Find the number of output features in scikit image

skimage_output_features.py

import numpy as np
from skimage.measure import regionprops_table

img = np.ones((5, 5), dtype=int)
mask = np.zeros((5, 5), dtype=int)
mask[0:3, 0:3] = 1

feat_names = (
    "area",
    "bbox",
    "area_bbox",
    "moments_central",
    "centroid",
    "area_convex",
    # 'ConvexHull',
    # "image_convex",
    # "coords",
    "eccentricity",
    "equivalent_diameter_area",
    "euler_number",
    "extent",
    # 'Extrema',
    "feret_diameter_max",
    "area_filled",
    # "image_filled",
    "moments_hu",
    # "image",
    "inertia_tensor",
    "inertia_tensor_eigvals",
    # "image_intensity",
    "centroid_local",
    "axis_major_length",
    "intensity_max",
    "intensity_mean",
    "intensity_min",
    "intensity_std",
    "axis_minor_length",
    "axis_minor_length",
    "moments",
    "moments_normalized",
    "orientation",
    "perimeter",
    "perimeter_crofton",
    # 'PixelIdxList',
    # 'PixelList',
    # "slice",
    "solidity",
    # 'SubarrayIdx'
    "moments_weighted_central",
    "moments_weighted_central",
    "centroid_weighted",
    "centroid_weighted",
    "moments_weighted_hu",
    "moments_weighted_hu",
    "centroid_weighted_local",
    "centroid_weighted_local",
    "moments_weighted",
    "moments_weighted",
    "moments_weighted_normalized",
    "moments_weighted_normalized",
)
feats = regionprops_table(img, mask, properties=feat_names)
from pprint import pprint

pprint(feats)