analyse_object error about pliman HOT 2 CLOSED

library(pliman)
#> |==========================================================|
#> | Tools for Plant Image Analysis (pliman 1.2.0)            |
#> | Author: Tiago Olivoto                                    |
#> | Type 'citation('pliman')' to know how to cite pliman     |
#> | Type 'vignette('pliman_start')' for a short tutorial     |
#> | Visit 'http://bit.ly/pkg_pliman' for a complete tutorial |
#> |==========================================================|
setwd("E:/Downloads")
# set_wd_here() # set the working directory to the path of file
img <- image_import("img.jpg") 

# first of all, you need to choose an index to segment
# 1. leaves and reference from the background (keep as foreground)
# 2. leaves from reference (keep leaves)

# the following, will perform the segmentation with all available indexes
# image_segment_iter(img, nseg = 2)

# after some tests, the two indexes are B and R-G
image_segment_iter(img, index = c("B", "R-G"))
#>      image   pixels   percent
#> 1 original 22943448 100.00000
#> 2     seg1  8181438  35.65915
#> 3     seg2  8101020  99.01707

# note that fill_hull = TRUE may help you to fill holes
# you can also test the 'filter' argument.. this will remove possible noises


# Now, you can use analyze_objects, with the the following arguments
# the reference object will be colored in red (this will help you to see if the segmentation was performed correctly)
res <- analyze_objects(img, 
                       reference = TRUE, # indicates that there is a reference in the image
                       back_fore_index = "B", # index to segment reference + leaves from background
                       fore_ref_index = "R-G", # index to segment reference and leaves
                       watershed = FALSE, # set to TRUE if leaves are touching each other
                       # object_size = "large", # this will control how watershed works.. try changing to small
                       marker = "area",
                       filter = 3, # remove noise
                       fill_hull = TRUE, # if FALSE, will result in several 'holes' in the leaves
                       reference_area = 4) # I assumed that the reference has 4 cm2, change according

res$results
#>   id         x        y      area   area_ch perimeter radius_mean radius_min
#> 3  3  381.7126 1348.023 109.80755 111.68415  44.81007    6.119369   4.124521
#> 4  4 1539.8681 1469.431 119.17742 121.80397  48.61357    6.424274   4.312093
#> 7  7 1593.0025 3085.195 111.60273 112.41278  45.41554    6.188672   4.312488
#> 8  8  372.5171 3127.172  67.94885  68.79991  37.53980    4.978166   2.893091
#>   radius_max radius_sd diam_mean diam_min diam_max major_axis minor_axis
#> 3   9.126145  1.495792 12.238738 8.249043 18.25229   16.67364   8.418830
#> 4   9.912393  1.527892 12.848548 8.624187 19.82479   17.26657   8.825506
#> 7   9.493167  1.583863 12.377345 8.624976 18.98633   17.20527   8.303927
#> 8   8.104797  1.575048  9.956331 5.786181 16.20959   14.85112   5.850375
#>     length    width radius_ratio eccentricity     theta  solidity convexity
#> 3 17.98685 8.626488     2.212656    0.3471054  1.561144 0.9831973 0.8981382
#> 4 18.61489 9.100198     2.298743    0.3307280  1.445139 0.9784362 0.8417816
#> 7 18.87298 8.751091     2.201320    0.3266697 -1.538252 0.9927940 0.9189865
#> 8 15.98549 5.975648     2.801432    0.2299912  1.416736 0.9876299 0.9147805
#>   elongation circularity circularity_haralick circularity_norm   coverage
#> 3  0.5204003    18.28601             4.091057         1.458265 0.09628134
#> 4  0.5111334    19.82992             4.204665         1.581383 0.10449702
#> 7  0.5363163    18.48137             3.907329         1.473814 0.09785539
#> 8  0.6261830    20.73967             3.160644         1.655233 0.05957884
#>          asm      con       cor       var       idm       sav       sva
#> 3 0.04002358 2.705853 0.7732885  6.967612 0.6046174  8.175257  70.01186
#> 4 0.02118343 2.881822 0.9005808 15.493289 0.5958295 16.751592 289.50067
#> 7 0.03846488 1.495121 0.9385237 13.160129 0.6938088 16.850686 287.62320
#> 8 0.03103248 1.506769 0.9401819 13.594603 0.7055227 16.120046 265.57900
#>        sen      ent      dva       den       f12       f13
#> 3 1.186175 1.631566 2.705853 0.5830037 0.2156136 0.5714213
#> 4 1.441160 1.917670 2.881822 0.5930027 0.3361421 0.7345269
#> 7 1.343339 1.678359 1.495121 0.4842656 0.4114297 0.7621291
#> 8 1.399063 1.724419 1.506769 0.4773082 0.4498587 0.7953645