Blob detection based on laplacian-of-gaussian, to detect localized bright foci in an image. This is similar to the method used in scikit-image but extended to nD arrays and .tif images.
blob.py is installed as the primary entry point to output blob locations in
human- and machine-readable formats. It takes a grayscale TIFF image and prints
out blob coordinates in CSV format, for example:
> blob find my_image.tif
...
661 309
768 309
382 311
...
For convenience, a plotting function is also provided: blob plot image.tif peaks.csv.
demo.py is provided in the source repository to give a visual example using
the Hubble Deep Field image (from scikit-image) as sample data.
The common options to blob find are documented below:
--threshold THRESHOLD: The minimum filter response (proportional to intensity) required to detect a blob.--size LOW HIGH: The range of scales to search. The filter response will be strongest when the size of the spot matches the size of the filter.
The --help option provides details of all available options.
No installation is required, blob.py functions as a self-contained executable.
If desired, it can be installed as the executable blob, using setup.py,
detailed description of installation options can be found in the
official documentation.
Python 3, Scipy, Numpy and tifffile. All
are available from PyPI and can be installed as described in the
pip documentation. If necessary, a more up-to-date installer for
tifffile is maintained here.
The demo script additionally requires matplotlib, which is also available through PyPI.
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