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65 lines
1.6 KiB
Markdown
65 lines
1.6 KiB
Markdown
# How to save predictions in different output formats
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Use this guide when you need BatDetect2 outputs in a specific representation for downstream tools.
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## Choose the format that matches the job
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Current built-in output formats include:
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- `raw`: one NetCDF file per clip, best for rich structured outputs,
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- `parquet`: tabular storage for data analysis workflows,
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- `soundevent`: prediction-set JSON for soundevent-style tooling,
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- `batdetect2`: legacy per-recording JSON output.
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## Select a format from the CLI
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Use `--format` for quick experiments.
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```bash
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batdetect2 predict directory \
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path/to/model.ckpt \
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path/to/audio_dir \
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path/to/outputs \
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--format parquet
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```
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## Use an outputs config for repeatable runs
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Use an outputs config when you want reproducible control over format and transforms.
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Example:
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```yaml
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format:
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name: raw
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include_class_scores: true
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include_features: true
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include_geometry: true
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transform:
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detection_transforms: []
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clip_transforms: []
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```
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Run with:
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```bash
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batdetect2 predict directory \
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path/to/model.ckpt \
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path/to/audio_dir \
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path/to/outputs \
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--outputs-config path/to/outputs.yaml
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```
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## Pick the simplest useful format
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- Use `raw` if you want the richest output surface and easy round-tripping.
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- Use `parquet` if you want tabular analysis in Python or data-lake workflows.
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- Use `soundevent` if you want prediction-set JSON.
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- Use `batdetect2` only when you need the legacy JSON shape.
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## Related pages
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- Outputs config reference: {doc}`../reference/outputs-config`
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- Output formats reference: {doc}`../reference/output-formats`
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- Output transforms reference: {doc}`../reference/output-transforms`
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