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BSD 3-Clause License | ||
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Copyright (c) 2021, Kevin Cutler | ||
All rights reserved. | ||
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Redistribution and use in source and binary forms, with or without | ||
modification, are permitted provided that the following conditions are met: | ||
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1. Redistributions of source code must retain the above copyright notice, this | ||
list of conditions and the following disclaimer. | ||
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2. Redistributions in binary form must reproduce the above copyright notice, | ||
this list of conditions and the following disclaimer in the documentation | ||
and/or other materials provided with the distribution. | ||
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3. Neither the name of the copyright holder nor the names of its | ||
contributors may be used to endorse or promote products derived from | ||
this software without specific prior written permission. | ||
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | ||
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE | ||
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL | ||
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR | ||
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, | ||
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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# ncolor | ||
Fast remapping of intance labels 1,2,3,...,M to N repeating, disjoint labels, 1,2,3,...,N. The four-color-theorem guarantees that at most four colors is required for any 2D segmentation/map, but this algorithm will opt for 5 or 6 to give an acceptable result quickly. Also works for 3D labels (<8 colors typically required) and perhaps higher dimensions as well. |
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#4-color algorthm based on https://forum.image.sc/t/relabel-with-4-colors-like-map/33564 with extensions and improvements | ||
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import numpy as np | ||
from numba import njit | ||
import scipy | ||
from scipy.ndimage.morphology import binary_dilation, binary_erosion | ||
import edt | ||
import random | ||
import fastremap | ||
from skimage import measure | ||
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def label(lab,n=4,conn=2): | ||
# needs to be in standard label form | ||
# but also needs to be in int32 data type to work properly; the formatting automatically | ||
# puts it into the smallest datatype to save space | ||
lab = format_labels(lab).astype(np.int32) | ||
idx = connect(lab, conn) | ||
idx = mapidx(idx) | ||
colors = render_net(idx, n=n, rand=10) | ||
lut = np.ones(lab.max()+1, dtype=np.uint8) | ||
for i in colors: lut[i] = colors[i] | ||
lut[0] = 0 | ||
return lut[lab] | ||
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def neighbors(shape, conn=1): | ||
dim = len(shape) | ||
block = scipy.ndimage.generate_binary_structure(dim, conn) | ||
block[tuple([1]*dim)] = 0 | ||
idx = np.where(block>0) | ||
idx = np.array(idx, dtype=np.uint8).T | ||
idx = np.array(idx-[1]*dim) | ||
acc = np.cumprod((1,)+shape[::-1][:-1]) | ||
return np.dot(idx, acc[::-1]) | ||
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@njit(fastmath=True) | ||
def search(img, nbs): | ||
s, line = 0, img.ravel() | ||
rst = np.zeros((len(line),2), img.dtype) | ||
for i in range(len(line)): | ||
if line[i]==0:continue | ||
for d in nbs: | ||
if line[i+d]==0: continue | ||
if line[i]==line[i+d]: continue | ||
rst[s,0] = line[i] | ||
rst[s,1] = line[i+d] | ||
s += 1 | ||
return rst[:s] | ||
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def connect(img, conn=1): | ||
buf = np.pad(img, 1, 'constant') | ||
nbs = neighbors(buf.shape, conn) | ||
rst = search(buf, nbs) | ||
if len(rst)<2: | ||
return rst | ||
rst.sort(axis=1) | ||
key = (rst[:,0]<<16) | ||
key += rst[:,1] | ||
order = np.argsort(key) | ||
key[:] = key[order] | ||
diff = key[:-1]!=key[1:] | ||
idx = np.where(diff)[0]+1 | ||
idx = np.hstack(([0], idx)) | ||
return rst[order][idx] | ||
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def mapidx(idx): | ||
dic = {} | ||
for i in np.unique(idx): dic[i] = [] | ||
for i,j in idx: | ||
dic[i].append(j) | ||
dic[j].append(i) | ||
return dic | ||
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# create a connection mapping | ||
def render_net(conmap, n=4, rand=12, depth=0, max_depth=5): | ||
