Draw

labvision.images.draw.draw_filled_polygon(im, points, color=(0, 0, 255))

Adds a filled polygon to an image

Parameters:
  • im – np.ndarrary of dtype np.uint8
  • points – N, 2 ndarray of corner points
  • color – BGR color tuple or images library color
Returns:

im: ndarray
labvision.images.draw.draw_circle(im, cx, cy, rad, color=(0, 255, 255), thickness=2)

Draw Circle NEEDS DOCSTRING

Parameters:
  • im –
  • cx –
  • cy –
  • rad –
  • color –
  • thickness –
Returns:
labvision.images.draw.draw_circles(im, circles, color=(0, 255, 255), thickness=2)

NEEDS DOCSTRING

Parameters:
  • im –
  • circles –
  • color –
  • thickness –
Returns:
labvision.images.draw.draw_circles_with_scale(im, circles, values, cmap=<sphinx.ext.autodoc.importer._MockObject object>, thickness=2)

NEEDS DOCSTRING

Parameters:
  • im –
  • circles –
  • values –
  • cmap –
  • thickness –
Returns:
labvision.images.draw.draw_delaunay_tess(im, points)

Draws the delaunay tesselation for a set of points on an image

Parameters:
  • im (input image) – Any number of channels
  • points (array of N points) – Shape (N, 2). points[:, 0] contains x coordinates points[:, 1] contains y coordinates
Returns:

in – Same shape and type as input image
Return type:

annotated image
labvision.images.draw.draw_polygon(im, vertices, color=(0, 0, 255), thickness=1)

Draws a polygon on an image from a list of vertices

Parameters:
  • im (input image) – Any number of channels
  • vertices (array of N vertices) –
    Shape (N, 2) where
    vertices[:, 0] contains x coordinates vertices[:, 1] contains y coordinates
  • color (BGR tuple) – if input image is grayscale then circles will be black
  • thickness (int) – Thickness of the lines
Returns:

out – Same shape and type as input image
Return type:

output image
labvision.images.draw.draw_polygons(im, polygons, color=(0, 0, 255))

Draws multiple polygons on an image from a list of polygons

Parameters:
  • im (input image) – Any number of channels
  • polygons (array containing coordinates of polygons) – shape is (P, N, 2) where P is the number of polygons, N is the number of vertices in each polygon. [:, :, 0] contains x coordinates, [:, :, 1] contains y coordinates.
  • color (BGR tuple) –
Returns:

img – Same shape and type as input image
Return type:

annotated image
labvision.images.draw.draw_voronoi_cells(im, points)

Draws the voronoi cells for a set of points on an image

Parameters:
  • im (input image) – Any number of channels
  • points (array of N points) – Shape (N, 2). points[:, 0] contains x coordinates points[:, 1] contains y coordinates
Returns:

im – Same shape and type as input image
Return type:

annotated image
labvision.images.draw.draw_contours(im, contours, col=(0, 0, 255), thickness=1)

NEEDS DOCSTRING

Parameters:
  • im –
  • contours –
  • col –
  • thickness –
Returns: