diff --git a/Project.toml b/Project.toml
index a9a1942dc3ed35be76e2d25c9ce017a876c2be4f..4f052cf5204ae8709c638e5f1e5b4146a325a99f 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
name = "TaggingBackends"
uuid = "e551f703-3b82-4335-b341-d497b48d519b"
authors = ["François Laurent", "Institut Pasteur"]
-version = "0.11.1"
+version = "0.12"
[deps]
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
diff --git a/pyproject.toml b/pyproject.toml
index 734c7134be041b1a4874b5f72677545a33af109a..bcd821c30c78d91f3a70d0b9b279d92bef2c9645 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[tool.poetry]
name = "TaggingBackends"
-version = "0.11.1"
+version = "0.12.0"
description = "Backbone for LarvaTagger.jl tagging backends"
authors = ["François Laurent"]
diff --git a/src/taggingbackends/data/labels.py b/src/taggingbackends/data/labels.py
index e2b93ad59c98dc9e2e86584be438592b5bcf8bb7..a962b57bf18fae3ece4da2ab3ea82197daca793f 100644
--- a/src/taggingbackends/data/labels.py
+++ b/src/taggingbackends/data/labels.py
@@ -66,7 +66,9 @@ because label colors are also stored in the `labelspec` attribute.
With taggingbackends==0.9, a related attribute was introduced:
`secondarylabelspec`. To get a unique array of indexable labels, both primary
-and secondary labels in a same array, use `full_label_list` instead.
+and secondary labels in a same array, use either `encoding_label_list` or
+`decoding_label_list` instead. The two properties typically equal, unless
+attribute `decodingspec` is defined.
"""
class Labels:
@@ -84,6 +86,7 @@ class Labels:
self.secondarylabelspec = None
self._tracking = tracking
self._input_labels = None
+ self.decodingspec = None
#
self.filepath = None # unused attribute; may help to manage data
# dependencies in the future
@@ -177,8 +180,10 @@ class Labels:
elif len(key) == 3:
run, larva, timestamp = key
self.set_timestep(run, larva, timestamp, value)
+ elif len(key) < 1:
+ raise IndexError("too few dimensions")
else:
- raise IndexError("too few of many dimensions")
+ raise IndexError("too many dimensions")
else:
run = key
self.set_run(run, value)
@@ -264,6 +269,7 @@ class Labels:
self.labels, self.metadata = new_self.labels, new_self.metadata
self.labelspec, self.units = new_self.labelspec, new_self.units
self.secondarylabelspec = new_self.secondarylabelspec
+ # no `decodingspec` in label files
self.tracking = new_self.tracking
return self
@@ -306,6 +312,7 @@ class Labels:
self.units = data.get("units", {})
self.labelspec = data.get("labels", {})
self.secondarylabelspec = data.get("secondarylabels", [])
+ self.decodingspec = None # ensure it is not set
self._tracking = data.get("dependencies", [])
if isinstance(self._tracking, dict):
self._tracking = [self._tracking]
@@ -322,7 +329,7 @@ class Labels:
List of str: all different labels including primary and secondary labels.
"""
@property
- def full_label_list(self):
+ def encoding_label_list(self):
if isinstance(self.labelspec, dict):
labelset = self.labelspec['names']
else:
@@ -331,6 +338,18 @@ class Labels:
labelset = labelset + self.secondarylabelspec
return labelset
+ """
+ List of str: all different labels including primary and secondary labels.
+ """
+ @property
+ def decoding_label_list(self):
+ labelspec = self.decodingspec
+ if labelspec is None:
+ return self.encoding_label_list
+ if self.secondarylabelspec:
+ labelset = labelset + self.secondarylabelspec
+ return labelset
+
"""
Encode the text labels as indices (`int` or `list` of `int`).
@@ -345,7 +364,7 @@ class Labels:
elif isinstance(label, dict):
encoded = {t: self.encode(l) for t, l in label.items()}
else:
- labelset = self.full_label_list
+ labelset = self.encoding_label_list
if isinstance(label, str):
encoded = labelset.index(label) + 1
elif isinstance(label, int):
@@ -358,7 +377,25 @@ class Labels:
"""
Decode the label indices as text (`str` or `list` of `str`).
- Text labels are picked in `labelspec`.
+ Text labels are picked in `labelspec`, or `decodingspec` instead if defined.
+
+ `decodingspec` is set to decode the encoded output from a tagger that
+ defines redundant labels, which are remapped onto labels in `labelspec`.
+ These may include several sections in their config file, including
+ `original_behavior_labels`, `behavior_labels`, `remapped_behavior_labels`.
+
+ Note that `decodingspec` should not be set to decode a label file. A label
+ file should use and mention the remapped labels only, if the latter are
+ defined by the tagger used to generate the label file. In the case of
+ decoding a label file, `labelspec` only should be defined in the `Labels`
+ object.
+
+ To forget about these considerations, call `load_model_config` first if
+ processing the output of a tagger, or do not call that method otherwise.
+
+ MaggotUBA's `predict_model` does not call `decode` but directly indexes into
+ `behavior_labels`. As a consequence, the above subtleties do not apply to
+ MaggotUBA.
"""
def decode(self, label=None):
if label is None:
@@ -368,7 +405,7 @@ class Labels:
elif isinstance(label, dict):
decoded = {t: self.decode(l) for t, l in label.items()}
else:
- labelset = self.full_label_list
+ labelset = self.decoding_label_list
if isinstance(label, int):
decoded = labelset[label-1]
elif isinstance(label, str):
@@ -378,6 +415,14 @@ class Labels:
decoded = [labelset[l-1] for l in label]
return decoded
+ def load_model_config(self, config):
+ try:
+ self.labelspec = config["remapped_behavior_labels"]
+ except KeyError:
+ self.labelspec = config["behavior_labels"]
+ else:
+ self.decodingspec = config["behavior_labels"]
+
class LabelEncoder(json.JSONEncoder):
def default(self, labels):
if isinstance(labels, Labels):
diff --git a/src/taggingbackends/main.py b/src/taggingbackends/main.py
index dde5335e0a03a7620aa8a334c59bc9fb800bc636..f530b149389f3eaba15cca571a46603acb349eed 100644
--- a/src/taggingbackends/main.py
+++ b/src/taggingbackends/main.py
@@ -14,6 +14,7 @@ Usage: tagging-backend [train|predict] --model-instance <name>
tagging-backend train ... --skip-make-dataset --skip-build-features
tagging-backend predict ... --make-dataset --build-features
tagging-backend predict ... --sandbox <token>
+ tagging-backend --help
`tagging-backend` typically is run using `poetry run`.
A name must be provided to identify the trained model and its location within
@@ -83,9 +84,9 @@ def main(fun=None):
format="%(levelname)s:%(name)s: %(message)s")
if fun is None:
# called by scripts/tagging-backend
- if not sys.argv[1:]:
+ if not sys.argv[1:] or any(arg == '--help' for arg in sys.argv):
help(True)
- sys.exit("too few input arguments; subcommand expected: 'train' or 'predict'")
+ #sys.exit("too few input arguments; subcommand expected: 'train' or 'predict'")
return
train_or_predict = sys.argv[1]
project_dir = model_instance = None