batdetect2/api.py

@@ -123,8 +123,6 @@ from batdetect2.utils.detector_utils import list_audio_files, load_model
 import audioread
 import os 
 import soundfile as sf
-import requests
-import io
 
 # Remove warnings from torch
 warnings.filterwarnings("ignore", category=UserWarning, module="torch")
@@ -281,49 +279,6 @@ def process_file(
         file_id
     )
 
-def process_url(
-    url: str,
-    model: DetectionModel = MODEL,
-    config: Optional[ProcessingConfiguration] = None,
-    device: torch.device = DEVICE,
-    file_id: str | None = None
-) -> du.RunResults:
-    """Process audio file with model.
-
-    Parameters
-    ----------
-    url : str
-        HTTP URL to load the audio data from
-    model : DetectionModel, optional
-        Detection model. Uses default model if not specified.
-    config : Optional[ProcessingConfiguration], optional
-        Processing configuration, by default None (uses default parameters).
-    device : torch.device, optional
-        Device to use, by default tries to use GPU if available.
-    file_id: Optional[str],
-        Give the data an id. Defaults to the URL
-    """
-    if config is None:
-        config = CONFIG
-
-    if file_id is None:
-        file_id = url
-
-    response = requests.get(url)
-
-    # Raise exception on HTTP error
-    response.raise_for_status()
-
-    # Retrieve body as raw bytes
-    raw_audio_data = response.content
-    
-    return du.process_file(
-        io.BytesIO(raw_audio_data),
-        model,
-        config,
-        device,
-        file_id
-    )
 
 def process_spectrogram(
     spec: torch.Tensor,

batdetect2/utils/audio_utils.py

@@ -9,7 +9,6 @@ import torch
 import audioread
 import os 
 import soundfile as sf
-import io
 
 from batdetect2.detector import parameters
 
@@ -148,10 +147,7 @@ def generate_spectrogram(
 def get_samplerate(
     path:  Union[
         str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ]):       
-    if isinstance(path, (BinaryIO, io.BytesIO)):
-        path.seek(0)
-    
+    ]):
     with sf.SoundFile(path) as f:
         return f.samplerate
 

batdetect2/utils/detector_utils.py

@@ -33,10 +33,8 @@ from batdetect2.types import (
 
 import audioread
 import os 
-import io
 import soundfile as sf
-import hashlib
-import uuid
+
 
 __all__ = [
     "load_model",
@@ -834,7 +832,7 @@ def process_file(
 
     _file_id = file_id
     if _file_id is None:
-        _file_id = _generate_id(path)
+        _file_id = os.path.basename(path) if isinstance(path, str) else "unknown"
 
     # convert results to a dictionary in the right format
     results = convert_results(
@@ -858,24 +856,6 @@ def process_file(
 
     return results
 
-def _generate_id(path:  Union[
-        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ]) -> str:
-    """ Generate an id based on the path.
-    
-    If the path is a str or PathLike it will parsed as the basename. 
-    This should ensure backwards compatibility with previous versions.     
-    """
-    if isinstance(path, str) or isinstance(path, os.PathLike):
-        return os.path.basename(path)
-    elif isinstance(path, (BinaryIO, io.BytesIO)):
-        path.seek(0)
-        md5 = hashlib.md5(path.read()).hexdigest()
-        path.seek(0)
-        return md5
-    else:
-        return str(uuid.uuid4())
-
 
 def summarize_results(results, predictions, config):
     """Print summary of results."""

tests/test_api.py

@@ -10,13 +10,11 @@ import torch
 from torch import nn
 
 from batdetect2 import api
-import io 
 
 PKG_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 TEST_DATA_DIR = os.path.join(PKG_DIR, "example_data", "audio")
 TEST_DATA = glob(os.path.join(TEST_DATA_DIR, "*.wav"))
 
-DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
 
 def test_load_model_with_default_params():
     """Test loading model with default parameters."""
@@ -282,28 +280,3 @@ def test_process_file_with_empty_predictions_does_not_fail(
 
     assert results is not None
     assert len(results["pred_dict"]["annotation"]) == 0
-
-def test_process_file_file_id_defaults_to_basename():
-    """Test that no detections are made above the nyquist frequency."""
-    # Recording donated by @@kdarras
-    basename = "20230322_172000_selec2.wav"
-    path = os.path.join(DATA_DIR, basename)
-
-    output = api.process_file(path)
-    predictions = output["pred_dict"]
-    id = predictions["id"]
-    assert id == basename
-
-def test_bytesio_file_id_defaults_to_md5():
-    """Test that no detections are made above the nyquist frequency."""
-    # Recording donated by @@kdarras
-    basename = "20230322_172000_selec2.wav"
-    path = os.path.join(DATA_DIR, basename)
-
-    with open(path, "rb") as f:
-        data = io.BytesIO(f.read())
-
-    output = api.process_file(data)
-    predictions = output["pred_dict"]
-    id = predictions["id"]
-    assert id == "7ade9ebf1a9fe5477ff3a2dc57001929"

tests/test_audio_utils.py

@@ -7,9 +7,7 @@ from hypothesis import strategies as st
 from batdetect2.detector import parameters
 from batdetect2.utils import audio_utils, detector_utils
 import io
-import os
-
-DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
+import requests
 
 @given(duration=st.floats(min_value=0.1, max_value=2))
 def test_can_compute_correct_spectrogram_width(duration: float):
@@ -146,48 +144,3 @@ def test_get_samplerate_using_bytesio():
 
     expected_sample_rate = 500000
     assert expected_sample_rate == sample_rate
-
-    
-
-def test_load_audio_using_bytes():
-    filename = "example_data/audio/20170701_213954-MYOMYS-LR_0_0.5.wav"
-    
-    with open(filename, "rb") as f:
-        audio_bytes = io.BytesIO(f.read())
-    
-    sample_rate, audio_data = audio_utils.load_audio(audio_bytes, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
-
-    expected_sample_rate, expected_audio_data = audio_utils.load_audio(filename, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
-
-    assert expected_sample_rate == sample_rate
-
-    assert np.array_equal(audio_data, expected_audio_data)
-
-
-
-def test_get_samplerate_using_bytesio_2():
-    basename = "20230322_172000_selec2.wav"
-    path = os.path.join(DATA_DIR, basename)
-
-    with open(path, "rb") as f:
-        audio_bytes = io.BytesIO(f.read())
-    
-    sample_rate = audio_utils.get_samplerate(audio_bytes)
-
-    expected_sample_rate = 192_000
-    assert expected_sample_rate == sample_rate
-
-def test_load_audio_using_bytes_2():
-    basename = "20230322_172000_selec2.wav"
-    path = os.path.join(DATA_DIR, basename)
-
-    with open(path, "rb") as f:
-        data = io.BytesIO(f.read())
-    
-    sample_rate, audio_data = audio_utils.load_audio(data, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
-
-    expected_sample_rate, expected_audio_data = audio_utils.load_audio(path, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
-
-    assert expected_sample_rate == sample_rate
-
-    assert np.array_equal(audio_data, expected_audio_data)