OpenCV

This arrow is a collection of vital algorithms implemented with the OpenCV API

This arrow can be built by enabling the KWIVER_ENABLE_OPENCV CMake flag

This arrow contains the following functionality:

Analyze Tracks Algorithm

class analyze_tracks : public kwiver::vital::algo::analyze_tracks

A class for outputting various debug info about feature tracks.

Public Functions

PLUGIN_INFO ("ocv", "Use OpenCV to analyze statistics of feature tracks.") analyze_tracks(): Constructor.

virtual ~analyze_tracks(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s currently configuration is valid.

virtual void print_info(vital::track_set_sptr track_set, stream_t &stream = std::cout) const

Output various information about the tracks stored in the input set.

Parameters:

track_set – [in] the tracks to analyze
stream – [in] an output stream to write data onto

class priv

Private implementation class.

Public Functions

inline priv(): Constructor.

inline ~priv(): Destructor.

Public Members

bool output_summary: Text output parameters.

Detect Features Algorithm

class detect_features : public kwiver::vital::algo::detect_features

OCV Specific base definition for algorithms that detect feature points

This extended algorithm_def provides a common implementation for the detect method.

Subclassed by kwiver::arrows::ocv::detect_features_BRISK, kwiver::arrows::ocv::detect_features_FAST, kwiver::arrows::ocv::detect_features_GFTT, kwiver::arrows::ocv::detect_features_MSER, kwiver::arrows::ocv::detect_features_ORB, kwiver::arrows::ocv::detect_features_STAR, kwiver::arrows::ocv::detect_features_simple_blob

Public Functions

virtual vital::feature_set_sptr detect(vital::image_container_sptr image_data, vital::image_container_sptr mask = vital::image_container_sptr()) const

Extract a set of image features from the provided image.

Extract a set of image features from the provided image

A given mask image should be one-channel (mask->depth() == 1). If the given mask image has more than one channel, only the first will be considered.

Parameters:

image_data – contains the image data to process
mask – Mask image where regions of positive values (boolean true) indicate regions to consider. Only the first channel will be considered.

Returns:

a set of image features

Detect Features AGAST Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::detect_features_AGAST” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Detect Features FAST Algorithm

class detect_features_FAST : public kwiver::arrows::ocv::detect_features 

Public Functions

PLUGIN_INFO ("ocv_FAST", "OpenCV feature detection via the FAST algorithm") detect_features_FAST(): Constructor.

virtual ~detect_features_FAST(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration vital::config_block is valid.

virtual vital::feature_set_sptr detect(vital::image_container_sptr image_data, vital::image_container_sptr mask = vital::image_container_sptr()) const

Extract a set of image features from the provided image.

Extract a set of image features from the provided image

A given mask image should be one-channel (mask->depth() == 1). If the given mask image has more than one channel, only the first will be considered. This method overrides the base detect method and adds dynamic threshold adaptation. It adjusts the detector’s feature strength threshold to try and extract a target number of features in each frame. Because scene content varies between images, different feature strength thresholds may be necessary to get the same number of feautres in different images.

Parameters:

image_data – contains the image data to process
mask – Mask image where regions of positive values (boolean true) indicate regions to consider. Only the first channel will be considered.

Returns:

a set of image features

class priv

Public Functions

inline priv(): Constructor.

inline cv::Ptr<cv::FastFeatureDetector> create() const: Create a new FAST detector instance with the current parameter values.

inline void update(cv::Ptr<cv::FeatureDetector> detector) const: Update the parameters of the given detector with the currently set values.

inline void update_config(config_block_sptr config) const: Update given config block with currently set parameter values.

inline void set_config(config_block_sptr const &config): Set parameter values based on given config block.

inline bool check_config(vital::config_block_sptr const &config, logger_handle_t const &logger) const: Check config parameter values.

Detect Features GFTT Algorithm

class detect_features_GFTT : public kwiver::arrows::ocv::detect_features 

Public Functions

PLUGIN_INFO ("ocv_GFTT", "OpenCV feature detection via the GFTT algorithm") detect_features_GFTT(): Constructor.

virtual ~detect_features_GFTT(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration vital::config_block is valid.

class priv

Public Functions

inline priv(): Constructor.

inline cv::Ptr<cv::GFTTDetector> create() const: Create a new GFTT detector instance with the current parameter values.

inline void update_config(config_block_sptr config) const: Update given config block with currently set parameter values.

inline void set_config(config_block_sptr const &config): Set parameter values based on given config block.

