BIPL is a Big Image Python Library
Library to read big pyramidal images like in formats like BigTiff, Aperio SVS, Leica MRXS.
bipl.Slide - ndarray-like reader for multiscale images (svs, tiff, etc...)
import numpy as np
from bipl import Slide
slide = Slide.open('test.svs')
shape: tuple[int, ...] = slide.shape # Native shape
downsamples: tuple[int, ...] = slide.downsamples # List of pre-existing sub-resolution levels
# Get native miniature
tmb: np.ndarray = slide.thumbnail()
mpp: float = slide.mpp # X um per pixel, native resolution
image: np.ndarray = slide[:2048, :2048] # Get numpy.ndarray of 2048x2048 from full resolution
MPP = 16. # Let's say we want slide at 16 um/px resolution
downsample = MPP / slide.mpp
mini = slide.pool(downsample) # Gives `downsample`-times smaller image
mini = slide.resample(MPP) # Gives the same result
# Those ones trigger ndarray conversion
image: np.ndarray
image = mini[:512, :512] # Take a part of
image = mini.numpy() # Take a whole resolution level
image = np.array(mini, copy=False) # Use __array__ API
bipl.Mosaic - apply function for each tile of big image on desired scale.
import numpy as np
from bipl import Mosaic, Slide
m = Mosaic(step=512, overlap=0) # Read at [0:512], [512:1024], ...
# Open slide at 1:1 scale
s = Slide.open('test.svs')
# Target at 4 um/px resolution
# If `test.svs` has some pyramid in it (i.e. 1:1, 1:4, 1:16), it will be used to speed up reads.
s4 = s.resample(mpp=4.0)
# Get iterator over tiles.
# Reads will be at [0:512], [512:1024] ... @ MPP
tiles = m.iterate(s4)
# Read only subset of tiles according to binary mask (1s are read, 0s are not).
# `s4.shape * scale = mask.shape`, `scale <= 1`
tiles = tiles.select(mask, scale)
# Read all data, trigger I/O. All the previous calls do not trigger any disk reads beyond metadata.
images: list[np.ndarray] = [*tiles]
Installation
pip install bipl
BIPL is compatible with: Python 3.13+. Tested on Ubuntu & Windows.
DeepZoom server
To start use:
pip install bipl[deepzoom]
export SLIDES=~/slides
uvicorn bipl.dzi:app --workers 4 --host 0.0.0.0 --port 8000
Or you can just use a router from there:
from bipl.dzi import router
your_fastapi_app.include_router(router)
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