Root_Processing/rootprocessing/RP_crop.py at master · kdecarlo/Root_Processing · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
import numpy as np
import time
import scipy.ndimage as imp
import datetime

from scipy import ndimage
from skimage.morphology import skeletonize
import scipy.misc
from scipy.signal import medfilt
from PIL import Image
import os

from rootprocessing.RP_timerstart import RP_timerstart
from rootprocessing.RP_timerprogress import RP_timerprogress
from rootprocessing.RP_timerend import RP_timerend

def RP_crop(parameters):
    '''
    SUMMARY:
    'RP_crop': crops image.

    USING CODE:
    Using values in 'cropvals' (start row, end row, start col, end col), image is
    cropped down.  Note that row and col values correspond to x/y positions in ImageJ.

    PARAMETERS:
    1. image_filename: filename of evaluated image.
    2. output_filename: filename where image is to be saved.
    3. cropvals: 4x1 array specifying crop range - (1) start row, (2) end row,
    (3) start column, (4) end column.

    SAMPLE INPUT:
    ctype = 'Chamber2'
    wd_filename = '/Volumes/Untitled 2/rhizosphere'
    image_filename = wd_filename+'/stitched/'+ctype+'_stitched.fits'
    output_filename = wd_filename+'/morph_mask_crop/'+ctype+'_stitched_crop.fits'
    cropmat = [96,2848,1248,6384]
    '''

    starttime = time.time()
    scriptname = 'crop'
    RP_timerstart(scriptname)


    image_filename = parameters['image_filename']
    output_filename = parameters['output_filename']
    cropmat = parameters['cropmat']

    IO_mask = os.path.isfile(image_filename)
    if IO_mask is not True:
        raise ValueError('mask file not found.  Please re-check input files.')

    mask = Image.open(image_filename)

    mask = np.array(mask)

    imdim = np.shape(mask)

    if (cropmat[0] > imdim[0]) or (cropmat[1] > imdim[0]) or (cropmat[2] > imdim[1]) or (cropmat[3] > imdim[1]):
        raise ValueError('Crop values exceed image size.  Please re-check values in user_config file.')


    if np.sum(cropmat) == 0:
        cropmat = [0, imdim[0], 0, imdim[1]]
        y = cropmat[0:2]
        x = cropmat[2:4]
    else:
        y = cropmat[0:2]
        x = cropmat[2:4]


    #mask = mask[int(imdim[0]-y[1]):int(imdim[0]-y[0]+1),int(x[0]):int(x[1]+1)]
    mask = mask[int(y[0]):int(y[1]), int(x[0]):int(x[1])]
    mask = Image.fromarray(mask)
    mask.save(output_filename)

    RP_timerend(starttime)

    #scipy.misc.imsave(output_filename, mask)