thresh = 1e4 | ||
if depth<max_depth: | ||
nodes = list(conmap.keys()) | ||
np.random.seed(depth+1) | ||
np.random.shuffle(nodes) | ||
colors = dict(zip(nodes, [0]*len(nodes))) | ||
counter = dict(zip(nodes, [0]*len(nodes))) | ||
count = 0 | ||
while len(nodes)>0 and count<thresh: | ||
count+=1 | ||
k = nodes.pop(0) | ||
counter[k] += 1 | ||
hist = [1e4] + [0] * n | ||
for p in conmap[k]: | ||
hist[colors[p]] += 1 | ||
if min(hist)==0: | ||
colors[k] = hist.index(min(hist)) | ||
counter[k] = 0 | ||
continue | ||
hist[colors[k]] = 1e4 | ||
minc = hist.index(min(hist)) | ||
if counter[k]==rand: | ||
counter[k] = 0 | ||
np.random.seed(count) | ||
minc = np.random.randint(1,4) | ||
colors[k] = minc | ||
for p in conmap[k]: | ||
if colors[p] == minc: | ||
nodes.append(p) | ||
if count==thresh: | ||
print(n,'-color algorthm failed,trying again with',n+1,'colors. Depth',depth) | ||
colors = render_net(conmap,n+1,rand,depth+1,max_depth) | ||
return colors | ||
else: | ||
print('N-color algorthm exceeded max depth of',max_depth) | ||
return None | ||
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# Should work for 3D too. Could put into usigned integer form at the end... | ||
# Also could use some parallelization | ||
def format_labels(labels, clean=False, min_area=9): | ||
""" | ||
Puts labels into 'standard form', i.e. background=0 and cells 1,2,3,...,N-1,N. | ||
Optional clean flag: disconnect and disjoint masks and discard small masks beflow min_area. | ||
min_area default is 9px. | ||
""" | ||
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# Labels are stored as a part of a float array in Cellpose, so it must be cast back here. | ||
# some people also use -1 as background, so we must cast to the signed integar class. We | ||
# can safely assume no 2D or 3D image will have more than 2^31 cells. Finally, cv2 does not | ||
# play well with unsigned integers (saves to default uint8), so we cast to uint32. | ||
labels = labels.astype('int32') | ||
labels -= np.min(labels) | ||
labels = labels.astype('uint32') | ||
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# optional cleanup | ||
if clean: | ||
inds = np.unique(labels) | ||
for j in inds[inds>0]: | ||
mask = labels==j | ||
lbl = measure.label(mask) | ||
regions = measure.regionprops(lbl) | ||
regions.sort(key=lambda x: x.area, reverse=True) | ||
if len(regions) > 1: | ||
print('Warning - found mask with disjoint label.') | ||
for rg in regions[1:]: | ||
if rg.area <= min_area: | ||
labels[rg.coords[:,0], rg.coords[:,1]] = 0 | ||
print('secondary disjoint part smaller than min_area. Removing it.') | ||
else: | ||
print('secondary disjoint part bigger than min_area, relabeling. Area:',rg.area, | ||
'Label value:',np.unique(labels[rg.coords[:,0], rg.coords[:,1]])) | ||
labels[rg.coords[:,0], rg.coords[:,1]] = np.max(labels)+1 | ||
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rg0 = regions[0] | ||
if rg0.area <= min_area: | ||
labels[rg0.coords[:,0], rg0.coords[:,1]] = 0 | ||
print('Warning - found mask area less than', min_area) | ||
print('Removing it.') | ||
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fastremap.renumber(labels,in_place=True) # convenient to have unit increments from 1 to N cells | ||
labels = fastremap.refit(labels) # put into smaller data type if possible | ||
return labels |
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import setuptools | ||
from setuptools import setup | ||
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install_deps = ['numpy>=1.20.0', 'scipy', 'numba', | ||
'edt','fastremap','scikit-image'] | ||
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with open("README.md", "r") as fh: | ||
long_description = fh.read() | ||
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setup( | ||
name="ncolor", | ||
license="BSD", | ||
author="Kevin Cutler", | ||
author_email="kevinjohncutler@outlook.com", | ||
description="label matrix coloring algorithm", | ||
long_description=long_description, | ||
long_description_content_type="text/markdown", | ||
url="https://github.com/kevinjohncutler/ncolor", | ||
setup_requires=[ | ||
'pytest-runner', | ||
'setuptools_scm', | ||
], | ||
packages=setuptools.find_packages(), | ||
use_scm_version=True, | ||
install_requires = install_deps, | ||
# tests_require=[ | ||
# 'pytest' | ||
# ], | ||
include_package_data=True, | ||
classifiers=( | ||
"Programming Language :: Python :: 3", | ||
"License :: OSI Approved :: BSD License", | ||
"Operating System :: OS Independent", | ||
) | ||
) |