Update README.md (#5)
Browse files- Update README.md (d03ebfdaad7fcc920457c4060a3f01aa091a5887)
Co-authored-by: Alexander Gebhard <[email protected]>
README.md
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@@ -53,6 +53,13 @@ The model can be applied on all wav files present in a folder (`<data-root>`) an
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autrainer inference hf:autrainer/edansa-2019-cnn10-32k-t <data-root> <output-root>
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```
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## Training
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### Pretraining
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autrainer inference hf:autrainer/edansa-2019-cnn10-32k-t <data-root> <output-root>
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```
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In order to obtain the predictions based on the class-specific count thresholds, we recommend using a window size of 10s and a hop size of 1s (`-w 10 -s 1`).
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Then apply the postprocess_predictions.py script to obtain the final predictions by specifying the csv path (`--path`) to the results.csv:
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```
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python postprocess_predictions.py --path /path/to/results.csv
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```
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## Training
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### Pretraining
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