Public Members

int max_corners: Parameters.

Detect Features MSD Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::detect_features_MSD” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Detect Features MSER Algorithm

class detect_features_MSER : public kwiver::arrows::ocv::detect_features 

Public Functions

PLUGIN_INFO ("ocv_MSER", "OpenCV feature detection via the MSER algorithm") detect_features_MSER(): Constructor.

virtual ~detect_features_MSER(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration vital::config_block is valid.

class priv

Public Functions

inline priv(): Constructor.

inline void update_config(config_block_sptr config) const: Update given config block with currently set parameter values.

inline void set_config(config_block_sptr const &c): Set parameter values based on given config block.

inline bool check_config(vital::config_block_sptr const &c, logger_handle_t const &logger) const: Check config parameter values.

Public Members

int delta: Parameters.

Detect Features Simple BLOB Algorithm

class detect_features_simple_blob : public kwiver::arrows::ocv::detect_features 

Public Functions

PLUGIN_INFO ("ocv_simple_blob", "OpenCV feature detection via the simple_blob algorithm.") detect_features_simple_blob(): Constructor.

virtual ~detect_features_simple_blob(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration vital::config_block is valid.

class priv

Public Functions

inline priv(): Constructor.

inline cv::Ptr<cv::SimpleBlobDetector> create() const: Create new algorithm based on current parameter values.

inline void update_config(config_block_sptr config) const: Update config block with current parameters and values.

inline void set_config(config_block_sptr config): Set the current parameter values based on the given config block.

Detect Features STAR Algorithm

class detect_features_STAR : public kwiver::arrows::ocv::detect_features 

Public Functions

PLUGIN_INFO ("ocv_STAR", "OpenCV feature detection via the STAR algorithm") detect_features_STAR(): Constructor.

virtual ~detect_features_STAR(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration config_block is valid.

class priv

Draw Detected Object Set Algorithm

class draw_detected_object_set : public kwiver::vital::algo::draw_detected_object_set 

An abstract base class for algorithms which draw tracks on top of images in various ways, for analyzing results.

Public Functions

virtual vital::config_block_sptr get_configuration() const

Get this algorithm’s configuration block

This method returns the required configuration for the algorithm. The implementation of this method should be light-weight and only create and fill in the config block.

This base virtual function implementation returns an empty configuration.

Get this alg’s configuration block

Returns:: config_block containing the configuration for this algorithm and any nested components.

virtual void set_configuration(vital::config_block_sptr config)

Set this algorithm’s properties via a config block

This method is called to pass a configuration to the algorithm. The implementation of this method should be light-weight and only save the necessary config values. Defer any substantial processing in another method.

Throws:

no_such_configuration_value_exception – Thrown if an expected configuration value is not present.
algorithm_configuration_exception – Thrown when the algorithm is given an invalid config_block or is otherwise unable to configure itself.

Parameters:

config – The config_block instance containing the configuration parameters for this algorithm

virtual bool check_configuration(vital::config_block_sptr config) const

Check that the algorithm’s configuration config_block is valid

This checks solely within the provided config_block and not against the current state of the instance. This isn’t static for inheritance reasons.

Parameters:: config – The config block to check configuration of.
Returns:: true if the configuration check passed and false if it didn’t.

virtual kwiver::vital::image_container_sptr draw(kwiver::vital::detected_object_set_sptr detected_set, kwiver::vital::image_container_sptr image)

Draw detected object boxes om image.

Parameters:

detected_set – Set of detected objects
image – Boxes are drawn in this image

Returns:

Image with boxes and other annotations added.

class priv

Public Functions

inline void draw_box(cv::Mat &image, const vital::detected_object_sptr dos, std::string label, double prob, bool just_text = false, int offset_index = 0) const

Draw a box on an image.

This method draws a box on an image for the bounding box from a detected object.

When drawing a box with multiple class names, draw the first class_name with the just_text parameter false and all subsequent calls with it set to true. Also the offset parameter must be incremented so the labels do not overwrite.

