arrayfire / arrayfire/arrayfire-python

Does af.regions work on 3D image input?

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Dominant language
Python
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Description

From the documentation it appears as though the method is designed to work in 2D only:
`def regions(image, conn = CONNECTIVITY.FOUR, out_type = Dtype.f32):
"""
Find the connected components in the image.

Parameters
----------
image : af.Array
- A 2 D arrayfire array representing an image.

conn : optional: af.CONNECTIVITY. default: af.CONNECTIVITY.FOUR.
- Specifies the connectivity of the pixels.

out_type : optional: af.Dtype. default: af.Dtype.f32.
- Specifies the type for the output.

Returns
---------

output : af.Array
- An array where each pixel is labeled with its component number.

"""
output = Array()
safe_call(backend.get().af_regions(c_pointer(output.arr), image.arr,
conn.value, out_type.value))
return output`

Contributor guide

No contributing guide indexed for this repository

Research direction

Start at the af.regions entry point and compare its documented 2D input description with the underlying ArrayFire af_regions behavior for 3D arrays. Verify the behavior with a minimal 3D input, then update the documentation to state the supported dimensionality and expected connectivity semantics.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
computer-vision
Issue type
Documentation
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
35/100

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