outline = Observable(outline(Makie.Point2f, state))
+ shape_outline = Observable(outline_or_spine(Makie.Point2f, state))
shape_color = Observable(html_color(color))
# TODO: move the callbacks to `plot!`
@@ -201,7 +201,7 @@ function SingleLarvaView(larvae::Vector{LarvaModel}, controller; editabletags::B
)
step -= count(larva.missingsteps .< step)
_, state = larva.fullstates[step]
- shape_outline.val = outline(Makie.Point2f, state)
+ shape_outline.val = outline_or_spine(Makie.Point2f, state)
#
_, color = gettag(tag_lut, larva, timestep, fallback_color)
shape_color.val = html_color(color)
@@ -593,7 +593,7 @@ function DecoratedLarvae(larvae::Vector{DecoratedLarva})
else
@error begin
j_id = larvae[j].larva.model.id
- "cannot decorate invisible larva #$(j_id) - please file an issue at https://gitlab.pasteur.fr/nyx/larvatagger.jl/-/issues"
+ "Cannot decorate invisible larva #$(j_id)"
end
hovered_larva.val = 0
end
diff --git a/src/viewer.jl b/src/viewer.jl
index 6ea1a4c93e0779f2d77fc86d298de3e60cec76c2..7463492dd4eef02ba03de68d9bd57efd5c12df6a 100644
--- a/src/viewer.jl
+++ b/src/viewer.jl
@@ -42,7 +42,8 @@ function JSServe.jsrender(session::Session, vv::ViewerView)
DOM.div(JSServe.TailwindCSS, assaydom, trackdom; class="flex flex-row"))
end
-function larvaviewer(path::String; allow_multiple_tags::Union{Nothing, Bool}=false)
+function larvaviewer(path::String; allow_multiple_tags::Union{Nothing, Bool}=false,
+ kwargs...)
App() do session::Session
@@ -50,7 +51,7 @@ function larvaviewer(path::String; allow_multiple_tags::Union{Nothing, Bool}=fal
tryopenfile(controller, path)
- viewer = larvaviewer(controller; multipletags=allow_multiple_tags)
+ viewer = larvaviewer(controller; multipletags=allow_multiple_tags, kwargs...)
r(session, LarvaTaggerJS)
r(session, LarvaTaggerCSS)
@@ -62,6 +63,7 @@ end
function larvaviewer(controller;
editabletags::Bool=false,
multipletags::Union{Nothing, Bool}=false,
+ viewfactor::Real=1,
)
model = getlarvae(controller)
times = gettimes(controller)
@@ -85,10 +87,19 @@ function larvaviewer(controller;
@info isnothing(id) ? "No active larva" : "Activating larva #$(id)"
end
- viewer = ViewerView(assayviewer(delayed_controller),
+ kwargs = Dict{Symbol, Any}()
+ if viewfactor != 1
+ width, height = FIGSIZE
+ width = round(Int, width * viewfactor)
+ height = round(Int, height * viewfactor)
+ kwargs[:size] = (width, height)
+ end
+
+ viewer = ViewerView(assayviewer(delayed_controller; kwargs...),
trackviewer(controller;
editabletags=editabletags,
- multipletags=multipletags))
+ multipletags=multipletags,
+ kwargs...))
settimestep!(controller, 1)
diff --git a/src/wgl.jl b/src/wgl.jl
index c9cad2c70a4623d433ca57ff2afb8b4ac616f8d9..164fe6792251376c606e2a5ef7e82479807772a3 100644
--- a/src/wgl.jl
+++ b/src/wgl.jl
@@ -118,6 +118,7 @@ struct AssayPlot
end
function AssayPlot(ctrl, larvae::DecoratedLarvae; size=FIGSIZE)
+ gethub(ctrl)[:decoratedlarvae] = larvae
fig = Figure(resolution=size)
width = 0.1f0 # try to get 1px
color = RGBAf(0, 0, 0, 0.36)
@@ -421,10 +422,10 @@ mutable struct AssayViewer
dom
end
-function assayviewer(controller)
+function assayviewer(controller; kwargs...)
model = getlarvae(controller)
visible = Observable(true)
- plot = assayplot(model, controller, visible)
+ plot = assayplot(model, controller, visible; kwargs...)