Parameters:

image – [inout] Input image updated with drawn box
dos – [in] detected object with bounding box
label – [in] Text label to use for box
prob – [in] Probability value to add to label text
just_text – [in] Set to true if only draw text, not the bounding box. This is used when there are multiple labels for the same detection.
offset – [in] How much to offset text fill box from text baseline. This is used to offset labels when there are more than one label for a detection.

inline vital::image_container_sptr draw_detections(vital::image_container_sptr image_data, vital::detected_object_set_sptr in_set) const

Draw detected object on image.

This method draws the detections on a copy of the supplied image. The detections are drawn in confidence order up to the threshold. For each detection, the most likely class_name is optionally displayed below the box.

Parameters:

image_data – The image to draw on.
input_set – List of detections to draw.

Returns:

New image with boxes drawn.

inline bool name_selected(std::string const &name) const

See if name has been selected for display.

Parameters:: name – Name to check.
Returns:: true if name should be rendered

struct Bound_Box_Params

Draw Tracks Algorithm

class draw_tracks : public kwiver::vital::algo::draw_tracks

A class for drawing various information about feature tracks.

Public Functions

PLUGIN_INFO ("ocv", "Use OpenCV to draw tracked features on the images.") draw_tracks(): Constructor.

virtual ~draw_tracks(): Destructor.

virtual vital::config_block_sptr get_configuration() const

Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s currently configuration is valid.

virtual vital::image_container_sptr draw(vital::track_set_sptr display_set, vital::image_container_sptr_list image_data, vital::track_set_sptr comparison_set = vital::track_set_sptr())

Output images with tracked features drawn on them.

Draw features tracks on top of the input images.

This process can either be called in an offline fashion, where all tracks and images are provided to the function on the first call, or in an online fashion where only new images are provided on sequential calls. This function can additionally consumes a second track set for which can optionally be used to display additional information to provide a comparison between the two track sets.

Parameters:

display_set – [in] the main track set to draw
image_data – [in] a list of images the tracks were computed over
comparison_set – [in] optional comparison track set

Returns:

a pointer to the last image generated

class priv

Private implementation class.

Public Functions

inline priv(): Constructor.

inline ~priv(): Destructor.

Public Members

bool draw_track_ids: Parameters.

std::deque<cv::Mat> buffer: Internal variables.

Estimate Fundamental Matrix Algorithm

class estimate_fundamental_matrix : public kwiver::vital::algo::estimate_fundamental_matrix

A class that using OpenCV to estimate a fundamental matrix from matching 2D points.

Public Functions

PLUGIN_INFO ("ocv", "Use OpenCV to estimate a fundimental matrix from feature matches.") estimate_fundamental_matrix(): Constructor.

virtual ~estimate_fundamental_matrix(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration config_block is valid.

virtual vital::fundamental_matrix_sptr estimate(const std::vector<vital::vector_2d> &pts1, const std::vector<vital::vector_2d> &pts2, std::vector<bool> &inliers, double inlier_scale = 3.0) const

Estimate a fundamental matrix from corresponding points

If estimation fails, a NULL-containing sptr is returned

Parameters:

pts1 – [in] the vector or corresponding points from the source image
pts2 – [in] the vector of corresponding points from the destination image
inliers – [out] for each point pair, the value is true if this pair is an inlier to the fundamental matrix estimate
inlier_scale – [in] error distance tolerated for matches to be inliers

Estimate Homography Algorithm

class estimate_homography : public kwiver::vital::algo::estimate_homography: A class that using OpenCV to estimate a homography from matching 2D points.

Extract Descriptors Algorithm

class extract_descriptors : public kwiver::vital::algo::extract_descriptors

OCV specific definition for algorithms that describe feature points

This extended algorithm_def provides a common implementation for the extract method.

Subclassed by kwiver::arrows::ocv::extract_descriptors_BRIEF, kwiver::arrows::ocv::extract_descriptors_BRISK, kwiver::arrows::ocv::extract_descriptors_FREAK, kwiver::arrows::ocv::extract_descriptors_ORB

Public Functions

virtual vital::descriptor_set_sptr extract(vital::image_container_sptr image_data, vital::feature_set_sptr &features, vital::image_container_sptr image_mask = vital::image_container_sptr()) const

Extract from the image a descriptor corresponding to each feature.

