Decouple config loading from preprocess function

batdetect2/api.py

@@ -96,6 +96,7 @@ If you wish to use a custom model or change the default parameters, please
 consult the API documentation in the code.
 
 """
+
 import warnings
 from typing import List, Optional, Tuple
 
@@ -410,7 +411,9 @@ def print_summary(results: RunResults) -> None:
         Detection result.
     """
     print("Results for " + results["pred_dict"]["id"])
-    print("{} calls detected\n".format(len(results["pred_dict"]["annotation"])))
+    print(
+        "{} calls detected\n".format(len(results["pred_dict"]["annotation"]))
+    )
 
     print("time\tprob\tlfreq\tspecies_name")
     for ann in results["pred_dict"]["annotation"]:

batdetect2/data/labels.py

@@ -65,7 +65,6 @@ def generate_heatmaps(
 
         # Get the position of the sound event
         time, frequency = geometry.get_geometry_point(geom, position=position)
-        print(time, frequency)
 
         # Set 1.0 at the position of the sound event in the detection heatmap
         detection_heatmap = arrays.set_value_at_pos(

batdetect2/train/preprocess.py

@@ -116,6 +116,9 @@ def preprocess_single_annotation(
     if path.is_file() and not replace:
         return
 
+    if path.is_file() and replace:
+        path.unlink()
+
     sample = generate_train_example(
         clip_annotation,
         class_mapper,
@@ -133,21 +136,18 @@ def preprocess_annotations(
     target_sigma: float = TARGET_SIGMA,
     filename_fn: FilenameFn = _get_filename,
     replace: bool = False,
-    config_file: Optional[PathLike] = None,
+    config: Optional[PreprocessingConfig] = None,
     max_workers: Optional[int] = None,
-    **kwargs,
 ) -> None:
     """Preprocess annotations and save to disk."""
     output_dir = Path(output_dir)
 
+    if config is None:
+        config = PreprocessingConfig()
+
     if not output_dir.is_dir():
         output_dir.mkdir(parents=True)
 
-    if config_file is not None:
-        config = load_config(config_file, **kwargs)
-    else:
-        config = PreprocessingConfig(**kwargs)
-
     with Pool(max_workers) as pool:
         list(
             tqdm(