Front Panel:Get Image Method

Short Name: FP.Get Image

Requires: Base Development System

Class: VI Methods

To Use: Create a method.

Returns an image of the front panel as a flattened pixmap. Use the Front Panel:Get Image Scaled method to return an image of the front panel and scale it proportionally according to the maximum width and height you wire to the method.

If a front panel is not visible, LabVIEW does not update the values in the objects on the front panel. If you call a VI whose front panel is not visible and you use the Front Panel:Get Image method to create an image of the front panel, the image does not reflect any value changes that occurred when you ran the VI.

If you want the image to reflect value changes, make sure the front panel is open before any values change. If you do not want to display the front panel but want the image to reflect value changes, create a Property Node from any terminal on the block diagram of the VI for which you want to create a front panel image.

You also can use the Append Front Panel Image to Report VI to create an image of a front panel and append it to a report.

Parameters

Data type	Name	Required	Description
	visible area only	No	Indicates if the front panel image includes just the objects in the visible area of the front panel (TRUE) or all the front panel objects (FALSE). The default is TRUE.
	Image Depth	No	Indicates the color depth, or number of supported colors, of the image: 1 (1-bit, black and white), 4 (4-bit, 16 colors), 8 (8-bit, 256 colors), or 24 (24-bit, true color). The default is 8.
	Image Data	Yes	Information about the image so you can use the Draw Flattened Pixmap VI to draw it as a picture or use the Graphics Formats VIs to save the image to a file. This cluster is similar to the image data output of the Read JPEG File, Read PNG File, and Read BMP File VIs. image type—Reserved for future use. image depth—Specifies the color depth of the image, which is the number of bits to use to describe the color of each pixel in the image. Valid values include 1, 4, 8, and 24 bits per pixel. image depth affects how LabVIEW interprets the values of image and colors. image—Array of bytes that describes the color of each pixel in the image in raster order. The value of image depth determines how LabVIEW interprets the value of this output. If image depth is 24, each pixel has three bytes to describe its color. The first byte for each pixel describes the red value, the second byte describes the green value, and the third byte describes the blue value. If image depth is 8, each pixel has one byte to describe its color. The value of each bit corresponds to an element in colors, which stores 32-bit RGB values where the most-significant byte is zero, followed in order by red, green, and blue values. If image depth is 4, the behavior is similar to when image depth is 8 except valid values in image include 0 through 15. If image depth is 1, any value of zero in image corresponds to element 0 in colors. All other values correspond to element 1 in colors. The size of the array might be larger than expected due to padding. mask—Array of bytes in which each bit describes mask information for a pixel. The first byte describes the first eight pixels, the second byte describes the next eight pixels, and so on. If a bit is zero, LabVIEW draws the corresponding pixel as transparent. If the array is empty, LabVIEW draws all pixels without transparency. If the array does not contain a bit for each pixel in the image, LabVIEW draws any pixels missing from the array without transparency. colors—Array of RGB color values that correspond to the values in image. The value of image depth determines how LabVIEW interprets the value of this output. If image depth is 24, LabVIEW ignores this output. If image depth is 8, the array has 256 elements. If image depth is 4, the array has 16 elements. If image depth is 1, the array has 2 elements. Rectangle—Cluster that contains coordinates that describe the bounding rectangle of the image, where the upper-left corner is at (0,0). The bottom right edges of the bounds does not include the image.

Remarks

The following table lists the characteristics of this method.