comparison auto_local_threshold.py @ 1:c90b91f4a07b draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/2d_auto_local_threshold/ commit 8a2a5763d1ac38b3c7974bd7c2da4d5c1101a0a9

0:a20c14eb5f98

import argparse
import sys
import skimage.io
import skimage.filters
import skimage.util

threshOptions = {
    'gaussian': lambda img_raw, bz: skimage.filters.threshold_local(img_raw, bz, method='gaussian'),
    'mean': lambda img_raw, bz: skimage.filters.threshold_local(img_raw, bz, method='mean'),
    'median': lambda img_raw, bz: skimage.filters.threshold_local(img_raw, bz, method='median')

    parser.add_argument('thresh_type', choices=threshOptions.keys(), help='thresholding method')
    parser.add_argument('dark_background', default=True, type=bool, help='True if background is dark')
    args = parser.parse_args()

    img_in = skimage.io.imread(args.input_file.name)
    thresh = threshOptions[args.thresh_type](img_in, args.block_size)

    if args.dark_background:
        res = img_in > thresh
    else:

1:c90b91f4a07b

import argparse
import sys
import skimage.io
import skimage.filters
import skimage.util
import numpy as np

threshOptions = {
    'gaussian': lambda img_raw, bz: skimage.filters.threshold_local(img_raw, bz, method='gaussian'),
    'mean': lambda img_raw, bz: skimage.filters.threshold_local(img_raw, bz, method='mean'),
    'median': lambda img_raw, bz: skimage.filters.threshold_local(img_raw, bz, method='median')

    parser.add_argument('thresh_type', choices=threshOptions.keys(), help='thresholding method')
    parser.add_argument('dark_background', default=True, type=bool, help='True if background is dark')
    args = parser.parse_args()

    img_in = skimage.io.imread(args.input_file.name)
    img_in = np.reshape(img_in, [img_in.shape[0], img_in.shape[1]])
    thresh = threshOptions[args.thresh_type](img_in, args.block_size)

    if args.dark_background:
        res = img_in > thresh
    else: