/
get_segimg.py
133 lines (126 loc) · 4.37 KB
/
get_segimg.py
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import cv2
import pickle
import numpy as np
import copy
import hashlib
import os
from os.path import join
_COLORS = np.array(
[
0.000, 0.447, 0.741,
0.850, 0.325, 0.098,
0.929, 0.694, 0.125,
0.494, 0.184, 0.556,
0.466, 0.674, 0.188,
0.301, 0.745, 0.933,
0.635, 0.078, 0.184,
1.000, 0.000, 0.000,
1.000, 0.500, 0.000,
0.749, 0.749, 0.000,
0.000, 1.000, 0.000,
0.000, 0.000, 1.000,
0.667, 0.000, 1.000,
0.333, 0.667, 0.000,
0.333, 1.000, 0.000,
0.667, 0.333, 0.000,
0.667, 0.667, 0.000,
0.667, 1.000, 0.000,
1.000, 0.333, 0.000,
1.000, 0.667, 0.000,
1.000, 1.000, 0.000,
0.000, 0.667, 0.500,
0.000, 1.000, 0.500,
0.333, 0.000, 0.500,
0.333, 0.667, 0.500,
0.333, 1.000, 0.500,
0.667, 0.000, 0.500,
0.667, 0.333, 0.500,
0.667, 1.000, 0.500,
1.000, 0.000, 0.500,
1.000, 0.333, 0.500,
1.000, 0.667, 0.500,
1.000, 1.000, 0.500,
0.000, 0.333, 1.000,
0.000, 0.667, 1.000,
0.000, 1.000, 1.000,
0.333, 0.000, 1.000,
0.333, 0.333, 1.000,
0.333, 0.667, 1.000,
0.333, 1.000, 1.000,
0.667, 0.000, 1.000,
0.667, 0.333, 1.000,
0.667, 0.667, 1.000,
0.667, 1.000, 1.000,
1.000, 0.000, 1.000,
1.000, 0.333, 1.000,
1.000, 0.667, 1.000,
0.667, 0.000, 0.000,
0.833, 0.000, 0.000,
1.000, 0.000, 0.000,
0.000, 0.667, 0.000,
0.000, 0.833, 0.000,
0.000, 0.000, 0.667,
0.000, 0.000, 0.833,
0.000, 0.000, 1.000,
]
).astype(np.float32).reshape(-1, 3)
def __add_all_masks(image, masks, color):
mask_image = copy.deepcopy(image)
for i in range(len(masks)):
for (a,b) in masks[i]:
mask_image[a,b,:] = mask_image[a,b,:]*0.5 + color[i]*255*0.5
return mask_image
def get_segimg(im_file, result_file, output_file):
image = cv2.imread(im_file)
with open(result_file, 'rb') as dbfile:
result = pickle.load(dbfile)
masks = result['masks']
assigned_colors = [_COLORS[int(hashlib.sha256(str(masks[i]).encode('utf-8')).hexdigest(), 16) % 55] for i in range(len(masks))]
segimage = __add_all_masks(image, masks, assigned_colors)
cv2.imwrite(output_file, segimage)
def get_cellcount(result_file):
with open(result_file, 'rb') as dbfile:
result = pickle.load(dbfile)
return len(result['masks'])
'''
# get new segmentation images:
input_path = '/Users/ed/Documents/UM/NN_outs/qc_check'
for f in os.listdir(input_path):
age_folder = os.path.join(input_path, f)
for im in os.listdir(age_folder):
if im[-1] == 'g':
print(im)
qcname = 'qc' + str(im[0:(len(im)-4)]) + '.result'
result_file = os.path.join(age_folder, qcname) # find result here (maybe from "age_foler" & "im").
output_file = os.path.join(im, '_qc.png') # change this
get_segimg(im, result_file, output_file)
#get cell count:
count_file = '/Users/ed/Documents/UM/NN_outs/qc_check/qc_check.txt'
input_path = '/Users/ed/Documents/UM/NN_outs/qc_check'
for f in os.listdir(input_path):
age_folder = os.path.join(input_path, f)
for result in os.listdir(age_folder):
if im[-1] == 'g':
count = get_cellcount(result)
with open(count_file, 'w') as f:
f.write(im + str(count) +'\n')
'''
count_file = '/Users/ed/Documents/UM/NN_outs/qc_check.txt'
input_path = '/Users/ed/Documents/UM/NN_outs/qc_check'
for f in os.listdir(input_path):
if f.startswith('.'):
print(f)
else:
age_folder = join(input_path, f)
for im in os.listdir(age_folder):
if im.startswith('.'):
print(im)
elif im[-1] == 'g':
print(im)
result_file = join(age_folder, 'Prediction/qc' + im[0:-3] + 'result') # find result here (maybe from "age_foler" & "im").
output_file = join(age_folder, 'Prediction/qc' + im) # change this
get_segimg(join(age_folder, im), result_file, output_file)
count = get_cellcount(result_file)
with open(count_file, 'a+') as f:
print(count)
f.write('qc' + im + ': ' + str(count) +'\n')