Formatting

batdetect2/evaluate/evaluate.py

@@ -6,7 +6,7 @@ from sklearn.metrics import auc, roc_curve
 from soundevent import data
 from soundevent.evaluation import match_geometries
 
-from batdetect2.train.targets import build_encoder, get_class_names
+from batdetect2.train.targets import build_target_encoder, get_class_names
 
 
 def match_predictions_and_annotations(

batdetect2/modules.py

@@ -29,7 +29,7 @@ from batdetect2.train.losses import compute_loss
 from batdetect2.train.targets import (
     TargetConfig,
     build_decoder,
-    build_encoder,
+    build_target_encoder,
     get_class_names,
 )
 
@@ -78,7 +78,7 @@ class DetectorModel(L.LightningModule):
 
         # Training targets
         self.class_names = get_class_names(self.config.targets.classes)
-        self.encoder = build_encoder(
+        self.encoder = build_target_encoder(
             self.config.targets.classes,
             replacement_rules=self.config.targets.replace,
         )

batdetect2/train/__init__.py

@@ -15,10 +15,19 @@ from batdetect2.train.dataset import (
     LabeledDataset,
     SubclipConfig,
     TrainExample,
+    get_preprocessed_files,
 )
 from batdetect2.train.labels import LabelConfig, load_label_config
-from batdetect2.train.preprocess import preprocess_annotations
-from batdetect2.train.targets import TargetConfig, load_target_config
+from batdetect2.train.preprocess import (
+    generate_train_example,
+    preprocess_annotations,
+)
+from batdetect2.train.targets import (
+    TagInfo,
+    TargetConfig,
+    build_target_encoder,
+    load_target_config,
+)
 from batdetect2.train.train import TrainerConfig, load_trainer_config, train
 
 __all__ = [
@@ -26,12 +35,16 @@ __all__ = [
     "LabelConfig",
     "LabeledDataset",
     "SubclipConfig",
+    "TagInfo",
     "TargetConfig",
     "TrainExample",
     "TrainerConfig",
     "TrainingConfig",
     "add_echo",
     "augment_example",
+    "build_target_encoder",
+    "generate_train_example",
+    "get_preprocessed_files",
     "load_agumentation_config",
     "load_label_config",
     "load_target_config",

batdetect2/train/dataset.py

@@ -101,7 +101,7 @@ class LabeledDataset(Dataset):
         preprocessing: Optional[PreprocessingConfig] = None,
     ):
         return cls(
-            get_files(directory, extension),
+            get_preprocessed_files(directory, extension),
             subclip=subclip,
             augmentation=augmentation,
             preprocessing=preprocessing,
@@ -143,5 +143,7 @@ class LabeledDataset(Dataset):
         return adjust_width(tensor, width)
 
 
-def get_files(directory: PathLike, extension: str = ".nc") -> Sequence[Path]:
+def get_preprocessed_files(
+    directory: PathLike, extension: str = ".nc"
+) -> Sequence[Path]:
     return list(Path(directory).glob(f"*{extension}"))

batdetect2/train/preprocess.py

@@ -20,7 +20,7 @@ from batdetect2.preprocess import (
 from batdetect2.train.labels import LabelConfig, generate_heatmaps
 from batdetect2.train.targets import (
     TargetConfig,
-    build_encoder,
+    build_target_encoder,
     build_sound_event_filter,
     get_class_names,
 )
@@ -76,7 +76,7 @@ def generate_train_example(
         event for event in clip_annotation.sound_events if filter_fn(event)
     ]
 
-    encoder = build_encoder(
+    encoder = build_target_encoder(
         config.target.classes,
         replacement_rules=config.target.replace,
     )

batdetect2/train/targets.py

@@ -12,7 +12,7 @@ from batdetect2.terms import TagInfo, get_tag_from_info
 __all__ = [
     "TargetConfig",
     "load_target_config",
-    "build_encoder",
+    "build_target_encoder",
     "build_decoder",
     "filter_sound_event",
 ]
@@ -91,7 +91,7 @@ def build_replacer(
     return replacer
 
 
-def build_encoder(
+def build_target_encoder(
     classes: List[TagInfo],
     replacement_rules: Optional[List[ReplaceConfig]] = None,
 ) -> Callable[[Iterable[data.Tag]], Optional[str]]: