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README.md
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`Kitchen/participant_mapping.tsv` maps anonymized Kitchen IDs back to the
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original local recording names.
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## Known data issue
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Lab participant `P21` contains 4,707 source JPEG files that OpenCV cannot
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`Kitchen/participant_mapping.tsv` maps anonymized Kitchen IDs back to the
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original local recording names.
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## Getting started
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The full dataset is approximately 600 GB. We recommend starting with
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`Kitchen/P12` (the Yianni recording), which is one of the higher-quality
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recordings, before downloading the remainder of the dataset.
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## Force preprocessing and sensor quality
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The piezoresistive sensors are noisy. [`preprocess.py`](preprocess.py) contains
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the preprocessing pipeline used to derive contact ground truth from the raw
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sensor measurements. This pipeline is intended for contact estimation; work
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that directly predicts force magnitudes will require a somewhat different
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preprocessing pipeline.
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Some fingers experienced sensor drift or sensor malfunction during a
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recording. A combination of manual and automatic review was used to filter out
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the affected measurements. In the processed CSV files, the corresponding force
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columns are set to `NaN` for the affected intervals. Consequently, some fingers
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are absent from the supplied visualizations. Learning pipelines should treat
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these values as missing data rather than as zero-force observations, and should
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mask or otherwise handle them during training and evaluation.
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## Known data issue
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Lab participant `P21` contains 4,707 source JPEG files that OpenCV cannot
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