JSON Results Specification

Limelight's JSON results output is a collection of arrays containing targeting results. Separate arrays exist for retroreflective, fiducial, neural classifier, and neural detector results. JSON is human-readable and easy to parse in any language on any platform, so it is perfect for most use-cases.

The same JSON results output may be retrieved using the REST/HTTP, Websocket, and NetworkTables APIs.

Parsing this JSON output is incredibly easy with our FRC libraries.

Limelightlib has built-in functionality that parses the JSON Dump into a LimelightResults object.

https://github.com/LimelightVision/limelightlib-wpijava

https://github.com/LimelightVision/limelightlib-wpicpp

Every JSON result contains the following entries:

Key Name	Value Description
tl	Targeting latency (milliseconds consumed by tracking loop this frame)
cl	Capture latency (milliseconds between the end of the exposure of the middle row to the beginning of the tracking loop)
tx	Horizontal Offset From Crosshair To Target (LL1: -27 degrees to 27 degrees / LL2: -29.8 to 29.8 degrees)
ty	Vertical Offset From Crosshair To Target (LL1: -20.5 degrees to 20.5 degrees / LL2: -24.85 to 24.85 degrees)
txnc	Horizontal Offset From Principal Pixel To Target (degrees)
tync	Vertical Offset From Principal Pixel To Target (degrees)
ta	Undistorted, normalized area of target (0-100)
PythonOut	Output data from python SnapScript Pipelines
stdev_mt1	MT1 Standard Deviation [x, y, z, roll, pitch, yaw] (meters, degrees)
stdev_mt2	MT2 Standard Deviation [x, y, z, roll, pitch, yaw] (meters, degrees)
pID	Current Pipeline index
pTYPE	Current Pipeline Type e.g. "pipe_color"
ts	Timestamp in milliseconds from boot.
v	Validity indicator. 1 = valid targets, 0 = no valid targets
botpose	Botpose (MegaTag): x,y,z, roll, pitch, yaw (meters, degrees)
botpose_wpired	Botpose (MegaTag, WPI Red driverstation): x,y,z, roll, pitch, yaw (meters, degrees)
botpose_wpiblue	Botpose (MegaTag, WPI Blue driverstation): x,y,z, roll, pitch, yaw (meters, degrees)
botpose_orb	Botpose (MegaTag2): x,y,z, roll, pitch, yaw (meters, degrees)
botpose_orb_wpired	Botpose (MegaTag2, WPI Red driverstation): x,y,z, roll, pitch, yaw (meters, degrees)
botpose_orb_wpiblue	Botpose (MegaTag2, WPI Blue driverstation): x,y,z, roll, pitch, yaw (meters, degrees)
botpose_avgarea	Average area of tags used to compute botpose
botpose_avgdist	Max distance between tags used to compute botpose (meters)
botpose_span	Max distance between tags used to compute botpose (meters)
botpose_tagcount	Number of tags used to compute botpose
Retro	Color/Retroreflective pipeline results array
Fiducial	AprilTag pipeline results array
Detector	Neural Detector pipeline results array
Classifier	Classifier pipeline results array
Barcode	Barcode pipeline results array

Color/Retroreflective Results

The "Retro" array contains entries with the following structure:

Key Name	Value Description
t6c_ts	Camera Pose in target space as computed by solvepnp (x,y,z,rx,ry,rz)
t6r_fs	Robot Pose in field space as computed by solvepnp (x,y,z,rx,ry,rz)
t6r_ts	Robot Pose in target space as computed by solvepnp (x,y,z,rx,ry,rz)
t6t_cs	Target Pose in camera space as computed by solvepnp (x,y,z,rx,ry,rz)
t6t_rs	Target Pose in robot space as computed by solvepnp (x,y,z,rx,ry,rz)
ta	The size of the target as a percentage of the image (0-1)
tx	X-coordinate of the center of the target in degrees relative to crosshair. Positive-right, center-zero
tx_nocross	X-coordinate of the center of the target in degrees relative to principal piexel. Positive-right, center-zero
txp	X-coordinate of the center of the target in pixels relative to crosshair. Positive-right, center-zero
ty	Y-coordinate of the center of the target in degrees relative to crosshair. Positive-down, center-zero
ty_nocross	Y-coordinate of the center of the target in degrees relative to principal pixel. Positive-right, center-zero
typ	Y-coordinate of the center of the target in pixels relative to crosshair. Positive-down, center-zero
pts	Corners array (pixels) [x0,y0,x1,y1.....]. Must be enabled in output tab