Extract from the image a descriptor corresponding to each feature

Parameters:

image_data – contains the image data to process
features – the feature locations at which descriptors are extracted

Returns:

a set of feature descriptors

Extract Descriptors BRIEF Algorithm

class extract_descriptors_BRIEF : public kwiver::arrows::ocv::extract_descriptors 

Public Functions

PLUGIN_INFO ("ocv_BRIEF", "OpenCV feature-point descriptor extraction via the BRIEF algorithm") extract_descriptors_BRIEF(): Constructor.

virtual ~extract_descriptors_BRIEF(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration config_block is valid.

class priv

Public Functions

inline priv(): Constructor.

inline cv::Ptr<cv_BRIEF_t> create() const: Create new algorithm instance using current parameter values.

inline void update(cv::Ptr<cv_BRIEF_t> descriptor) const: Update given algorithm using current parameter values.

Extract Descriptors DAISY Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::extract_descriptors_DAISY” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Extract Descriptors FREAK Algorithm

class extract_descriptors_FREAK : public kwiver::arrows::ocv::extract_descriptors 

Public Functions

PLUGIN_INFO ("ocv_FREAK", "OpenCV feature-point descriptor extraction via the FREAK algorithm") extract_descriptors_FREAK(): Constructor.

extract_descriptors_FREAK(extract_descriptors_FREAK const &other)

Constructor.

Copy Constructor

Parameters:: other – The other FREAK descriptor extractor to copy

virtual ~extract_descriptors_FREAK(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration config_block is valid.

class priv

Public Functions

inline priv(): Constructor.

inline cv::Ptr<cv_FREAK_t> create() const: Create new cv::Ptr algo instance.

inline void update(cv::Ptr<cv_FREAK_t> freak) const: Update algorithm instance with current parameter values.

inline void update_config(vital::config_block_sptr &config) const: Set current parameter values to the given config block.

inline void set_config(vital::config_block_sptr const &config): Set our parameters based on the given config block.

Public Members

bool orientation_normalized: Params.

Extract Descriptors LATCH Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::extract_descriptors_LATCH” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Extract Descriptors LUCID Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::extract_descriptors_LUCID” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Extrack Descriptors BRISK Algorithm

class extract_descriptors_BRISK : public kwiver::arrows::ocv::extract_descriptors 

Detect Features BRISK Algorithm

class detect_features_BRISK : public kwiver::arrows::ocv::detect_features 

Extrack Descriptors ORB Algorithm

class extract_descriptors_ORB : public kwiver::arrows::ocv::extract_descriptors 

Detect Features ORB Algorithm

class detect_features_ORB : public kwiver::arrows::ocv::detect_features 

Extrack Descriptors SIFT Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::extract_descriptors_SIFT” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Detect Features SIFT Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::detect_features_SIFT” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Extrack Descriptors SURF Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::extract_descriptors_SURF” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Detect Features SURF Algorithm

Warning

doxygenclass: Cannot find class “kwiver::arrows::ocv::detect_features_SURF” in doxygen xml output for project “kwiver” from directory: ./_build/xml

Hough Circle Detector Algorithm

class hough_circle_detector : public kwiver::vital::algo::image_object_detector 

Public Functions

virtual vital::config_block_sptr get_configuration() const

Get this algorithm’s configuration block

This method returns the required configuration for the algorithm. The implementation of this method should be light-weight and only create and fill in the config block.

This base virtual function implementation returns an empty configuration.

Get this alg’s configuration block

Returns:: config_block containing the configuration for this algorithm and any nested components.

virtual void set_configuration(vital::config_block_sptr config)

Set this algorithm’s properties via a config block

This method is called to pass a configuration to the algorithm. The implementation of this method should be light-weight and only save the necessary config values. Defer any substantial processing in another method.

Throws:

no_such_configuration_value_exception – Thrown if an expected configuration value is not present.
algorithm_configuration_exception – Thrown when the algorithm is given an invalid config_block or is otherwise unable to configure itself.

