comparison projective_transformation.py @ 3:be9a815e2240 draft

"planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit ee372547082b693ef1bbe10b5b7ea8660b9779df"

2:1ffdb07020ee

See file LICENSE for detail or copy at https://opensource.org/licenses/MIT

"""

import argparse
import imghdr
import warnings

import numpy as np
import pandas as pd
import skimage.color

def transform(moving_fn, fixed_fn, warp_mat, output_fn):

    moving = skimage.io.imread(moving_fn)
    extension = imghdr.what(moving_fn)
    nDims = len(moving.shape)
    assert nDims in [2, 3, 4, 5, 6], 'this tool only supports up to 6 dimensions'

    if moving.shape[-1] in [3, 4] and nDims > 2:
        isRGB = True

        warped_moving = map_coordinates(moving, warped_coords, cval=0)

    with warnings.catch_warnings():
        warnings.simplefilter("ignore")
        if isMulCh:
            tifffile.imwrite(output_fn + '.tif', warped_moving, imagej=True, metadata={'mode': 'composite'})
        else:
            skimage.io.imsave(output_fn + '.' + extension, warped_moving)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Transform the image")
    parser.add_argument("fixed_image", help="Path to the fixed image")

3:be9a815e2240

See file LICENSE for detail or copy at https://opensource.org/licenses/MIT

"""

import argparse
import warnings

import numpy as np
import pandas as pd
import skimage.color

def transform(moving_fn, fixed_fn, warp_mat, output_fn):

    moving = skimage.io.imread(moving_fn)
    nDims = len(moving.shape)
    assert nDims in [2, 3, 4, 5, 6], 'this tool only supports up to 6 dimensions'

    if moving.shape[-1] in [3, 4] and nDims > 2:
        isRGB = True

        warped_moving = map_coordinates(moving, warped_coords, cval=0)

    with warnings.catch_warnings():
        warnings.simplefilter("ignore")
        if isMulCh:
            tifffile.imwrite(output_fn, warped_moving, imagej=True, metadata={'mode': 'composite'})
        else:
            skimage.io.imsave(output_fn, warped_moving)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Transform the image")
    parser.add_argument("fixed_image", help="Path to the fixed image")