| leaf_id_flavia | R Documentation | 
Image analysis of leaves to predict species.
From the original manuscript: "The Flavia dataset contains 1907 leaf images. There are 32 different species and each has 50-77 images. Scanners and digital cameras are used to acquire the leaf images on a plain background. The isolated leaf images contain blades only, without a petiole. These leaf images are collected from the most common plants in Yangtze, Delta, China. Those leaves were sampled on the campus of the Nanjing University and the Sun Yat-Sen arboretum, Nanking, China."
The reference below has details information on the features used for prediction.
Columns:
species:  factor (32 levels)
apex:  factor (9 levels)
base:  factor (6 levels)
shape:  factor (5 levels)
denate_edge:  factor (levels: 'no' and 'yes')
lobed_edge:  factor (levels: 'no' and 'yes')
smooth_edge:  factor (levels: 'no' and 'yes')
toothed_edge:  factor (levels: 'no' and 'yes')
undulate_edge:  factor (levels: 'no' and 'yes')
outlying_polar:  numeric
skewed_polar:  numeric
clumpy_polar:  numeric
sparse_polar:  numeric
striated_polar:  numeric
convex_polar:  numeric
skinny_polar:  numeric
stringy_polar:  numeric
monotonic_polar:  numeric
outlying_contour:  numeric
skewed_contour:  numeric
clumpy_contour:  numeric
sparse_contour:  numeric
striated_contour:  numeric
convex_contour:  numeric
skinny_contour:  numeric
stringy_contour:  numeric
monotonic_contour:  numeric
num_max_ponits:  numeric
num_min_points:  numeric
diameter:  numeric
area:  numeric
perimeter:  numeric
physiological_length:  numeric
physiological_width:  numeric
aspect_ratio:  numeric
rectangularity:  numeric
circularity:  numeric
compactness:  numeric
narrow_factor:  numeric
perimeter_ratio_diameter:  numeric
perimeter_ratio_length:  numeric
perimeter_ratio_lw:  numeric
num_convex_points:  numeric
perimeter_convexity:  numeric
area_convexity:  numeric
area_ratio_convexity:  numeric
equivalent_diameter:  numeric
eccentriciry:  numeric
contrast:  numeric
correlation_texture:  numeric
inverse_difference_moments:  numeric
entropy:  numeric
mean_red_val:  numeric
mean_green_val:  numeric
mean_blue_val:  numeric
std_red_val:  numeric
std_green_val:  numeric
std_blue_val:  numeric
correlation:  numeric
leaf_id_flavia | 
 a data frame  | 
Lakshika, Jayani PG, and Thiyanga S. Talagala. "Computer-aided interpretable features for leaf image classification." arXiv preprint arXiv:2106.08077 (2021).
https://github.com/SMART-Research/leaffeatures_paper
data(leaf_id_flavia)
str(leaf_id_flavia)
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