def main(path_images, level=DEFAULT_LEVEL, overwrite=False, nb_jobs=1):
paths_img = sorted(glob.glob(path_images))
_wrap_convert = partial(convert_image, level=level, overwrite=overwrite)
list(
wrap_execute_sequence(_wrap_convert,
paths_img,
desc='converting images',
nb_jobs=nb_jobs))
def main(path_images, scales, overwrite, nb_jobs):
image_paths = sorted(glob.glob(path_images))
image_path_scales = [(im_path, sc) for im_path in image_paths
for sc in scales]
if not image_paths:
logging.info('No images found on "%s"', path_images)
return
_wrap_scale = partial(wrap_scale_image, overwrite=overwrite)
list(wrap_execute_sequence(_wrap_scale, image_path_scales,
desc='Scaling images', nb_jobs=nb_jobs))
def main(path_images, padding, nb_jobs):
image_paths = sorted(glob.glob(path_images))
if not image_paths:
logging.info('No images found on "%s"', path_images)
return
_wrap_crop = partial(wrap_img_crop, padding=padding)
list(
wrap_execute_sequence(_wrap_crop,
image_paths,
desc='Crop image tissue',
nb_jobs=nb_jobs))
def main(path_images, cut_dim, overwrite, nb_jobs):
image_paths = sorted(glob.glob(path_images))
if not image_paths:
logging.info('No images found on "%s"', path_images)
return
_wrap_split = partial(split_image, cut_dim=cut_dim, overwrite=overwrite)
list(
wrap_execute_sequence(_wrap_split,
image_paths,
desc='Cut image tissues',
nb_jobs=nb_jobs))