arrayfire / arrayfire/arrayfire-python
Does af.regions work on 3D image input?
- 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