def color_normalization(template_image_path, color_norm_method):
"""
The function put all the color normalization methods together.
:param template_image_path: the template image for normalization
:type template_image_path: string
:param color_norm_method: the method for color normalization
:type color_norm_method: string
:return: color_normalizer. It is the initialized object for the
actual normalization.
:rtype: object
"""
template_image = staintools.read_image(template_image_path)
standardizer = staintools.LuminosityStandardizer.standardize(
template_image)
if color_norm_method == 'Reinhard':
color_normalizer = stainNorm_Reinhard.Normalizer()
color_normalizer.fit(standardizer)
elif color_norm_method == 'Macenko':
color_normalizer = stainNorm_Macenko.Normalizer()
color_normalizer.fit(standardizer)
elif color_norm_method == 'Vahadane':
color_normalizer = staintools.StainNormalizer(method='vahadane')
color_normalizer.fit(standardizer)
return color_normalizer
def colorN(img_path):
img = utils.read_image(img_path)
fit_img = utils.read_image('/cptjack/totem/zhaofeiyan/DataSet/data-ori/target.png')
n = stainNorm_Macenko.Normalizer()
n.fit(fit_img)
t_img = n.transform(img)
return t_img
def colorN(img):
# 染色标准化处理，选取目标图片target.png作为参考图，调用stainNorm_Macenko.Normalizer()方法
fit_img = utils.read_image(
'/cptjack/totem/zhaofeiyan/DataSet/data-ori/target.png')
n = stainNorm_Macenko.Normalizer()
n.fit(fit_img)
t_img = n.transform(img)
return t_img
def color_normalization(template_image_path, color_norm_method):
"""
The function put all the color normalization methods together.
:param string template_image_path: the path of the image used as a template
:param string color_norm_method: one of the three methods: vahadane, macenko, reinhard.
:return object
"""
template_image = staintools.read_image(template_image_path)
standardizer = staintools.LuminosityStandardizer.standardize(
template_image)
if color_norm_method == 'Reinhard':
color_normalizer = stainNorm_Reinhard.Normalizer()
color_normalizer.fit(standardizer)
elif color_norm_method == 'Macenko':
color_normalizer = stainNorm_Macenko.Normalizer()
color_normalizer.fit(standardizer)
elif color_norm_method == 'Vahadane':
color_normalizer = staintools.StainNormalizer(method='vahadane')
color_normalizer.fit(standardizer)
return color_normalizer
def Normalization(inputPath, outputPath, sampleImagePath, num_threads=8):
inputPathContent = os.listdir(inputPath)
normPathContent = os.listdir(outputPath)
remainlList = []
for i in inputPathContent:
if not i in normPathContent:
remainlList.append(i)
inputPathContent = [i for i in remainlList if not i.endswith('.bat')]
inputPathContent = [i for i in inputPathContent if not i.endswith('.txt')]
target = cv2.imread(sampleImagePath)
target = cv2.cvtColor(target, cv2.COLOR_BGR2RGB)
normalizer = stainNorm_Macenko.Normalizer()
normalizer.fit(target)
pool = ThreadPool(num_threads)
pool.map(Normalize_Main, inputPathContent)
pool.close()
pool.join()
import stain_utils as utils
import stainNorm_Macenko
import cv2
i3 = utils.read_image('./data/i3.png')
i2 = utils.read_image('./data/i2.png')
n = stainNorm_Macenko.Normalizer()
n.fit(i2)
out = n.transform(i3)
cv2.imwrite('ans1.jpg', out)
import stainNorm_Reinhard
import vahadane
import cv2 as cv
from os import listdir, mkdir
from os.path import isfile, join, isdir
# paths
source_path = "/home/fred/Projects/srt-cancer-img/pair-data/"
suffix = "frames/x40/"
save_path = "/home/fred/Projects/srt-cancer-img/pair-data/output/"
# normalizers
normalizer_rd = stainNorm_Reinhard.Normalizer()
normalizer_mk = stainNorm_Macenko.Normalizer()
normalizer_vd = vahadane.vahadane()
for dirname in listdir(source_path):
if 'A06' in dirname:
print("Processing directory ", dirname)
imgs = [f for f in listdir(join(source_path, dirname, suffix))]
for img in imgs[1:]:
source = stain_utils.read_image(
join(source_path, dirname, suffix, img))
target = stain_utils.read_image(
join(source_path, dirname.replace('A', 'H', 1), suffix,
img.replace('A', 'H', 1)))