Predicts the probability that a x3p scan will be good and also predicts the reason why it is bad quality if it is predicted to be bad quality.

Predicts the probability that a x3p scan will be good and also predicts the reason why it is bad quality if it is predicted to be bad quality.

predict_quality(x3plist, x3pnamevector)

Arguments

x3plist

list of x3p scans of a bullet land

x3pnamevector

a vector of names of x3p files

Value

a dataframe with one row, containing all feature values and a prediction of the scan quality

Examples

data(fau277_bb_l2)
predict_quality(list(fau277_bb_l2, fau277_bb_l2), x3pnamevector=c(1,2))
#> # A tibble: 2 × 11
#>   x3p    x3pname quali…¹ quali…² asses…³ asses…⁴ extra…⁵ asses…⁶ asses…⁷ asses…⁸
#>   <I<li>   <dbl>   <dbl> <chr>     <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
#> 1 <x3p>        1   0.858 good     0.0891    4.72    38.3   0.317    1.11    95.2
#> 2 <x3p>        2   0.858 good     0.0891    4.72    38.3   0.317    1.11    95.2
#> # … with 1 more variable: lighting_protocol <fct>, and abbreviated variable
#> #   names ¹​quality_pred, ²​quality_type, ³​assess_percentile_na_proportion,
#> #   ⁴​assess_col_na, ⁵​extract_na, ⁶​assess_middle_na_proportion,
#> #   ⁷​assess_rotation, ⁸​assess_bottomempty