visualise the 3D segmentation result
- The most convenient way would be:
pip install segview
- You can also Include the file
segview.py
in your project directory
segview.render_label(label, metadata, alpha=1) # see the 3D model of labels
segview.annotate_label(image, label, axis=-1) # see the 2D slice with labels along different axes
segview.render_image(image, metadata) # see the 3D render of an image
segview.render_image(image, metadata, feature) # see the 3D image with features
segview.annotate_feature(image, feature) # see 2D slice with features
label
is a 3Dnumpy
array- Usually it is the result of image segmentation, having the same structure
- Value
0
corresponds to the background - Its shape is
(x, y, z)
.
feature
is a 2Dnumpy
array- Usually it is the result of intensity maxima locating
- It is 3D positions,
[(x1, y1, z1), (x2, y2, z2), ...]
- Its shape is
(feature_number, 3)
metadata
is a dictionary containing the voxel size- It is only used in 3D visualisation, as many z-stack images have lower resolutions along z-axis
{'voxel_size_x': 1, 'voxel_size_y': 1, 'voxel_size_z': 1}
alpha
adjusts the brightness of the result