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4b75e13fa2
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2100a3e483
@ -1,5 +1,5 @@
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[bumpversion]
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current_version = 1.2.0
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current_version = 1.1.1
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commit = True
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tag = True
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@ -3,4 +3,4 @@ import logging
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numba_logger = logging.getLogger("numba")
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numba_logger.setLevel(logging.WARNING)
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__version__ = "1.2.0"
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__version__ = "1.1.1"
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@ -45,12 +45,6 @@ def cli():
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default=False,
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help="Extracts CNN call features",
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)
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@click.option(
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"--chunk_size",
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type=float,
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default=2,
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help="Specifies the duration of chunks in seconds. BatDetect2 will divide longer files into smaller chunks and process them independently. Larger chunks increase computation time and memory usage but may provide more contextual information for inference.",
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)
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@click.option(
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"--spec_features",
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is_flag=True,
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@ -86,7 +80,6 @@ def detect(
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ann_dir: str,
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detection_threshold: float,
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time_expansion_factor: int,
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chunk_size: float,
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**args,
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):
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"""Detect bat calls in files in AUDIO_DIR and save predictions to ANN_DIR.
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@ -115,7 +108,7 @@ def detect(
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**args,
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"time_expansion": time_expansion_factor,
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"spec_slices": False,
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"chunk_size": chunk_size,
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"chunk_size": 2,
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"detection_threshold": detection_threshold,
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}
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)
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@ -154,7 +147,6 @@ def print_config(config: ProcessingConfiguration):
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click.echo("\nProcessing Configuration:")
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click.echo(f"Time Expansion Factor: {config.get('time_expansion')}")
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click.echo(f"Detection Threshold: {config.get('detection_threshold')}")
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click.echo(f"Chunk Size: {config.get('chunk_size')}s")
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if __name__ == "__main__":
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@ -1,6 +1,6 @@
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[project]
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name = "batdetect2"
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version = "1.2.0"
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version = "1.1.1"
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description = "Deep learning model for detecting and classifying bat echolocation calls in high frequency audio recordings."
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authors = [
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{ "name" = "Oisin Mac Aodha", "email" = "oisin.macaodha@ed.ac.uk" },
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@ -130,29 +130,3 @@ def test_cli_detect_fails_gracefully_on_empty_file(tmp_path: Path):
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)
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assert result.exit_code == 0
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assert f"Error processing file {empty_file}" in result.output
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def test_can_set_chunk_size(tmp_path: Path):
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results_dir = tmp_path / "results"
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# Remove results dir if it exists
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if results_dir.exists():
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results_dir.rmdir()
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result = runner.invoke(
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cli,
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[
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"detect",
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"example_data/audio",
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str(results_dir),
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"0.3",
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"--chunk_size",
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"1",
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],
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)
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assert "Chunk Size: 1.0s" in result.output
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assert result.exit_code == 0
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assert results_dir.exists()
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assert len(list(results_dir.glob("*.csv"))) == 3
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assert len(list(results_dir.glob("*.json"))) == 3
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