将带有 skimage 的非 RGBA 4-tile 多页 tiff 图像加载到 dask 数组中

Question

我需要阅读一个包含由 Suite2p 神经生物学包生成的多页 tiff 的文件夹。从 Suite2p 源代码中，多重 tiff 创建如下：

import numpy as np
from tifffile import TiffWriter

# fake example images
img_5_tiles = np.random.randint(0,65535,(5,10,20), dtype='uint16')
img_4_tiles = img_5_tiles[1:,...]

# save fake images
with TiffWriter(r'D:tiles.tiff') as tif:
    for frame in img_5_tiles:
        tif.save(frame)

with TiffWriter(r'D:tiles.tiff') as tif:
    for frame in img_4_tiles:
        tif.save(frame)

当我尝试将它们读入 dask 时，skimage.io 默认的 tifffile 插件无法获得正确的形状：

from dask.array.image import imread
from skimage import io

def read_with_tifffile(path):
    return io.imread(path, plugin='tifffile')

# should produce (5,10,20) instead of (1,10,20)
imread(r'D:tiles.tiff', imread=read_with_tifffile).shape

我可以通过使用非默认 skimage.io.imread 插件 'pil'

来克服这个问题

def read_with_pil(path):
    return io.imread(path, plugin='pil', mode='L')

# gives (1,5,10,20) which is acceptable
imread(r'D:tiles.tiff', imread=read_with_pil).shape

不幸的是，如果图块数等于 4，skimage 开始以不同方式处理形状：

# gives (1,10,20,4) instead of (1,4,10,20)
imread(r'D:tiles.tiff', imread=read_with_pil).shape

通过阅读 skimage 文档，它可能试图将我的图像解释为 RGBA，然后失败了。是否有强制 'uint16' 多页读取所有图像形状的解决方案？

如有任何建议，我们将不胜感激！

Answer 1

基于cgohlke的评论：

from dask.array.image import imread
import numpy as np
from skimage import io
import tifffile

# fake data
img_with_4_tiles = np.random.randint(0,65535,(4,10,20), dtype='uint16')

with tifffile.TiffWriter(r'D:tiles.tiff') as tif:
    for frame in img_with_4_tiles:
        tif.save(frame)
        
# my original bad solution
def read_with_pil(path):
    return io.imread(path, plugin='pil', mode='L')

print(imread(r'D:tiles.tiff', imread=read_with_pil).shape)

# a good solution from the horse's mouth (https://pypi.org/user/cgohlke/)
def read_with_tifffile(path):
    return tifffile.imread(path, is_shaped=False)

print(imread(r'D:tiles.tiff', imread=read_with_tifffile).shape)

将带有 skimage 的非 RGBA 4-tile 多页 tiff 图像加载到 dask 数组中

Loading non RGBA 4-tile multi page tiff images with skimage into dask array

python

python-imaging-library

scikit-image

dask