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https://github.com/macaodha/batdetect2.git
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999dc93d88
Clarify BatDetect2API usage, add examples and NumPy-style docstrings, and tighten CLI help and reference pages for prediction, training, evaluation, and fine-tuning workflows.
40 lines
1.0 KiB
Markdown
40 lines
1.0 KiB
Markdown
# `BatDetect2API` reference
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`BatDetect2API` is the main Python entry point for BatDetect2.
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Use it when you want to load a model, run prediction, inspect detections,
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evaluate results, or train from Python.
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Defined in `batdetect2.api_v2`.
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## Main ways to create it
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- `BatDetect2API.from_checkpoint(path, ...)`
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- load a trained checkpoint, a bundled checkpoint alias, or a Hugging Face
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checkpoint.
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- `BatDetect2API.from_config(model_config=..., targets_config=..., ...)`
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- build a full model stack from config objects.
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## Common tasks
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- Load a checkpoint and run prediction on one file.
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- Run prediction on many files or clips.
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- Save predictions in one of the supported output formats.
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- Evaluate a model on labelled data.
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- Fine-tune an existing checkpoint on new targets.
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## Generated reference
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```{eval-rst}
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.. autoclass:: batdetect2.api_v2.BatDetect2API
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```
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## Related pages
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- Python tutorial:
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{doc}`../tutorials/integrate-with-a-python-pipeline`
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- Outputs config reference:
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{doc}`outputs-config`
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- Output formats reference:
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{doc}`output-formats`
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