Add ignore at ends when evaluating

src/batdetect2/data/annotations/legacy.py

@@ -89,18 +89,9 @@ def annotation_to_sound_event(
         uuid=uuid.uuid5(NAMESPACE, f"{sound_event.uuid}_annotation"),
         sound_event=sound_event,
         tags=[
-            data.Tag(
-                key=label_key,  # type: ignore
-                value=annotation.label,
-            ),
-            data.Tag(
-                key=event_key,  # type: ignore
-                value=annotation.event,
-            ),
-            data.Tag(
-                key=individual_key,  # type: ignore
-                value=str(annotation.individual),
-            ),
+            data.Tag(key=label_key, value=annotation.label),
+            data.Tag(key=event_key, value=annotation.event),
+            data.Tag(key=individual_key, value=str(annotation.individual)),
         ],
     )
 
@@ -121,12 +112,7 @@ def file_annotation_to_clip(
     recording = data.Recording.from_file(
         full_path,
         time_expansion=file_annotation.time_exp,
-        tags=[
-            data.Tag(
-                key=label_key,  # type: ignore
-                value=file_annotation.label,
-            )
-        ],
+        tags=[data.Tag(key=label_key, value=file_annotation.label)],
     )
 
     return data.Clip(
@@ -153,12 +139,7 @@ def file_annotation_to_clip_annotation(
         uuid=uuid.uuid5(NAMESPACE, f"{file_annotation.id}_clip_annotation"),
         clip=clip,
         notes=notes,
-        tags=[
-            data.Tag(
-                key=label_key,  # type: ignore
-                value=file_annotation.label,
-            )
-        ],
+        tags=[data.Tag(key=label_key, value=file_annotation.label)],
         sound_events=[
             annotation_to_sound_event(
                 annotation,

src/batdetect2/evaluate/match.py

@@ -57,6 +57,7 @@ class MatchConfig(BaseConfig):
     affinity_threshold: float = 0.0
     time_buffer: float = 0.005
     frequency_buffer: float = 1_000
+    ignore_start_end: float = 0.01
 
 
 def _to_bbox(geometry: data.Geometry) -> data.BoundingBox:
@@ -273,6 +274,17 @@ def greedy_match(
         yield None, target_idx, 0
 
 
+def _is_in_bounds(
+    geometry: data.Geometry,
+    clip: data.Clip,
+    buffer: float,
+) -> bool:
+    start_time = compute_bounds(geometry)[0]
+    return (start_time >= clip.start_time + buffer) and (
+        start_time <= clip.end_time - buffer
+    )
+
+
 def match_sound_events_and_raw_predictions(
     clip_annotation: data.ClipAnnotation,
     raw_predictions: List[RawPrediction],
@@ -286,14 +298,29 @@ def match_sound_events_and_raw_predictions(
         for sound_event_annotation in clip_annotation.sound_events
         if targets.filter(sound_event_annotation)
         and sound_event_annotation.sound_event.geometry is not None
+        and _is_in_bounds(
+            sound_event_annotation.sound_event.geometry,
+            clip=clip_annotation.clip,
+            buffer=config.ignore_start_end,
+        )
     ]
 
-    target_geometries: List[data.Geometry] = [  # type: ignore
+    target_geometries: List[data.Geometry] = [
         sound_event_annotation.sound_event.geometry
         for sound_event_annotation in target_sound_events
         if sound_event_annotation.sound_event.geometry is not None
     ]
 
+    raw_predictions = [
+        raw_prediction
+        for raw_prediction in raw_predictions
+        if _is_in_bounds(
+            raw_prediction.geometry,
+            clip=clip_annotation.clip,
+            buffer=config.ignore_start_end,
+        )
+    ]
+
     predicted_geometries = [
         raw_prediction.geometry for raw_prediction in raw_predictions
     ]

src/batdetect2/plotting/common.py

@@ -32,9 +32,12 @@ def plot_spectrogram(
     max_freq: Optional[float] = None,
     ax: Optional[axes.Axes] = None,
     figsize: Optional[Tuple[int, int]] = None,
+    add_colorbar: bool = False,
+    colorbar_kwargs: Optional[dict] = None,
+    vmin: Optional[float] = None,
+    vmax: Optional[float] = None,
     cmap="gray",
 ) -> axes.Axes:
-
     if isinstance(spec, torch.Tensor):
         spec = spec.numpy()
 
@@ -54,10 +57,16 @@ def plot_spectrogram(
     if max_freq is None:
         max_freq = spec.shape[-2]
 
-    ax.pcolormesh(
+    mappable = ax.pcolormesh(
         np.linspace(start_time, end_time, spec.shape[-1] + 1, endpoint=True),
         np.linspace(min_freq, max_freq, spec.shape[-2] + 1, endpoint=True),
         spec,
         cmap=cmap,
+        vmin=vmin,
+        vmax=vmax,
     )
+
+    if add_colorbar:
+        plt.colorbar(mappable, ax=ax, **(colorbar_kwargs or {}))
+
     return ax

src/batdetect2/targets/__init__.py

@@ -28,12 +28,17 @@ from batdetect2.targets.rois import (
     ROITargetMapper,
     build_roi_mapper,
 )
-from batdetect2.targets.terms import call_type, individual
+from batdetect2.targets.terms import (
+    call_type,
+    data_source,
+    generic_class,
+    individual,
+)
 from batdetect2.typing.targets import Position, Size, TargetProtocol
 
 __all__ = [
-    "DEFAULT_TARGET_CONFIG",
     "AnchorBBoxMapperConfig",
+    "DEFAULT_TARGET_CONFIG",
     "ROITargetMapper",
     "SoundEventDecoder",
     "SoundEventEncoder",
@@ -44,6 +49,8 @@ __all__ = [
     "build_sound_event_decoder",
     "build_sound_event_encoder",
     "call_type",
+    "data_source",
+    "generic_class",
     "get_class_names_from_config",
     "individual",
     "load_target_config",

src/batdetect2/targets/terms.py

@@ -6,6 +6,7 @@ __all__ = [
     "call_type",
     "individual",
     "data_source",
+    "generic_class",
 ]
 
 # The default key used to reference the 'generic_class' term.

src/batdetect2/typing/postprocess.py

@@ -47,29 +47,7 @@ class GeometryDecoder(Protocol):
 
 
 class RawPrediction(NamedTuple):
-    """Intermediate representation of a single detected sound event.
-
-    Holds extracted information about a detection after initial processing
-    (like peak finding, coordinate remapping, geometry recovery) but before
-    final class decoding and conversion into a `SoundEventPrediction`. This
-    can be useful for evaluation or simpler data handling formats.
-
-    Attributes
-    ----------
-    geometry: data.Geometry
-        The recovered estimated geometry of the detected sound event.
-        Usually a bounding box.
-    detection_score : float
-        The confidence score associated with this detection, typically from
-        the detection heatmap peak.
-    class_scores : xr.DataArray
-        An xarray DataArray containing the predicted probabilities or scores
-        for each target class at the detection location. Indexed by a
-        'category' coordinate containing class names.
-    features : xr.DataArray
-        An xarray DataArray containing extracted feature vectors at the
-        detection location. Indexed by a 'feature' coordinate.
-    """
+    """Intermediate representation of a single detected sound event."""
 
     geometry: data.Geometry
     detection_score: float