Documentation
¶
Overview ¶
*
- This is probably the most important package in the repository. It contains
- all the segmentation algorithms and the utilities to transform from an
- image to a graph and from a DisjointSet forest to an image.
Index ¶
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
Types ¶
type ImageColor ¶
type ImageColor struct {
// contains filtered or unexported fields
}
*
- Color type that implements color.RGBA
type Segmenter ¶
type Segmenter struct {
// contains filtered or unexported fields
}
*
- Type used to run all the segmentation algorithms.
- It stores the graph, the resultset, the original image, the graph
- obtained from the image and if it will generate a result image with
- random colors.
func New ¶
*
- Returns a new Segmenter, generates a graph of the given graph type from
- the given image using the given weight function to compute the edge
- weights.
func (*Segmenter) GetResultImage ¶
*
- Returns the result image. Returns nil if no segmentation algorithm
- has been executed before.
func (*Segmenter) SegmentGBS ¶
*
- Performs the image segmentation using the "Graph Based Segmentation"
- algorithm. It uses sigma to apply a gaussian filter with it to the image
- to smooth it before running the algorithm.
- k and minSize are the algorithm parameters. For more information on this
- algorithm refer to either my report which link is on the repo's README or
- to: http://cs.brown.edu/~pff/papers/seg-ijcv.pdf
func (*Segmenter) SegmentHMSF ¶
*
- Performs the image segmentation using the "Heuristic for Minimum Spanning
- Forests" algorithm. It uses the weightfn to compute the weight of the
- graph edges. minWeight is the only parameter.
- For more information on this algorithm refer to either my report which link
- is on the repo's README or to:
- http://algo2.iti.kit.edu/wassenberg/wassenberg09parallelSegmentation.pdf
func (*Segmenter) SetRandomColors ¶
*
- Sets the random color attribute to true or false according to val
Source Files
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