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After you've taken images of your fibre slides, they need to be preprocessed before feeding to the model.
The preprocessing stage does three steps:
- re-orient the image so that it appears perfectly flat
- snip out the large black rectangular section
- convert the image to black-and-white, emphasising all pixels that are of a particular hue range - highlighting your fluorescent fibres.
After converting your images into
$ source activate fluorescent-fibre-counting $ python -m preprocess <directory containing your images> <directory you want to store preprocessed images in>
Calibrating hue ranges for your fibres
The default calibration expects green fluorescent fibres. If you have a different colour - or shade - you want to count, then use the
--max-hue options for
python -m preprocess. The hue values range from 0. to 1..