BBIT-Kai
59 lines
3.7 KiB
YAML
59 lines
3.7 KiB
YAML
%YAML:1.0
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BaseConfig:
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minDetectorConfidence: 0.6 # If the confidence of a detector bbox is lower than this, then it won't be considered for tracking
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TargetManagement:
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enableBboxUnClipping: 1 # In case the bbox is likely to be clipped by image border, unclip bbox
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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
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# [Creation & Termination Policy]
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minIouDiff4NewTarget: 0.55 # 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.
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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]
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probationAge: 5 # If the target's age exceeds this, the target will be considered to be valid.
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maxShadowTrackingAge: 30 # Max length of shadow tracking. If the shadowTrackingAge exceeds this limit, the tracker will be terminated.
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earlyTerminationAge: 1 # If the shadowTrackingAge reaches this threshold while in TENTATIVE period, the target will be terminated prematurely.
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TrajectoryManagement:
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useUniqueID: 0 # Use 64-bit long Unique ID when assignining tracker ID. Default is [true]
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DataAssociator:
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dataAssociatorType: 0 # the type of data associator among { DEFAULT= 0 }
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associationMatcherType: 0 # the type of matching algorithm among { GREEDY=0, GLOBAL=1 }
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checkClassMatch: 1 # If checked, only the same-class objects are associated with each other. Default: true
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# [Association Metric: Thresholds for valid candidates]
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minMatchingScore4Overall: 0.0 # Min total score
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minMatchingScore4SizeSimilarity: 0.6 # Min bbox size similarity score
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minMatchingScore4Iou: 0.0 # Min IOU score
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minMatchingScore4VisualSimilarity: 0.7 # Min visual similarity score
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# [Association Metric: Weights]
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matchingScoreWeight4VisualSimilarity: 0.6 # Weight for the visual similarity (in terms of correlation response ratio)
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matchingScoreWeight4SizeSimilarity: 0.0 # Weight for the Size-similarity score
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matchingScoreWeight4Iou: 0.4 # Weight for the IOU score
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StateEstimator:
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stateEstimatorType: 1 # the type of state estimator among { DUMMY=0, SIMPLE=1, REGULAR=2 }
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# [Dynamics Modeling]
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processNoiseVar4Loc: 2.0 # Process noise variance for bbox center
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processNoiseVar4Size: 1.0 # Process noise variance for bbox size
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processNoiseVar4Vel: 0.1 # Process noise variance for velocity
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measurementNoiseVar4Detector: 4.0 # Measurement noise variance for detector's detection
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measurementNoiseVar4Tracker: 16.0 # Measurement noise variance for tracker's localization
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VisualTracker:
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visualTrackerType: 1 # the type of visual tracker among { DUMMY=0, NvDCF=1 }
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# [NvDCF: Feature Extraction]
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useColorNames: 1 # Use ColorNames feature
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useHog: 0 # Use Histogram-of-Oriented-Gradient (HOG) feature
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featureImgSizeLevel: 2 # Size of a feature image. Valid range: {1, 2, 3, 4, 5}, from the smallest to the largest
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featureFocusOffsetFactor_y: -0.2 # The offset for the center of hanning window relative to the feature height. The center of hanning window would move by (featureFocusOffsetFactor_y*featureMatSize.height) in vertical direction
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# [NvDCF: Correlation Filter]
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filterLr: 0.075 # learning rate for DCF filter in exponential moving average. Valid Range: [0.0, 1.0]
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filterChannelWeightsLr: 0.1 # learning rate for the channel weights among feature channels. Valid Range: [0.0, 1.0]
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gaussianSigma: 0.75 # Standard deviation for Gaussian for desired response when creating DCF filter [pixels]
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