Example JSON for Color / Retroreflective Pipelines

{
  "Barcode": [],
  "Classifier": [],
  "Detector": [],
  "Fiducial": [],
  "PythonOut": [],
  "Retro": [
    {
      "pts": [],
      "t6c_ts": [],
      "t6r_fs": [],
      "t6r_ts": [],
      "t6t_cs": [],
      "t6t_rs": [],
      "ta": 0.00531171215698123,
      "tx": -4.535492777705656,
      "tx_nocross": -4.428826910553056,
      "txp": 542.53076171875,
      "ty": -1.1722867231218714,
      "ty_nocross": -0.09285491974145543,
      "typ": 504.5538635253906
    },
    {
      "pts": [],
      "t6c_ts": [],
      "t6r_fs": [],
      "t6r_ts": [],
      "t6t_cs": [],
      "t6t_rs": [],
      "ta": 0.005779948551207781,
      "tx": 8.465099348209478,
      "tx_nocross": 8.571765215362078,
      "txp": 822.1087036132812,
      "ty": -2.524207730360601,
      "ty_nocross": -1.444775926980185,
      "typ": 533.6112060546875
    },
  ],
  "botpose": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "botpose_avgarea": 0,
  "botpose_avgdist": 0,
  "botpose_orb": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "botpose_orb_wpiblue": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "botpose_orb_wpired": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "botpose_span": 0,
  "botpose_tagcount": 0,
  "botpose_wpiblue": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "botpose_wpired": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "cl": 37.619998931884766,
  "focus_metric": 0,
  "pID": 0,
  "pTYPE": "pipe_color",
  "stdev_mt1": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "stdev_mt2": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "t6c_rs": [
    0,
    0,
    0,
    0,
    0,
    0
  ],
  "ta": 0.39156023412942886,
  "tl": 22.64053726196289,
  "ts": 215248.979204,
  "tx": -4.3848327488723555,
  "txnc": -4.278166881719756,
  "ty": -1.1144596937982527,
  "tync": -0.035027890417836716,
  "v": 1
}

AprilTag/Fiducial Results

The "Fiducial" array contains entries with the following structure:

Key Name	Value Description
fid	Fiducial tag ID
fam	Fiducial Family (16H5C, 25H9C, 36H11C, etc)
pts	Return individual corner points. Must be enabled.
skew	Currently unused
t6c_ts	Camera Pose in target space as computed by this fiducial (x,y,z,pitch,yaw,roll) (meters, degrees)
t6r_fs	Robot Pose in field space as computed by this fiducial (x,y,z,pitch,yaw,roll) (meters, degrees)
t6r_fs_orb	Robot Pose in field space as computed by this fiducial (Megatag2) (x,y,z,pitch,yaw,roll) (meters, degrees)
t6r_ts	Robot Pose in target space as computed by this fiducial (x,y,z,pitch,yaw,roll) (meters, degrees)
t6t_cs	Target Pose in camera space as computed by this fiducial (x,y,z,pitch,yaw,roll) (meters, degrees)
t6t_rs	Target Pose in robot space as computed by this fiducial (x,y,z,pitch,yaw,roll) (meters, degrees)
ta	The size of the target as a percentage of the image (0-1)
tx	X-coordinate of the center of the target in degrees relative to crosshair. Positive-right, center-zero
tx_nocross	X-coordinate of the center of the target in degrees relative to principal piexel. Positive-right, center-zero
txp	X-coordinate of the center of the target in pixels relative to crosshair. Positive-right, center-zero
ty	Y-coordinate of the center of the target in degrees relative to crosshair. Positive-down, center-zero
ty_nocross	Y-coordinate of the center of the target in degrees relative to principal pixel. Positive-right, center-zero
typ	Y-coordinate of the center of the target in pixels relative to crosshair. Positive-down, center-zero
pts	Corners array (pixels) [x0,y0,x1,y1.....]. Must be enabled in output tab

Example JSON for AprilTag Pipelines

{
    "Classifier": [],
    "Detector": [],
    "Fiducial": [
    {
        "fID": 2,
        "fam": "16H5C",
        "pts": [],
        "skew": [],
        "t6c_ts": [
        0.33247368976801916,
        -0.05672695778305914,
        -2.5042031405987144,
        -4.680849607956358,
        -5.171154989721864,
        4.528697946312339
        ],
        "t6r_fs": [
        4.738896418276903,
        -1.5926603672041666,
        0.5194469577830592,
        4.522658587661256,
        4.258580454853879,
        5.5236539893713275
        ],
        "t6r_ts": [
        0.33247368976801916,
        -0.05672695778305914,
        -2.5042031405987144,
        -4.680849607956358,
        -5.171154989721864,
        4.528697946312339
        ],
        "t6t_cs": [
        -0.09991902572799474,
        -0.1234042720218289,
        2.5218203039582496,
        4.278368708252767,
        5.508508005282244,
        -4.1112864453027775
        ],
        "t6t_rs": [
        -0.09991902572799474,
        -0.1234042720218289,
        2.5218203039582496,
        4.278368708252767,
        5.508508005282244,
        -4.1112864453027775
        ],
        "ta": 0.005711808800697327,
        "tx": -2.0525293350219727,
        "txp": 149.4874725341797,
        "ty": 2.7294836044311523,
        "typ": 107.14710235595703
    }
    ],
    "Retro": [],
    "pID": 0,
    "tl": 19.78130340576172,
    "ts": 3284447.910569,
    "v": 1
}

