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How to choose an inference input mode
Use this guide to decide whether process directory, process file_list, or
process dataset is the right entry point for your run.
Use process directory when the recordings already live together
This is the simplest choice.
Use it when:
- your recordings are already organized in one directory tree,
- you want BatDetect2 to discover audio files for you,
- you are doing a first pass over a folder of recordings.
batdetect2 process directory \
path/to/model.ckpt \
path/to/audio_dir \
path/to/outputs
Use process file_list when you need explicit control over the file set
Use it when:
- you want to run only a selected subset,
- your files are spread across directories,
- another tool has already produced the exact list of recordings to process.
The list file should contain one path per line.
batdetect2 process file_list \
path/to/model.ckpt \
path/to/audio_files.txt \
path/to/outputs
Use process dataset when your workflow is already annotation-set driven
Use it when:
- your project already has a
soundeventannotation set, - you want prediction runs aligned with that annotation metadata,
- you want BatDetect2 to resolve recording paths from the annotation set.
batdetect2 process dataset \
path/to/model.ckpt \
path/to/annotation_set.json \
path/to/outputs
The dataset command reads a soundevent annotation set and extracts unique
recording paths before inference.
Rule of thumb
- Start with
directoryfor the easiest first run. - Use
file_listwhen selection matters. - Use
datasetwhen the rest of your workflow is already dataset-based.
Related pages
- Run batch predictions:
{doc}
run-batch-predictions - Tune inference clipping:
{doc}
tune-inference-clipping - Process command reference:
{doc}
../reference/cli/predict