arrayfire / arrayfire/arrayfire-python
Does af.regions work on 3D image input?
- Dominant language
- Python
- Stars
- 422
- Forks
- 63
- PR merge metrics
- No merged PRs in 30d
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
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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