Source code for arthropod_describer.plugins.test_plugin.properties.geodesic_length_cpp

import copy
import os
import subprocess
import typing
from pathlib import Path
from typing import Optional

import skimage.io
from skimage import img_as_ubyte
from skimage.morphology import skeletonize, medial_axis

from arthropod_describer.common.common import Info
from arthropod_describer.common.label_image import RegionProperty, PropertyType
from arthropod_describer.common.photo import Photo
from arthropod_describer.common.plugin import PropertyComputation
from arthropod_describer.common.regions_cache import RegionsCache, Region
from arthropod_describer.common.units import Value
from arthropod_describer.common.user_params import UserParam
from arthropod_describer.plugins.test_plugin.properties.geodesic_utils import compute_longest_geodesic, \
    compute_longest_geodesic_perf


[docs]class GeodesicLength(PropertyComputation): """ GROUP: Basic properties NAME: Geodesic length(cpp) DESCRIPTION: Geodesic length (px or mm) KEY: geodesic_length2 """ def __init__(self, info: Optional[Info] = None): super().__init__(info) def __call__(self, photo: Photo, region_labels: typing.List[int], regions_cache: RegionsCache) -> \ typing.List[RegionProperty]: # lab_img = photo['Labels'].label_image props: typing.List[RegionProperty] = [] for label in region_labels: # _, length = get_longest_geodesic(lab_img, label) if label not in regions_cache.regions: continue region_obj = regions_cache.regions[label] # length, _, _ = compute_longest_geodesic(region_obj.mask) # skeleton = skeletonize(region_obj.mask) # length = compute_longest_geodesic_perf(skeleton) # skimage.io.imsave('C:/Users/radoslav/Desktop/body_region.png', region_obj.mask) # compute_longest_geodesic(lab_img == label) bin_path = Path(__file__).parent / 'bin/geodesic_length.exe' reg_path = Path(__file__).parent / f'body_region_{photo.image_name}.png' skimage.io.imsave(str(reg_path), img_as_ubyte(region_obj.mask), check_contrast=False) out_path = Path(__file__).parent / f'result_{photo.image_name}.txt' args = [ str(bin_path), str(reg_path), str(out_path) ] return_obj = subprocess.run(args, cwd=str(bin_path.parent)) if return_obj.returncode != 0: continue with open(out_path) as f: length = float(f.readlines()[0].strip()) if length < 0: os.remove(reg_path) os.remove(out_path) continue prop = RegionProperty() prop.label = int(label) prop.info = copy.deepcopy(self.info) value = Value(float(length), self._px_unit) if photo.image_scale is not None: # prop.unit = 'mm' prop.value = value / photo.image_scale else: prop.value = value prop.val_names = ['Geodesic length2'] prop.num_vals = 1 props.append(prop) os.remove(reg_path) os.remove(out_path) return props @property def user_params(self) -> typing.List[UserParam]: return super().user_params @property def region_restricted(self) -> bool: return super().region_restricted @property def computes(self) -> typing.Dict[str, Info]: return {self.info.key: self.info}
[docs] def example(self, prop_name: str) -> RegionProperty: prop = RegionProperty() prop.label = 0 prop.info = copy.deepcopy(self.info) prop.value = None prop.num_vals = 1 prop.prop_type = PropertyType.Scalar prop.val_names = [] return prop
[docs] def target_worksheet(self, prop_name: str) -> str: return super(GeodesicLength, self).target_worksheet(self.info.key)
@property def group(self) -> str: return super().group