FeatureTrackerConfig¶
This message is used to configure the FeatureTracker node. You can set the CornerDetector, FeatureMaintainer and MotionEstimator.
Reference¶
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class
depthai.
FeatureTrackerConfig
FeatureTrackerConfig message. Carries config for feature tracking algorithm
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class
CornerDetector
Corner detector configuration structure.
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class
Thresholds
Threshold settings structure for corner detector.
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property
decreaseFactor
When detected number of features exceeds the maximum in a cell threshold is lowered by multiplying its value with this factor.
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property
increaseFactor
When detected number of features doesn’t exceed the maximum in a cell, threshold is increased by multiplying its value with this factor.
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property
initialValue
Minimum strength of a feature which will be detected. 0 means automatic threshold update. Recommended so the tracker can adapt to different scenes/textures. Each cell has its own threshold. Empirical value.
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property
max
Maximum limit for threshold. Applicable when automatic threshold update is enabled. 0 means auto. Empirical value.
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property
min
Minimum limit for threshold. Applicable when automatic threshold update is enabled. 0 means auto, 6000000 for HARRIS, 1200 for SHI_THOMASI. Empirical value.
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property
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class
Type
Members:
HARRIS
SHI_THOMASI
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property
name
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property
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property
cellGridDimension
Ensures distributed feature detection across the image. Image is divided into horizontal and vertical cells, each cell has a target feature count = numTargetFeatures / cellGridDimension. Each cell has its own feature threshold. A value of 4 means that the image is divided into 4x4 cells of equal width/height. Maximum 4, minimum 1.
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property
enableSobel
Enable 3x3 Sobel operator to smoothen the image whose gradient is to be computed. If disabled, a simple 1D row/column differentiator is used for gradient.
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property
enableSorting
Enable sorting detected features based on their score or not.
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property
numMaxFeatures
Hard limit for the maximum number of features that can be detected. 0 means auto, will be set to the maximum value based on memory constraints.
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property
numTargetFeatures
Target number of features to detect. Maximum number of features is determined at runtime based on algorithm type.
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property
thresholds
Threshold settings. These are advanced settings, suitable for debugging/special cases.
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property
type
Corner detector algorithm type.
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class
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class
FeatureMaintainer
FeatureMaintainer configuration structure.
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property
enable
Enable feature maintaining or not.
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property
lostFeatureErrorThreshold
Optical flow measures the tracking error for every feature. If the point can’t be tracked or it’s out of the image it will set this error to a maximum value. This threshold defines the level where the tracking accuracy is considered too bad to keep the point.
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property
minimumDistanceBetweenFeatures
Used to filter out detected feature points that are too close. Requires sorting enabled in detector. Unit of measurement is squared euclidean distance in pixels.
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property
trackedFeatureThreshold
Once a feature was detected and we started tracking it, we need to update its Harris score on each image. This is needed because a feature point can disappear, or it can become too weak to be tracked. This threshold defines the point where such a feature must be dropped. As the goal of the algorithm is to provide longer tracks, we try to add strong points and track them until they are absolutely untrackable. This is why, this value is usually smaller than the detection threshold.
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property
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class
MotionEstimator
Used for feature reidentification between current and previous features.
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class
OpticalFlow
Optical flow configuration structure.
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property
epsilon
Feature tracking termination criteria. Optical flow will refine the feature position on each pyramid level until the displacement between two refinements is smaller than this value. Decreasing this number increases runtime.
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property
maxIterations
Feature tracking termination criteria. Optical flow will refine the feature position maximum this many times on each pyramid level. If the Epsilon criteria described in the previous chapter is not met after this number of iterations, the algorithm will continue with the current calculated value. Increasing this number increases runtime.
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property
pyramidLevels
Number of pyramid levels, only for optical flow. AUTO means it’s decided based on input resolution: 3 if image width <= 640, else 4. Valid values are either 3/4 for VGA, 4 for 720p and above.
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property
searchWindowHeight
Image patch height used to track features. Must be an odd number, maximum 9. N means the algorithm will be able to track motion at most (N-1)/2 pixels in a direction per pyramid level. Increasing this number increases runtime
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property
searchWindowWidth
Image patch width used to track features. Must be an odd number, maximum 9. N means the algorithm will be able to track motion at most (N-1)/2 pixels in a direction per pyramid level. Increasing this number increases runtime
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property
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class
Type
Members:
LUCAS_KANADE_OPTICAL_FLOW
HW_MOTION_ESTIMATION
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property
name
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property
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property
enable
Enable motion estimation or not.
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property
opticalFlow
Optical flow configuration. Takes effect only if MotionEstimator algorithm type set to LUCAS_KANADE_OPTICAL_FLOW.
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property
type
Motion estimator algorithm type.
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class
-
get
(self: depthai.FeatureTrackerConfig) → depthai.RawFeatureTrackerConfig Retrieve configuration data for FeatureTracker.
- Returns
config for feature tracking algorithm
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getData
(self: object) → numpy.ndarray[numpy.uint8] Get non-owning reference to internal buffer
- Returns
Reference to internal buffer
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getRaw
(self: depthai.ADatatype) → depthai.RawBuffer
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set
(self: depthai.FeatureTrackerConfig, config: depthai.RawFeatureTrackerConfig) → depthai.FeatureTrackerConfig Set explicit configuration.
- Parameter
config
: Explicit configuration
- Parameter
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setCornerDetector
(*args, **kwargs) Overloaded function.
setCornerDetector(self: depthai.FeatureTrackerConfig, cornerDetector: depthai.RawFeatureTrackerConfig.CornerDetector.Type) -> depthai.FeatureTrackerConfig
Set corner detector algorithm type.
- Parameter
cornerDetector
: Corner detector type, HARRIS or SHI_THOMASI
setCornerDetector(self: depthai.FeatureTrackerConfig, config: depthai.RawFeatureTrackerConfig.CornerDetector) -> depthai.FeatureTrackerConfig
Set corner detector full configuration.
- Parameter
config
: Corner detector configuration
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setData
(*args, **kwargs) Overloaded function.
setData(self: depthai.Buffer, arg0: List[int]) -> None
- Parameter
data
: Copies data to internal buffer
setData(self: depthai.Buffer, arg0: numpy.ndarray[numpy.uint8]) -> None
- Parameter
data
: Copies data to internal buffer
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setFeatureMaintainer
(*args, **kwargs) Overloaded function.
setFeatureMaintainer(self: depthai.FeatureTrackerConfig, enable: bool) -> depthai.FeatureTrackerConfig
Enable or disable feature maintainer.
Parameter
enable
:setFeatureMaintainer(self: depthai.FeatureTrackerConfig, config: depthai.RawFeatureTrackerConfig.FeatureMaintainer) -> depthai.FeatureTrackerConfig
Set feature maintainer full configuration.
- Parameter
config
: feature maintainer configuration
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setHwMotionEstimation
(self: depthai.FeatureTrackerConfig) → depthai.FeatureTrackerConfig Set hardware accelerated motion estimation using block matching. Faster than optical flow (software implementation) but might not be as accurate.
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setMotionEstimator
(*args, **kwargs) Overloaded function.
setMotionEstimator(self: depthai.FeatureTrackerConfig, enable: bool) -> depthai.FeatureTrackerConfig
Enable or disable motion estimator.
Parameter
enable
:setMotionEstimator(self: depthai.FeatureTrackerConfig, config: depthai.RawFeatureTrackerConfig.MotionEstimator) -> depthai.FeatureTrackerConfig
Set motion estimator full configuration.
- Parameter
config
: Motion estimator configuration
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setNumTargetFeatures
(self: depthai.FeatureTrackerConfig, numTargetFeatures: int) → depthai.FeatureTrackerConfig Set number of target features to detect.
- Parameter
numTargetFeatures
: Number of features
- Parameter
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setOpticalFlow
(*args, **kwargs) Overloaded function.
setOpticalFlow(self: depthai.FeatureTrackerConfig) -> depthai.FeatureTrackerConfig
Set optical flow as motion estimation algorithm type.
setOpticalFlow(self: depthai.FeatureTrackerConfig, config: depthai.RawFeatureTrackerConfig.MotionEstimator.OpticalFlow) -> depthai.FeatureTrackerConfig
Set optical flow full configuration.
- Parameter
config
: Optical flow configuration
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class
-
class
dai
::
FeatureTrackerConfig
: public dai::Buffer¶ FeatureTrackerConfig message. Carries config for feature tracking algorithm
Public Types
-
using
CornerDetector
= RawFeatureTrackerConfig::CornerDetector¶
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using
MotionEstimator
= RawFeatureTrackerConfig::MotionEstimator¶
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using
FeatureMaintainer
= RawFeatureTrackerConfig::FeatureMaintainer¶
Public Functions
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FeatureTrackerConfig
()¶ Construct FeatureTrackerConfig message.
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~FeatureTrackerConfig
() = default¶
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FeatureTrackerConfig &
setCornerDetector
(dai::FeatureTrackerConfig::CornerDetector::Type cornerDetector)¶ Set corner detector algorithm type.
- Parameters
cornerDetector
: Corner detector type, HARRIS or SHI_THOMASI
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FeatureTrackerConfig &
setCornerDetector
(dai::FeatureTrackerConfig::CornerDetector config)¶ Set corner detector full configuration.
- Parameters
config
: Corner detector configuration
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FeatureTrackerConfig &
setOpticalFlow
()¶ Set optical flow as motion estimation algorithm type.
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FeatureTrackerConfig &
setOpticalFlow
(dai::FeatureTrackerConfig::MotionEstimator::OpticalFlow config)¶ Set optical flow full configuration.
- Parameters
config
: Optical flow configuration
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FeatureTrackerConfig &
setHwMotionEstimation
()¶ Set hardware accelerated motion estimation using block matching. Faster than optical flow (software implementation) but might not be as accurate.
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FeatureTrackerConfig &
setNumTargetFeatures
(std::int32_t numTargetFeatures)¶ Set number of target features to detect.
- Parameters
numTargetFeatures
: Number of features
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FeatureTrackerConfig &
setMotionEstimator
(bool enable)¶ Enable or disable motion estimator.
- Parameters
enable
:
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FeatureTrackerConfig &
setMotionEstimator
(dai::FeatureTrackerConfig::MotionEstimator config)¶ Set motion estimator full configuration.
- Parameters
config
: Motion estimator configuration
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FeatureTrackerConfig &
setFeatureMaintainer
(bool enable)¶ Enable or disable feature maintainer.
- Parameters
enable
:
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FeatureTrackerConfig &
setFeatureMaintainer
(dai::FeatureTrackerConfig::FeatureMaintainer config)¶ Set feature maintainer full configuration.
- Parameters
config
: feature maintainer configuration
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FeatureTrackerConfig &
set
(dai::RawFeatureTrackerConfig config)¶ Set explicit configuration.
- Parameters
config
: Explicit configuration
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dai::RawFeatureTrackerConfig
get
() const¶ Retrieve configuration data for FeatureTracker.
- Return
config for feature tracking algorithm
Private Members
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using