def geojson_to_masks(
file_proc,
mask_types=["filled", "edge", "labels"],
img_size=None,
):
# annot_types = list(masks_to_create.keys())
annotationsImporter = annotationUtils.GeojsonImporter()
# Instance to save masks
masks = annotationUtils.MaskGenerator()
weightedEdgeMasks = annotationUtils.WeightedEdgeMaskGenerator(sigma=8,
w0=10)
distMapMasks = annotationUtils.DistanceMapGenerator(truncate_distance=None)
# Decompose file name
drive, path_and_file = os.path.splitdrive(file_proc)
path, file = os.path.split(path_and_file)
# file_base, ext = os.path.splitext(file)
# Read annotation: Correct class has been selected based on annot_type
annot_dict_all, roi_size_all, image_size = annotationsImporter.load(
file_proc)
if img_size is not None:
image_size = img_size
annot_types = set(annot_dict_all[k]["properties"]["label"]
for k in annot_dict_all.keys())
masks = {}
for annot_type in annot_types:
# print("annot_type: ", annot_type)
# Filter the annotations by label
annot_dict = {
k: annot_dict_all[k]
for k in annot_dict_all.keys()
if annot_dict_all[k]["properties"]["label"] == annot_type
}
# Create masks
# Binary - is always necessary to creat other masks
binaryMasks = annotationUtils.BinaryMaskGenerator(
image_size=image_size,
erose_size=5,
obj_size_rem=500,
save_indiv=True)
mask_dict = binaryMasks.generate(annot_dict)
# Distance map
if "distance" in mask_types:
mask_dict = distMapMasks.generate(annot_dict, mask_dict)
# Weighted edge mask
if "weigthed" in mask_types:
mask_dict = weightedEdgeMasks.generate(annot_dict, mask_dict)
# border_mask
if "border_mask" in mask_types:
border_detection_threshold = max(
round(1.33 * image_size[0] / 512 + 0.66), 1)
borderMasks = annotationUtils.BorderMaskGenerator(
border_detection_threshold=border_detection_threshold)
mask_dict = borderMasks.generate(annot_dict, mask_dict)
return mask_dict
def gen_mask_from_geojson(files_proc,
masks_to_create_value=[
'filled', 'edge', 'distance', 'weigthed',
'border_mask'
],
img_size=None,
infer=False,
border_detection_threshold=6):
masks_to_create = {}
# annot_types = list(masks_to_create.keys())
annotationsImporter = annotationUtils.GeojsonImporter()
# Instance to save masks
masks = annotationUtils.MaskGenerator()
weightedEdgeMasks = annotationUtils.WeightedEdgeMaskGenerator(sigma=8,
w0=10)
distMapMasks = annotationUtils.DistanceMapGenerator(truncate_distance=None)
borderMasks = annotationUtils.BorderMaskGenerator(
border_detection_threshold=border_detection_threshold)
# %% Loop over all files
for i, file_proc in enumerate(files_proc):
print('PROCESSING FILE:')
print(file_proc)
# Decompose file name
drive, path_and_file = os.path.splitdrive(file_proc)
path, file = os.path.split(path_and_file)
# file_base, ext = os.path.splitext(file)
# Read annotation: Correct class has been selected based on annot_type
annot_dict_all, roi_size_all, image_size = annotationsImporter.load(
file_proc)
if img_size is not None:
image_size = img_size
annot_types = set(annot_dict_all[k]['properties']['label']
for k in annot_dict_all.keys())
print("annot_types: ", annot_types)
for annot_type in annot_types:
if infer:
file_name_save = os.path.join(
drive, path, annot_type + '_filled_output.png')
else:
file_name_save = os.path.join(drive, path,
annot_type + '_filled.png')
if os.path.exists(file_name_save):
print("skip to generate mask:", file_name_save)
continue
# print("annot_type: ", annot_type)
masks_to_create[annot_type] = masks_to_create_value
# Filter the annotations by label
annot_dict = {
k: annot_dict_all[k]
for k in annot_dict_all.keys()
if annot_dict_all[k]['properties']['label'] == annot_type
}
# print("len(annot_dict):", len(annot_dict))
# print("annot_dict.keys():", annot_dict.keys())
# Create masks
# Binary - is always necessary to creat other masks
print(' .... creating binary masks .....')
binaryMasks = annotationUtils.BinaryMaskGenerator(
image_size=image_size,
erose_size=5,
obj_size_rem=500,
save_indiv=True)
mask_dict = binaryMasks.generate(annot_dict)
# Save binary masks FILLED if specified
if 'filled' in masks_to_create[annot_type]:
if infer:
file_name_save = os.path.join(
drive, path, annot_type + '_filled_output.png')
else:
file_name_save = os.path.join(drive, path,
annot_type + '_filled.png')
masks.save(mask_dict, 'fill', file_name_save)
# Edge mask
if 'edge' in masks_to_create[annot_type]:
if infer:
file_name_save = os.path.join(
drive, path, annot_type + '_edge_output.png')
else:
file_name_save = os.path.join(drive, path,
annot_type + '_edge.png')
masks.save(mask_dict, 'edge', file_name_save)
# Distance map
if 'distance' in masks_to_create[annot_type]:
print(' .... creating distance maps .....')
