Fiji script for protein detection

from ij import IJ, ImagePlus
from ij.process import FloatProcessor
from array import zeros


def box_maker(radius):
    box = []
    for i in range(2*radius):
        y = []
        for j in range(2*radius):
            y.append(0)
        box.append(y)

    box[4][4] = 1
    box[4][3] = 1
    box[3][4] = 1
    box[5][4] = 1
    box[4][5] = 1
    return box

def config_img(imp):
    pix = list(imp.getProcessor().getPixels())
    w = imp.getWidth()
    h = imp.getHeight()
    new_im = []

    for i in range(h):
        y = []
        for j in range(w):
            y.append(pix[i*h+j])
        new_im.append(y)

    return new_im

def protein_find(pix, y, x, boxcent, boxedge):
    centsum = 0.0
    for boxx, boxy in boxcent:
        centsum += pix[y + boxy][x + boxx]
    centavg = centsum/5

    edgesum = 0.0
    for boxx, boxy in boxedge:
        edgesum += pix[y + boxy][x + boxx]
    edgeavg = edgesum/36

    if centavg/edgeavg > 2.0:
        return x, y
    else:
        return 0, 0



radius = 5

box = box_maker(radius)
imp = IJ.getImage()
h = imp.getHeight()
w = imp.getWidth()
IJ.run("16-bit")

#------------------------------------------------
#Adaptive Histogram Equalisation
blocksize = '127'
histogram_bins = '256'
maximum_slope = '3'
mask = "*None*"
fast = True
process_as_composite = True

parameters = "blocksize =" + blocksize + " histogram=" + histogram_bins + \
    " maximum=" + maximum_slope + " mask=" + mask
if fast:
  parameters += " fast_(less_accurate)"

IJ.run( "Enhance Local Contrast (CLAHE)", parameters )

#------------------------------------------------

IJ.run("Subtract Background...", "rolling=10")
new_pix = config_img(imp)


boxcent = [[4, 4], [3, 4], [4, 3], [5, 4], [4,5]]
boxedge = [[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [0, 9],
[1, 0], [1, 9], [2, 0], [2, 9], [3, 0], [3, 9], [4, 0], [4, 9], [5, 0], [5, 9], [6, 0], [6, 9],
[7, 0], [7, 9], [8, 0], [8, 9], [9, 0], [9, 1], [9, 2], [9, 3], [9, 4], [9, 5], [9, 6], [9, 7],
[9, 8], [9, 9]]

prots = []
counts = 0
for i in range(h):
    for j in range(w):
        if (i > 0 + radius) and (i < h - 2*radius) and (j > 0 + radius) and (j < w - 2*radius):
            outx, outy = protein_find(new_pix, i, j, boxcent, boxedge)
            if outx != 0:
                prots.append([i, j])
                counts +=1




pix2 = zeros('f', w * h)

for i in range(len(prots)):
    x, y = prots[i]
    pix2[x*h+y] = 1.0

fp = FloatProcessor(imp.getWidth(), imp.getHeight(), pix2, None)
imp3 = ImagePlus("prots", fp)
imp3.show()
print counts