play = player(controller)
on(visible) do b
if b
@@ -448,14 +449,50 @@ end
struct LarvaInfo
controller
id::LarvaID
+ hovered::AbstractObservable{Bool}
+ clicked::AbstractObservable{Bool}
reviewed::AbstractObservable{Bool}
edited::AbstractObservable{Bool}
included::AbstractObservable{Bool}
end
function larvainfo(controller, id)
+ hovered = Observable(false)
+ clicked = Observable(false)
reviewed = Observable(false)
edited = Observable(false)
+ #
+ larvae = gethub(controller)[:decoratedlarvae]
+ larvaindex = nothing
+ for (i, larva) in enumerate(larvae.larvae)
+ larva = larva.larva
+ if larva.model.id == id
+ larvaindex = i
+ end
+ end
+ larvavisible = larvae.larvae[larvaindex].larva.visible
+ on(hovered) do b
+ if larvae.hovering_active[]
+ if b
+ if larvavisible[]
+ larvae.hovered_larva[] = larvaindex
+ end
+ else
+ i = larvae.hovered_larva[]
+ if i != 0
+ # TODO: additionally condition the below warning on the type of larva
+ # view (in AssayPlot, warn; in TrackPlot, do not warn)
+ #i == larvaindex || @warn "Larva #$(larvae.larvae[i].larva.model.id) unexpectedly decorated"
+ larvae.hovered_larva[] = 0
+ end
+ end
+ end
+ end
+ on(clicked) do b
+ @assert b
+ activatelarva!(controller, id)
+ clicked.val = false
+ end
on(edited) do b
if b
#@assert reviewed[]
@@ -474,6 +511,8 @@ function larvainfo(controller, id)
included = Observable(false)
LarvaInfo(controller,
id,
+ hovered,
+ clicked,
reviewed,
edited,
included)
@@ -482,7 +521,10 @@ end
JSServe.jsrender(session::Session, li::LarvaInfo) = r(session, prerender(li))
function prerender(li::LarvaInfo)
- label = "#$(li.id)"
+ label = DOM.label("#$(li.id)",
+ onmouseenter=js"JSServe.update_obs($(li.hovered), true)",
+ onmouseleave=js"JSServe.update_obs($(li.hovered), false)",
+ onmouseup=js"JSServe.update_obs($(li.clicked), true)")
discard_larva_edits = js"LarvaTagger.discardLarvaEdits(this, $(li.edited), $label)"
reviewed_checkbox = DOM.input(type="checkbox",
checked=li.reviewed,
@@ -501,8 +543,7 @@ function prerender(li::LarvaInfo)
DOM.tr(DOM.td(label),
DOM.td(reviewed_checkbox, style="text-align: center;"),
DOM.td(edited_checkbox, style="text-align: center;"),
- DOM.td(included_checkbox, style="text-align: center;"),
- )
+ DOM.td(included_checkbox, style="text-align: center;"))
end
struct LarvaFilter
@@ -990,9 +1031,10 @@ end
function trackviewer(controller;
editabletags::Bool=true,
multipletags::Union{Nothing, Bool}=nothing,
+ kwargs...
)
model = getlarvae(controller)
- plot = trackplot(model, controller; editabletags=editabletags)
+ plot = trackplot(model, controller; editabletags=editabletags, kwargs...)
play = player(controller)
sele = tagselector(controller; editabletags=editabletags, multipletags=multipletags)
TrackViewer(plot, play, sele, nothing)
diff --git a/test/deploy_and_test.sh b/test/deploy_and_test.sh
index 71e3406660068220d960b8a8175a82e5cb94a681..4d3ca51c7c3f1c59d122a296b6a3df53a4ea53f6 100755
--- a/test/deploy_and_test.sh
+++ b/test/deploy_and_test.sh
@@ -103,7 +103,7 @@ if [ -f ../../LarvaTagger_test_data.tgz ]; then
tar zxvf ../../LarvaTagger_test_data.tgz
else
# Not recommended; reproducibility is not guarantee across hosts or architectures yet
- wget -O- https://dl.pasteur.fr/fop/l3qruSQR/LarvaTagger_test_data.tgz | tar zxv
+ wget -O- https://dl.pasteur.fr/fop/8MvgygD4/LarvaTagger_test_data.tgz | tar zxv
fi
if [ "$LOCAL_SCENARII" = "1" ]; then
diff --git a/test/scenarii.sh b/test/scenarii.sh
index 59a96d49a14ad72fc414f258b986496c9cd975a9..cfe2784ad504372ec4396e644b400137203a0839 100755
--- a/test/scenarii.sh
+++ b/test/scenarii.sh
@@ -44,6 +44,10 @@ maggotuba="../MaggotUBA"
seed=1028347112001
