%YAML:1.0
BaseConfig:
minDetectorConfidence: 0 # If the confidence of a detector bbox is lower than this, then it won’t be considered for tracking
TargetManagement:
maxTargetsPerStream: 150 # Max number of targets to track per stream. Recommended to set >10. Note: this value should account for the targets being tracked in shadow mode as well. Max value depends on the GPU memory capacity
[Creation & Termination Policy]
minIouDiff4NewTarget: 0.5 # If the IOU between the newly detected object and any of the existing targets is higher than this threshold, this newly detected object will be discarded.
minTrackerConfidence: 0.2 # If the confidence of an object tracker is lower than this on the fly, then it will be tracked in shadow mode. Valid Range: [0.0, 1.0]
probationAge: 3 # If the target’s age exceeds this, the target will be considered to be valid.
maxShadowTrackingAge: 150 # Max length of shadow tracking. If the shadowTrackingAge exceeds this limit, the tracker will be terminated.
earlyTerminationAge: 1 # If the shadowTrackingAge reaches this threshold while in TENTATIVE period, the the target will be terminated prematurely.
TrajectoryManagement:
useUniqueID: 0 # Use 64-bit long Unique ID when assignining tracker ID.
enableReAssoc: 1 # Enable Re-Assoc
[Re-Assoc: Motion-based]
minTrajectoryLength4Projection: 20 # min trajectory length required to make projected trajectory
prepLength4TrajectoryProjection: 10 # the length of the trajectory during which the state estimator is updated to make projections
trajectoryProjectionLength: 300 # the length of the projected trajectory
[Re-Assoc: Trajectory Similarity]
minTrackletMatchingScore: 0.2 # min tracklet similarity score for matching in terms of average IOU between tracklets
maxAngle4TrackletMatching: 180 # max angle difference for tracklet matching [degree]
minSpeedSimilarity4TrackletMatching: 0.4 # min speed similarity for tracklet matching
minBboxSizeSimilarity4TrackletMatching: 0.2 # min bbox size similarity for tracklet matching
maxTrackletMatchingTimeSearchRange: 500 # the search space in time for max tracklet similarity
DataAssociator:
dataAssociatorType: 0 # the type of data associator among { DEFAULT= 0 }
associationMatcherType: 0 # the type of matching algorithm among { GREEDY=0, GLOBAL=1 }
checkClassMatch: 1 # If checked, only the same-class objects are associated with each other. Default: true
Thresholds in matching scores to be considered as a valid candidate for matching
minMatchingScore4Overall: 0.0 # Min total score
minMatchingScore4SizeSimilarity: 0.2 # Min bbox size similarity score
minMatchingScore4Iou: 0.0 # Min IOU score
thresholdMahalanobis: 9.4877 # Max Mahalanobis distance based on Chi-square probabilities
StateEstimator:
stateEstimatorType: 2 # the type of state estimator among { DUMMY=0, SIMPLE=1, REGULAR=2 }
[Dynamics Modeling]
noiseWeightVar4Loc: 0.05 # weight of process and measurement noise for bbox center; if set, location noise will be proportional to box height
noiseWeightVar4Vel: 0.00625 # weight of process and measurement noise for velocity; if set, velocity noise will be proportional to box height
useAspectRatio: 1 # use aspect ratio in Kalman filter’s observation
ReID:
reidType: 1 # the type of reid among { DUMMY=0, DEEP=1 }
batchSize: 100 # batch size of reid network
workspaceSize: 1000 # workspace size to be used by reid engine, in MB
reidFeatureSize: 128 # size of reid feature
reidHistorySize: 100 # max number of reid features kept for one object
inferDims: [128, 64, 3] # reid network input dimension CHW or HWC based on inputOrder
inputOrder: 1 # reid network input order among { NCHW=0, NHWC=1 }
colorFormat: 0 # reid network input color format among {RGB=0, BGR=1 }
networkMode: 0 # reid network inferenc e precision mode among {fp32=0, fp16=1, int8=2 }
offsets: [0.0, 0.0, 0.0] # array of values to be subtracted from each input channel, with length equal to number of channels
netScaleFactor: 1.0 # # scaling factor for reid network input after substracting offsets
inputBlobName: “images” # reid network input layer name
outputBlobName: “features” # reid network output layer name
uffFile: “model_tracker/mars-small128.uff” # ABSOLUTE path to reid network uff model
modelEngineFile: “/home/anavid-server/models_tst_amine/traking/model_tracker/mars-small128.uff_b100_gpu0_fp32.engine” # engine file path
keepAspc: 1 # whether to keep aspc ratio when resizing input objects for reid