Neural Detector Results

The "Detector" array contains entries with the following structure:

Key Name	Value Description
class	Human-readable class name string
classID	ClassID integer
conf	Confidence of the predicition
pts	Individual corner points as an array of [x,y] in pixels. Center-zero, positive right and down. Must be enabled.
ta	The size of the target as a percentage of the image (0-1)
tx	X-coordinate of the center of the target in degrees relative to crosshair. Positive-right, center-zero
tx_nocross	X-coordinate of the center of the target in degrees relative to principal piexel. Positive-right, center-zero
txp	X-coordinate of the center of the target in pixels relative to crosshair. Positive-right, center-zero
ty	Y-coordinate of the center of the target in degrees relative to crosshair. Positive-down, center-zero
ty_nocross	Y-coordinate of the center of the target in degrees relative to principal pixel. Positive-right, center-zero
typ	Y-coordinate of the center of the target in pixels relative to crosshair. Positive-down, center-zero
pts	Corners array (pixels) [x0,y0,x1,y1.....]. Must be enabled in output tab

Example JSON for Detector Pipelines

{
    "Classifier": [],
    "Detector": [
    {
        "class": "person",
        "classID": 0,
        "conf": 0.83984375,
        "pts": [],
        "ta": 0.2608712911605835,
        "tx": -2.45949649810791,
        "txp": 147.5,
        "ty": -10.066887855529785,
        "typ": 165.5
    }
    ],
    "Fiducial": [],
    "Retro": [],
    "pID": 0,
    "tl": 63.50614547729492,
    "ts": 4932985.266867,
    "v": 1
}

Neural Classifier Results

The "Classifier" array contains entries with the following structure:

Key Name	Value Description
class	Human-readable class name string
classID	ClassID integer
conf	Confidence of the predicition

Example JSON for Classifier Pipelines

{
    "Classifier": [
    {
        "class": "digital clock",
        "classID": 531,
        "conf": 0.16796875
    }
    ],
    "Detector": [],
    "Fiducial": [],
    "Retro": [],
    "pID": 0,
    "tl": 16.704740524291992,
    "ts": 4751332.7542280005,
    "v": 1
}

Barcode Results

The "Barcode" array contains entries with the following structure:

Key Name	Value Description
fam	Barcode Family e.g. "qr"
data	Decoded barcode data as string
ta	The size of the target as a percentage of the image (0-1)
tx	X-coordinate of the center of the target in degrees relative to crosshair. Positive-right, center-zero
tx_nocross	X-coordinate of the center of the target in degrees relative to principal piexel. Positive-right, center-zero
txp	X-coordinate of the center of the target in pixels relative to crosshair. Positive-right, center-zero
ty	Y-coordinate of the center of the target in degrees relative to crosshair. Positive-down, center-zero
ty_nocross	Y-coordinate of the center of the target in degrees relative to principal pixel. Positive-right, center-zero
typ	Y-coordinate of the center of the target in pixels relative to crosshair. Positive-down, center-zero
pts	Corners array (pixels) [x0,y0,x1,y1.....]. Must be enabled in output tab

Example JSON for Barcode Pipelines

{
    "Barcode": [
    {
        "fam": "QR",
        "data": "Hello, World!",
        "txp": 150.5,
        "typ": 120.75,
        "tx": -2.5,
        "ty": 1.8,
        "tx_nocross": -2.3,
        "ty_nocross": 2.0,
        "ta": 0.05,
        "pts": [[140, 110], [160, 110], [160, 130], [140, 130]]
    }
    ],
    "Classifier": [],
    "Detector": [],
    "Fiducial": [],
    "Retro": [],
    "pID": 0,
    "tl": 15.2,
    "ts": 4751332.7542280005,
    "v": 1
}

JSON Results Specification

Color/Retroreflective Results​

AprilTag/Fiducial Results​

Neural Detector Results​

Neural Classifier Results​

Barcode Results​

Color/Retroreflective Results

AprilTag/Fiducial Results

Neural Detector Results

Neural Classifier Results

Barcode Results