Attributes

params : (3, 3) array

Homogeneous transformation matrix.

Has the following form:

X = a0 * x - b0 * y + a1 =
  = s * x * cos(rotation) - s * y * sin(rotation) + a1

Y = b0 * x + a0 * y + b1 =
  = s * x * sin(rotation) + s * y * cos(rotation) + b1

where s is a scale factor and the homogeneous transformation matrix is:

[[a0  b0  a1]
 [b0  a0  b1]
 [0   0    1]]

The similarity transformation extends the Euclidean transformation with a single scaling factor in addition to the rotation and translation parameters.

Parameters

matrix : (3, 3) array, optional

Homogeneous transformation matrix.

scale : float, optional

Scale factor.

rotation : float, optional

Rotation angle in counter-clockwise direction as radians.

translation : (tx, ty) as array, list or tuple, optional

x, y translation parameters.

2D similarity transformation.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

skimage.transform._geometric.estimate_transform skimage.measure.fit.ransac skimage.transform._warps.warp

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

---

File: /skimage/transform/_geometric.py#1077
type: <class 'type'>
Commit: