sklearn.feature_extraction.image.img_to_graph

sklearn.feature_extraction.image.img_to_graph(img, *, mask=None, return_as=<class 'scipy.sparse._coo.coo_matrix'>, dtype=None)[source]

Graph of the pixel-to-pixel gradient connections.

Edges are weighted with the gradient values.

Read more in the User Guide.

Parameters:
imgndarray of shape (height, width) or (height, width, channel)

2D or 3D image.

maskndarray of shape (height, width) or (height, width, channel), dtype=bool, default=None

An optional mask of the image, to consider only part of the pixels.

return_asnp.ndarray or a sparse matrix class, default=sparse.coo_matrix

The class to use to build the returned adjacency matrix.

dtypedtype, default=None

The data of the returned sparse matrix. By default it is the dtype of img.

Returns:
graphndarray or a sparse matrix class

The computed adjacency matrix.

Notes

For scikit-learn versions 0.14.1 and prior, return_as=np.ndarray was handled by returning a dense np.matrix instance. Going forward, np.ndarray returns an np.ndarray, as expected.

For compatibility, user code relying on this method should wrap its calls in np.asarray to avoid type issues.