NetworkTables API

Limelight OS features a NetworkTables 4 Client. It auto-connects to the NetworkTables 4 Server running on FRC Robots based on the Team Number / ID configured in the Settings UI.

All data is published to a table that matches the device name (e.g. "limelight"). If a hostname / nickname is assigned to your camera, the table name will match the full limelight name (e.g. "limelight-top").

LimelightLib WPIJava and LimelightLib WPICPP interact with Limelight devices via NetworkTables.

Basic Targeting Data

Use the following code:

Java

NetworkTableInstance.getDefault().getTable("limelight").getEntry("<variablename>").getDouble(0);

LabView

C++

nt::NetworkTableInstance::GetDefault().GetTable("limelight")->GetNumber("<variablename>",0.0);

Python

NetworkTables.getTable("limelight").getNumber('<variablename>');

to retrieve this data:

key	type	description
tv	int	1 if valid target exists. 0 if no valid targets exist
tx	double	Horizontal Offset From Crosshair To Target (LL1: -27 degrees to 27 degrees / LL2: -29.8 to 29.8 degrees)
ty	double	Vertical Offset From Crosshair To Target (LL1: -20.5 degrees to 20.5 degrees / LL2: -24.85 to 24.85 degrees)
txnc	double	Horizontal Offset From Principal Pixel To Target (degrees)
tync	double	Vertical Offset From Principal Pixel To Target (degrees)
ta	double	Target Area (0% of image to 100% of image)
tl	double	The pipeline's latency contribution (ms). Add to "cl" to get total latency.
cl	double	Capture pipeline latency (ms). Time between the end of the exposure of the middle row of the sensor to the beginning of the tracking pipeline.
t2d	double	Array containing several values for matched-timestamp statistics: [targetValid, targetCount, targetLatency, captureLatency, tx, ty, txnc, tync, ta, tid, targetClassIndexDetector , targetClassIndexClassifier, targetLongSidePixels, targetShortSidePixels, targetHorizontalExtentPixels, targetVerticalExtentPixels, targetSkewDegrees]
getpipe	int	True active pipeline index of the camera (0 .. 9)
getpipetype	string	Pipeline Type e.g. "pipe_color"
json	string	Full JSON dump of targeting results. Must be enabled per-pipeline in the 'output' tab
tclass	string	Class name of primary neural detector result or neural classifier result
tc	doubleArray	Get the average HSV color underneath the crosshair region (3x3 pixel region) as a NumberArray
hb	double	heartbeat value. Increases once per frame, resets at 2 billion
hw	doubleArray	HW metrics [fps, cpu temp, ram usage, temp]
crosshairs	doubleArray	2D Crosshairs [cx0, cy0, cx1, cy1]
tcclass	string	Name of classifier pipeline's computed class
tdclass	string	Name of detector pipeline's primary detection

AprilTag and 3D Data

Use the following code:

Java

NetworkTableInstance.getDefault().getTable("limelight").getEntry("<variablename>").getDoubleArray(new double[6]);

C++

nt::NetworkTableInstance::GetDefault().GetTable("limelight")->GetNumberArray("<variablename>",std::vector<double>(6));

to retrieve this data:

key	type	description
botpose	doubleArray	Robot transform in field-space. Translation (X,Y,Z) in meters Rotation(Roll,Pitch,Yaw) in degrees, total latency (cl+tl), tag count, tag span, average tag distance from camera, average tag area (percentage of image)
botpose_wpiblue	doubleArray	Robot transform in field-space (blue driverstation WPILIB origin). Translation (X,Y,Z) in meters Rotation(Roll,Pitch,Yaw) in degrees, total latency (cl+tl), tag count, tag span, average tag distance from camera, average tag area (percentage of image)
botpose_wpired	doubleArray	Robot transform in field-space (red driverstation WPILIB origin). Translation (X,Y,Z) in meters, Rotation(Roll,Pitch,Yaw) in degrees, total latency (cl+tl), tag count, tag span, average tag distance from camera, average tag area (percentage of image)
botpose_orb	doubleArray	Robot transform in field-space (Megatag2). Translation (X,Y,Z) in meters Rotation(Roll,Pitch,Yaw) in degrees, total latency (cl+tl), tag count, tag span, average tag distance from camera, average tag area (percentage of image)
botpose_orb_wpiblue	doubleArray	Robot transform in field-space (Megatag2) (blue driverstation WPILIB origin). Translation (X,Y,Z) in meters Rotation(Roll,Pitch,Yaw) in degrees, total latency (cl+tl), tag count, tag span, average tag distance from camera, average tag area (percentage of image)
botpose_orb_wpired	doubleArray	Robot transform in field-space (Megatag2) (red driverstation WPILIB origin). Translation (X,Y,Z) in meters, Rotation(Roll,Pitch,Yaw) in degrees, total latency (cl+tl), tag count, tag span, average tag distance from camera, average tag area (percentage of image)
camerapose_targetspace	doubleArray	3D transform of the camera in the coordinate system of the primary in-view AprilTag (array (6)) [tx, ty, tz, pitch, yaw, roll] (meters, degrees)
targetpose_cameraspace	doubleArray	3D transform of the primary in-view AprilTag in the coordinate system of the Camera (array (6)) [tx, ty, tz, pitch, yaw, roll] (meters, degrees)
targetpose_robotspace	doubleArray	3D transform of the primary in-view AprilTag in the coordinate system of the Robot (array (6)) [tx, ty, tz, pitch, yaw, roll] (meters, degrees)
botpose_targetspace	doubleArray	3D transform of the robot in the coordinate system of the primary in-view AprilTag (array (6)) [tx, ty, tz, pitch, yaw, roll] (meters, degrees)
camerapose_robotspace	doubleArray	3D transform of the camera in the coordinate system of the robot (array (6))
tid	int	ID of the primary in-view AprilTag
stddevs	doubleArray	MegaTag Standard Deviations [MT1x, MT1y, MT1z, MT1roll, MT1pitch, MT1Yaw, MT2x, MT2y, MT2z, MT2roll, MT2pitch, MT2yaw]

