# davisinteractive.utils.visualization

## plot_scribble

plot_scribble(ax, scribble, frame, output_size=None, **kwargs)

**Arguments**

**ax**: Matplotlib Axis. Axis where to plot the scribble lines.**scribbles**: Scribble. Scribble to plot.**frame**: Integer. Frame of the scribble to plot.**output_size**: Tuple. Image size to scale the scribble points`(H, W)`

.****kwargs**: Dictionary. Additional parameters to pass at the`ax.plot(**kwargs)`

method.

**Returns**

`matplotlib.axis`

: Returns the given axis with the scribbles plotted on
it.

## draw_scribble

draw_scribble(img, scribble, frame, output_size=None, width=5)

**Arguments**

**img**: PIL Image. Image where to draw the scribbles.**scribbles**: Scribble. Scribble to plot.**frame**: Integer. Frame of the scribble to plot.**output_size**: Tuple. Image size to scale the scribble points`(H, W)`

.**width**: Integer. Width of the drawed lines.

**Returns**

`PIL Image`

: Returns the original image `img`

with the scribble draw on
it.

## overlay_mask

overlay_mask(im, ann, alpha=0.5, colors=None, contour_thickness=None)

This function allows you to overlay a mask over an image with some transparency.

**Arguments**

**im**: Numpy Array. Array with the image. The shape must be (H, W, 3) and the pixels must be represented as`np.uint8`

data type.**ann**: Numpy Array. Array with the mask. The shape must be (H, W) and the values must be intergers**alpha**: Float. Proportion of alpha to apply at the overlaid mask.**colors**: Numpy Array. Optional custom colormap. It must have shape (N, 3) being N the maximum number of colors to represent.**contour_thickness**: Integer. Thickness of each object index contour draw over the overlay. This function requires to have installed the package`opencv-python`

.

**Returns**

`Numpy Array`

: Image of the overlay with shape (H, W, 3) and data type
`np.uint8`

.