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66 lines
2.0 KiB
Markdown
66 lines
2.0 KiB
Markdown
# `BatDetect2API` reference
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`BatDetect2API` is the main entry point for the current Python workflow.
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It wraps model loading, inference, evaluation, output formatting, and training-related entry points behind one object.
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Defined in `batdetect2.api_v2`.
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## Create an API instance
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- `BatDetect2API.from_checkpoint(path, ...)`
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- load a trained checkpoint and optional config overrides.
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- `BatDetect2API.from_config(config)`
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- build a full stack from a `BatDetect2Config` object.
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## Inference methods
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- `process_file(audio_file, ...)`
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- run inference for one recording.
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- `process_files(audio_files, ...)`
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- run batch inference across a sequence of file paths.
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- `process_directory(audio_dir, ...)`
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- run inference across the audio files found in one directory.
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- `process_clips(clips, ...)`
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- run inference on an explicit sequence of clip objects.
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- `process_audio(audio, ...)`
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- run inference starting from a waveform array.
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- `process_spectrogram(spec, ...)`
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- run inference starting from a spectrogram tensor.
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## Prediction inspection helpers
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- `get_top_class_name(detection)`
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- return the highest-scoring class name for one detection.
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- `get_class_scores(detection, include_top_class=True, sort_descending=True)`
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- return ranked `(class_name, score)` pairs.
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- `get_detection_features(detection)`
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- return the per-detection feature vector.
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## Audio loading helpers
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- `load_audio(path)`
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- `load_recording(recording)`
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- `load_clip(clip)`
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- `generate_spectrogram(audio)`
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## Output persistence helpers
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- `save_predictions(predictions, path, audio_dir=None, format=None, config=None)`
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- `load_predictions(path, format=None, config=None)`
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Use these when you want to save programmatic predictions without going through the CLI.
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## Training and evaluation entry points
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- `train(...)`
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- `finetune(...)`
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- `evaluate(...)`
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- `evaluate_predictions(...)`
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## Related pages
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- Python tutorial: {doc}`../tutorials/integrate-with-a-python-pipeline`
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- Outputs config reference: {doc}`outputs-config`
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- Output formats reference: {doc}`output-formats`
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