Given two masks for the same file with matching cell IDs, find cells missing in the second mask.

find_missing_cells_from_paired_masks.py

import glob
import os
import pandas as pd
import numpy as np
import time
import skimage.io

pathIn = "Z:/Connor/Topacio_P2_AF/ashlar"
pathOut= "D:/julia/cell_filter/"

def compare_mask(path1, path2, out_filename):
    img1 = skimage.io.imread(path1)
    img2 = skimage.io.imread(path2)
    uni1 = np.unique(img1)
    uni2 = np.unique(img2)

    diff = set(uni1) - set(uni2)
    diff = np.array(list(diff)).astype('int')
    np.savetxt(out_filename, diff, delimiter=',')

os.chdir(pathIn)
cytoFiles = [filename for filename in glob.iglob('C0*/**/cytoRingMask.tif', recursive=True)]
nucleiFiles = [filename for filename in glob.iglob('C0*/**/nucleiRingMask.tif', recursive=True)]
out_filenames = [i.split('\\')[0] + '_mask_diff.csv' for i in cytoFiles]

if len(cytoFiles) != len(nucleiFiles): print("Masks missing")

for i in range(len(cytoFiles)):
    print(out_filenames[i],)
    t = time.time()
    path1 = nucleiFiles[i]
    path2 = cytoFiles[i]
    compare_mask(path1, path2, pathOut + out_filenames[i])
    timeInterval = time.time() - t
    print(i, "-", out_filenames[i], "\tElapsed time: ",timeInterval, " seconds.\n")