mask_dict = distMapMasks.generate(annot_dict, mask_dict)
# Save
if infer:
file_name_save = os.path.join(
drive, path, annot_type + '_distmap_output.png')
else:
file_name_save = os.path.join(drive, path,
annot_type + '_distmap.png')
masks.save(mask_dict, 'distance_map', file_name_save)
# Weighted edge mask
if 'weigthed' in masks_to_create[annot_type]:
print(' .... creating weighted edge masks .....')
mask_dict = weightedEdgeMasks.generate(annot_dict, mask_dict)
# Save
if infer:
file_name_save = os.path.join(
drive, path, annot_type + '_edgeweight_output.png')
else:
file_name_save = os.path.join(
drive, path, annot_type + '_edgeweight.png')
masks.save(mask_dict, 'edge_weighted', file_name_save)
# border_mask
if 'border_mask' in masks_to_create[annot_type]:
print(' .... creating border masks .....')
mask_dict = borderMasks.generate(annot_dict, mask_dict)
# Save
if infer:
file_name_save = os.path.join(
drive, path, annot_type + '_border_mask_output.png')
else:
file_name_save = os.path.join(
drive, path, annot_type + '_border_mask.png')
cv2.imwrite(file_name_save, mask_dict['border_mask'],
[cv2.IMWRITE_PNG_COMPRESSION, 9])
def gen_mask_from_geojson(self, files_proc, img_size=None, infer=False):
# %% Some housekeeping to setup example data
# files_proc= [os.path.abspath(os.path.join('..','data','maskGenerator','img','annotation.json'))]
# masks_to_create = {
# "cells": ['filled', 'edge', 'distance', 'weigthed'],
# "nuclei": ['filled', 'edge', 'distance', 'weigthed'],
# }
masks_to_create = {}
masks_to_create_value = ['filled', 'edge', 'distance', 'weigthed']
# annot_types = list(masks_to_create.keys())
annotationsImporter = annotationUtils.GeojsonImporter()
# Instance to save masks
masks = annotationUtils.MaskGenerator()
weightedEdgeMasks = annotationUtils.WeightedEdgeMaskGenerator(sigma=8, w0=10)
distMapMasks = annotationUtils.DistanceMapGenerator(truncate_distance=None)
# %% Loop over all files
count = len(files_proc)
for i, file_proc in enumerate(files_proc):
print('PROCESSING FILE:')
print(file_proc)
dir_name, file_name = os.path.split(file_proc)
api.showStatus('generating masks for: ' + dir_name.split('/')[-1])
api.showProgress(i / count * 100)
# Decompose file name
drive, path_and_file = os.path.splitdrive(file_proc)
path, file = os.path.split(path_and_file)
file_base, ext = os.path.splitext(file)
# Read annotation: Correct class has been selected based on annot_type
annot_dict_all, roi_size_all, image_size = annotationsImporter.load(file_proc)
if img_size is not None:
image_size = img_size
annot_types = set(annot_dict_all[k]['properties']['label'] for k in annot_dict_all.keys())
print("annot_types: ", annot_types)
for annot_type in annot_types:
# print("annot_type: ", annot_type)
masks_to_create[annot_type] = masks_to_create_value
# Filter the annotations by label
annot_dict = {k: annot_dict_all[k] for k in annot_dict_all.keys() if
annot_dict_all[k]['properties']['label'] == annot_type}
# print("len(annot_dict):", len(annot_dict))
# print("annot_dict.keys():", annot_dict.keys())
# Create masks
# Binary - is always necessary to creat other masks
print(' .... creating binary masks .....')
binaryMasks = annotationUtils.BinaryMaskGenerator(image_size=image_size, erose_size=5, obj_size_rem=500,
save_indiv=True)
mask_dict = binaryMasks.generate(annot_dict)
# Save binary masks FILLED if specified
if 'filled' in masks_to_create[annot_type]:
if infer:
file_name_save = os.path.join(drive, path, annot_type + '_filled_output.png')
else:
file_name_save = os.path.join(drive, path, annot_type + '_filled.png')
masks.save(mask_dict, 'fill', file_name_save)
# # Edge mask
# if 'edge' in masks_to_create[annot_type]:
# if infer:
# file_name_save = os.path.join(drive,path, annot_type + '_edge_output.png')
# else:
# file_name_save = os.path.join(drive,path, annot_type + '_edge.png')
# masks.save(mask_dict,'edge',file_name_save)
# Distance map
if 'distance' in masks_to_create[annot_type]:
print(' .... creating distance maps .....')
mask_dict = distMapMasks.generate(annot_dict, mask_dict)
# Save
if infer:
file_name_save = os.path.join(drive, path, annot_type + '_distmap_output.png')
else:
file_name_save = os.path.join(drive, path, annot_type + '_distmap.png')
masks.save(mask_dict, 'distance_map', file_name_save)