camerapose_robotspace_set	doubleArray	SET the camera's pose in the coordinate system of the robot.
priorityid	int	SET the required ID for tx/ty targeting. Ignore other targets. Does not affect localization
robot_orientation_set	doubleArray	SET Robot Orientation and angular velocities in degrees and degrees per second[yaw,yawrate,pitch,pitchrate,roll,rollrate]
fiducial_id_filters_set	doubleArray	Override valid fiducial ids for localization (array)
fiducial_offset_set	doubleArray	SET the 3D Point of Interest Offset [x,y,z]

Camera Controls

Use the following code:

Java

NetworkTableInstance.getDefault().getTable("limelight").getEntry("<variablename>").setNumber(<value>);

LabView

C++

nt::NetworkTableInstance::GetDefault().GetTable("limelight")->PutNumber("<variablename>",<value>);

Python

NetworkTables.getTable("limelight").putNumber('<variablename>',<value>)

to set this data:

ledMode	Sets limelight's LED state
[0]	use the LED Mode set in the current pipeline
[1]	force off
[2]	force blink
[3]	force on

pipeline	Sets limelight's current pipeline
0 .. 9	Select pipeline 0..9

stream	Sets limelight's streaming mode
0	Standard - Side-by-side streams if a webcam is attached to Limelight
1	PiP Main - The secondary camera stream is placed in the lower-right corner of the primary camera stream
2	PiP Secondary - The primary camera stream is placed in the lower-right corner of the secondary camera stream

crop	(Array) Sets the crop rectangle. The pipeline must utilize the default crop rectangle in the web interface. The array must have exactly 4 entries.
[0]	X0 - Min or Max X value of crop rectangle (-1 to 1)
[1]	X1 - Min or Max X value of crop rectangle (-1 to 1)
[2]	Y0 - Min or Max Y value of crop rectangle (-1 to 1)
[3]	Y1 - Min or Max Y value of crop rectangle (-1 to 1)

Java

double[] cropValues = new double[4];
cropValues[0] = -1.0;
cropValues[1] = 1.0;
cropValues[2] = -1.0;
cropValues[3] = 1.0;
NetworkTableInstance.getDefault().getTable("limelight").getEntry("crop").setDoubleArray(cropValues);

C++

wip

Python

Python scripts allow for arbitrary inbound and outbound data.

llpython	NumberArray sent by python scripts. This is accessible within robot code.
llrobot	NumberArray sent by the robot. This is accessible within python SnapScripts.

Raw Data

Corners:

Enable "send contours" in the "Output" tab to stream corner coordinates:

tcornxy

Number array of corner coordinates [x0,y0,x1,y1......]

Raw Targets:

Limelight posts three raw contours to NetworkTables that are not influenced by your grouping mode. That is, they are filtered with your pipeline parameters, but never grouped. X and Y are returned in normalized screen space (-1 to 1) rather than degrees.

rawtargets

[txnc,tync,ta,txnc2,tync2,ta2....]

Raw Fiducials:

Get all valid (unfiltered) fiducials

rawfiducials

[id, txnc, tync, ta, distToCamera, distToRobot, ambiguity, id2.....]

Raw Detections:

Get all valid (unfiltered) nerual detection results

rawdetections

[id, txnc, tync, ta, corner0x, corner0y, corner1x, corner1y, corner2x, corner2y, corner3x, corner3y, id2.....]

Raw Barcodes:

Get all valid (unfiltered) barcode results

rawbarcodes

string array of barcode data