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- [input]
- path=data/Image0.tif
- scale=2
- num_images=1
- # Define matrix_size to determines the number of surrounding pixels to # be
- # compared with, ideally make this number uneven # Being twice the size of the
- # actual ring thickness tends to be good
- matrix_size=26
- # Whether or not to remove high intensity pixels
- remove_high_intensity_pixels=false
- [output]
- dump_ring_to_image=false
- [ring]
- start=10
- end=130
- step=2
- # Giving thickness of rpiv.ing NOTE if rings raddi apiv.nd thickness are too
- # big, you will get errors from the gpu saying CL_piv.INVALID_WORK_GROUP_SIZE
- thickness=6
- # Set the maximum number of rings that should detected per ring pattern, if the
- # number of found rings is greater than max_count, then the output is ignored
- max_count=100
- # Should be the same dimension as input image
- width=1080
- height=1280
- [filter]
- # When images maximum is less than min ignore output. Min is the likelyness
- # value for a pixel to be the center of a ring and ranges from 0 to 1
- min=0.125
- # Consider only pixels that are above 0.8 * max when searching for clusters of
- # pixels. Where max, is the highest intensity in the image
- threshold=0.8
- [dup]
- # Set minumum distance between rings, and how close two different radius are
- # considerend to be same ring
- threshold=8.0
- [remove]
- # Up to what radii difference is a ring considered an inner or outer ring of two
- # intersecting rings
- threshold=4.0
- [radii]
- # Vary up from -radii_range to randii_range the radius to find the polynomial
- # that corresponds to the rings contrast
- range=6
- # Set the minimum contrast a ring should have to be considered a ring
- threshold=0.01
- # By how much may the ring center be displaced to find it's actual center and
- # it's actual radius
- displacement=1
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