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Game-theoretic integration of image segmentation methods, implemented in Python.
Hey! The project seems to be superb and really impactful! I want to use this library in my own project. I'd love to have it imported into my project as a normal python library
import gt_im_s
gts = gt_im_s.load_config("default_config.yaml")
mask = gts.generate_mask(image)
Where the default_config.yaml
file contains all the needed configs to run the mask generator, the input image
is a numpy.ndarray
with shape for example (100, 150, 3)
which are the image dimensions and the three RGB canals, and the output mask
is a similarly (100,150)
shaped numpy.ndarray
which contains 0
or 1
(or eventually 255
) values that correspond to the mask itself. If so, what the default_config.yaml
should contain to work correctly on for example this image?
import gt_im_s
gts = gt_im_s.load_config("default_config.yaml")
image_without_hair = gts.remove_hair(image)
Where all the things are the same as previously and the image_without_hair
is a numpy.ndarray
with the (100, 150, 3)
shape and the same structure as the input image
I'd love to have it working like this. If not, how can I make this project work smoothly and similarly to the two flows mentioned above?
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