+endTest() {
+ echo "----------------------------------------------------------------------------"
+}
+
prepareTestData() {
tmpdir="$SHUNIT_TMPDIR/$1"
rm -rf "$tmpdir"
@@ -79,6 +83,7 @@ testImportLabelFile() {
assertTrue '\`import\` failed to reproduce the imported.label file' '$(cmp "$datapath/imported.label" "$datapath/$filename")'
# clean up
rm -f "$datapath/$filename"
+ endTest
}
# requires: cropped.label
@@ -92,6 +97,7 @@ testCropTracks() {
assertTrue '\`import\` failed to reproduce the cropped.label file' '$(cmp "$datapath/cropped.label" "$datapath/$filename")'
# clean up
rm -f "$datapath/$filename"
+ endTest
}
# requires: sample.spine sample.outline test_train_default/predicted.label
@@ -106,14 +112,15 @@ testPredictDefault() {
[ -f "$maggotuba/models/$tagger/clf_config.json" ] || exit 1
# run
cd "$project_root"
- echo "\"$larvataggerjl\" predict \"$maggotuba\" $tagger \"$tmpdir/sample.spine\""
- "$larvataggerjl" predict "$maggotuba" $tagger "$tmpdir/sample.spine"
+ echo "\"$larvataggerjl\" predict \"$maggotuba\" $tagger \"$tmpdir/sample.spine\" --debug"
+ "$larvataggerjl" predict "$maggotuba" $tagger "$tmpdir/sample.spine" --debug
# compare
filename=predicted.label
predictions="$tmpdir/$filename"
expected_labels="$datapath/$tagger/$filename"
assertFalse "\`predict\` failed to generate file $filename" '[ -z "$predictions" ]'
assertTrue "\`predict\` failed to reproduce file $filename" '$(cmp "$expected_labels" "$predictions")'
+ endTest
}
# requires: sample.spine sample.outline original_predictions.label test_train_default/*
@@ -122,10 +129,11 @@ testTrainDefault() {
tmpdir=$(prepareTrainingData original_predictions.label $tagger)
# run
cd "$project_root"
- echo "\"$larvataggerjl\" train \"$maggotuba\" \"$tmpdir\" $tagger --seed $seed"
- "$larvataggerjl" train "$maggotuba" "$tmpdir" $tagger --seed $seed
+ echo "\"$larvataggerjl\" train \"$maggotuba\" \"$tmpdir\" $tagger --seed $seed --debug"
+ "$larvataggerjl" train "$maggotuba" "$tmpdir" $tagger --seed $seed --debug
# test
postTrain $tagger
+ endTest
}
# requires: sample.spine sample.outline imported.label test_train_one_class/*
@@ -138,6 +146,7 @@ testTrainOneClass() {
"$larvataggerjl" train "$maggotuba" "$tmpdir" $tagger --iterations 10 --seed $seed --labels="back-up,not back-up"
# test
postTrain $tagger
+ endTest
}
# requires: sample.spine sample.outline imported.label test_train_one_class_with_weights/*
@@ -150,6 +159,7 @@ testTrainOneClassWithWeights() {
"$larvataggerjl" train "$maggotuba" "$tmpdir" $tagger --iterations 10 --seed $seed --labels="not back-up,back-up" --class-weights 1,10
# test
postTrain $tagger
+ endTest
}
# requires: sample.spine sample.outline gui_imported.label test_train_one_class_with_encoder/*
@@ -162,6 +172,7 @@ testTrainOneClassWithEncoder() {
"$larvataggerjl" train "$maggotuba" "$tmpdir" $tagger --iterations 10 --seed $seed --labels="hunch,¬hunch" --pretrained-model=20230524-hunch-25 --balancing-strategy=maggotuba
# test
postTrain $tagger
+ endTest
}
# requires: sample.spine sample.outline trx.mat gui_imported.label original_predictions.label test_train_selected_files/*
@@ -178,6 +189,7 @@ testTrainSelectedFiles() {
# test
cd "$project_root"
postTrain $tagger
+ endTest
}
# requires: sample.spine sample.outline trx.mat gui_imported.label original_predictions.label test_train_recursive_selection/*
@@ -191,6 +203,7 @@ testTrainRecursiveSelection() {
"$larvataggerjl" train "$maggotuba" "$tmpdir/**/gui_imported.label" $tagger --seed $seed --labels="run_large,cast_large,hunch_large" --balancing-strategy=maggotuba --iterations=10
# test
postTrain $tagger
+ endTest
}
postTrain() {