arrayfire / arrayfire/arrayfire-python

Does af.regions work on 3D image input?

未关闭
#264 3 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看
主要语言
Python
星标
422
派生
63
PR 合并指标
30 天内没有已合并 PR

描述

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`

贡献指南

这个仓库没有索引到贡献指南

调研方向

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.

由索引模型根据 Issue 内容生成。

评估

技术栈
python
领域
computer-vision
Issue 类型
文档
难度
3/5
预计耗时
1-2 天
活跃度
停滞
描述清晰度
需要澄清
新手友好度
35/100

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。