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Why?

Compared to PIL and some other tiff related projects, this package is more for scientific imaging.

Features exposed from libtiff:

  1. responds to

    1. pixel bit depth

    2. number of channels

    3. compression scheme

  2. sequential and random access to frames in multi-frame tiff

  3. query length of multi-frame tiff

Open

from tiffreader import TiffReader
tif = TiffReader.open("file_path.tif")

Random Access

tif.seek(10)
frame = tif.read_current()  # gives a 2D numpy array

is equivalent to

frame = tif[10]

Sequential Access

example for an average image of the 10th to 20th frames:

tif.seek(10)
result = np.zeros(tif.shape, dtype=np.uint64)
for frame in zip(tif, range(10)):
    result += frame
result /= 10

Additionally

from tiffreader import save_tiff
array = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype=np.uint8)
save_tiff(array, "tif_path.tif")
tif.length  # length of multi-frame tiff stack
tif.shape   # shape of one frame
tiffinfo("tif_path.tif", ["width", "height"])  # wraps tiffinfo to query for additional tags

Metadata

Release files for tiffreader 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tiffreader 0.1.1
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Release files / tiffreader-0.1.1.tar.gz

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