Small Particle Detection, a shapes library-based object detector.
SPADE: Small PArticle DEtection
An algorithm primarily design to detect objects whose sizes aren’t larger a few pixels (particles) on fluorescence microscopy images.
It is an simplified version of marked point process.
SPADE has only been tested with Python 3.5 but should work with older versions. The only strict requirement is the package numpy. In order to use SPADE to its full extent, we recommend installing the scikit-image package and the full scipy ecosystem.
In a python script
You can install the package using PIP. The main function, spade2d, is in the spade.detection_2d module. It takes an image, a shapes library and a threshold as input. A typical usage would look like like
from skimage.io import imread, imshow from skimage.filters import threshold_otsu from skimage.color import label2rgb from numpy import percentile import matplotlib.pyplot as plt from spade.detection_2d import spade2d from spade.shapes.examples import potatoids5x5_smallest4px # Load the example image. image = imread("example_2d.png") # Separate cell image from background, using by Otsu's thresholding method. cell = image > threshold_otsu(image) # Focus on brightest pixels only potential_centers = image > percentile(image[cell], 99) # Detect particles. particles = spade2d(image=image, shapes_library=potatoids5x5_smallest4px, threshold=20, potential_centers=potential_centers, mask=cell) # Show detected particles as overlay on our original image. imshow(label2rgb(particles, image, bg_label=0)) plt.show()
See the examples in the example folder of the source dist for more information. Note that matplotlib and skimage are not required for SPADE to work.
From the command line
Also provided is a command line interface, that can be used as following:
python -m spade.cli INPUT_IMAGE THRESHOLD -o /path/to/output_image.png
Launch this command with -h for more information on its usage.
SPADE is released under the CeCILL-2.1 licence.
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