Source code for csbdeep.data.rawdata

# -*- coding: utf-8 -*-
from __future__ import print_function, unicode_literals, absolute_import, division
from six.moves import zip
from tifffile import imread
from collections import namedtuple
from itertools import chain

from ..utils import _raise, consume, axes_check_and_normalize
from ..utils.six import Path, FileNotFoundError



[docs]class RawData(namedtuple('RawData' ,('generator' ,'size' ,'description'))): """:func:`collections.namedtuple` with three fields: `generator`, `size`, and `description`. Parameters ---------- generator : function Function without arguments that returns a generator that yields tuples `(x,y,axes,mask)`, where `x` is a source image (e.g., with low SNR) with `y` being the corresponding target image (e.g., with high SNR); `mask` can either be `None` or a boolean array that denotes which pixels are eligible to extracted in :func:`create_patches`. Note that `x`, `y`, and `mask` must all be of type :class:`numpy.ndarray` and are assumed to have the same shape, where the string `axes` indicates the order and presence of axes of all three arrays. size : int Number of tuples that the `generator` will yield. description : str Textual description of the raw data. """
[docs] @staticmethod def from_folder(basepath, source_dirs, target_dir, axes='CZYX', pattern='*.tif*'): """Get pairs of corresponding TIFF images read from folders. Two images correspond to each other if they have the same file name, but are located in different folders. Parameters ---------- basepath : str Base folder that contains sub-folders with images. source_dirs : list or tuple List of folder names relative to `basepath` that contain the source images (e.g., with low SNR). target_dir : str Folder name relative to `basepath` that contains the target images (e.g., with high SNR). axes : str Semantics of axes of loaded images (assumed to be the same for all images). pattern : str Glob-style pattern to match the desired TIFF images. Returns ------- RawData :obj:`RawData` object, whose `generator` is used to yield all matching TIFF pairs. The generator will return a tuple `(x,y,axes,mask)`, where `x` is from `source_dirs` and `y` is the corresponding image from the `target_dir`; `mask` is set to `None`. Raises ------ FileNotFoundError If an image found in a `source_dir` does not exist in `target_dir`. Example -------- >>> !tree data data ├── GT │ ├── imageA.tif │ ├── imageB.tif │ └── imageC.tif ├── source1 │ ├── imageA.tif │ └── imageB.tif └── source2 ├── imageA.tif └── imageC.tif >>> data = RawData.from_folder(basepath='data', source_dirs=['source1','source2'], target_dir='GT', axes='YX') >>> n_images = data.size >>> for source_x, target_y, axes, mask in data.generator(): ... pass """ p = Path(basepath) pairs = [(f, p/target_dir/f.name) for f in chain(*((p/source_dir).glob(pattern) for source_dir in source_dirs))] len(pairs) > 0 or _raise(FileNotFoundError("Didn't find any images.")) consume(t.exists() or _raise(FileNotFoundError(t)) for s,t in pairs) axes = axes_check_and_normalize(axes) n_images = len(pairs) description = "{p}: target='{o}', sources={s}, axes='{a}', pattern='{pt}'".format(p=basepath, s=list(source_dirs), o=target_dir, a=axes, pt=pattern) def _gen(): for fx, fy in pairs: x, y = imread(str(fx)), imread(str(fy)) len(axes) >= x.ndim or _raise(ValueError()) yield x, y, axes[-x.ndim:], None return RawData(_gen, n_images, description)
[docs] @staticmethod def from_arrays(X, Y, axes='CZYX'): """Get pairs of corresponding images from numpy arrays.""" def _gen(): for x, y in zip(X ,Y): len(axes) >= x.ndim or _raise(ValueError()) yield x, y, axes[-x.ndim:], None return RawData(_gen, len(X), "numpy array")