Parameters:

config – The config_block instance containing the configuration parameters for this algorithm

virtual bool check_configuration(vital::config_block_sptr config) const

Check that the algorithm’s configuration config_block is valid

This checks solely within the provided config_block and not against the current state of the instance. This isn’t static for inheritance reasons.

Parameters:: config – The config block to check configuration of.
Returns:: true if the configuration check passed and false if it didn’t.

virtual vital::detected_object_set_sptr detect(vital::image_container_sptr image_data) const

Find all objects on the provided image

This method analyzes the supplied image and along with any saved context, returns a vector of detected image objects.

Parameters:: image_data – the image pixels
Returns:: vector of image objects found

class priv

Image Container Algorithm

class image_container : public kwiver::vital::image_container 

This image container wraps a cv::Mat.

Public Functions

explicit image_container(const cv::Mat &d, ColorMode cm): Constructor - from a cv::Mat.

inline explicit image_container(const vital::image &vital_image): Constructor - convert kwiver image to cv::Mat.

explicit image_container(const vital::image_container &image_cont): Constructor - convert base image container to cv::Mat.

inline image_container(const arrows::ocv::image_container &other): Copy Constructor.

virtual size_t size() const

The size of the image data in bytes

This size includes all allocated image memory, which could be larger than width*height*depth.

inline virtual size_t width() const: The width of the image in pixels.

inline virtual size_t height() const: The height of the image in pixels.

inline virtual size_t depth() const: The depth (or number of channels) of the image.

inline virtual vital::image get_image() const: Get an in-memory image class to access the data.

inline cv::Mat get_Mat() const: Access the underlying cv::Mat data structure.

Public Static Functions

static vital::image ocv_to_vital(const cv::Mat &img, ColorMode cm)

Convert an OpenCV cv::Mat to a VITAL image

This function constructs a vital::image from a cv::Mat and wraps the same memory. If the memory is owned by the cv::Mat this function will use a mat_image_memory class to retain the original memory and reference counting. If the cv::Mat does not own the memory, the vital::image will point to the same memory but also not take ownership. That is vital::image::memory() will return nullptr.

static vital::image_pixel_traits ocv_to_vital(int type): Convert an OpenCV cv::Mat type value to a vital::image_pixel_traits.

static cv::Mat vital_to_ocv(const vital::image &img, ColorMode cm)

Convert a VITAL image to an OpenCV cv::Mat

This function constructs a cv::Mat from a vital::image and wraps the same memory whenever possible. If the vital::image contains a mat_image_memory then the image data was originally created as a cv::Mat and this function will reconstruct the cv::Mat using the original memory and reference counting, if possible. If the vital::image does not own its memory, then the wrapped cv::Mat will also not own the memory.

The supported memory layouts are far more restricted in cv::Mat than in vital::image. If the image is not of a compatible type and cannot be directly wrapped then the a new cv::Mat is allocated and the image is deep copied. The same is true if the user requests a color mode other than the default BGR used by OpenCV. The data will be copied into new memory and the color is converted.

static int vital_to_ocv(const vital::image_pixel_traits &pt): Convert a vital::image_pixel_traits to an OpenCV cv::Mat type integer.

Image I/O Algorithm

class image_io : public kwiver::vital::algo::image_io 

A class for using OpenCV to read and write images.

Public Functions

virtual kwiver::vital::metadata_sptr load_metadata_(std::string const &filename) const

Implementation specific metadata functionality.

Load image metadata from the file

Parameters:

filename – the path to the file to read
filename – the path to the file to read

Returns:

pointer to the loaded metadata

Returns:

pointer to the loaded metadata

Match Features Algorithm

class match_features : public kwiver::vital::algo::match_features

OCV specific definition for algorithms that match feature point descriptors

This extended algorithm_def provides a common implementation for the match method.

Subclassed by kwiver::arrows::ocv::match_features_bruteforce, kwiver::arrows::ocv::match_features_flannbased

Public Functions

virtual vital::match_set_sptr match(vital::feature_set_sptr feat1, vital::descriptor_set_sptr desc1, vital::feature_set_sptr feat2, vital::descriptor_set_sptr desc2) const

Match one set of features and corresponding descriptors to another

Parameters:

feat1 – the first set of features to match
desc1 – the descriptors corresponding to feat1
feat2 – the second set fof features to match
desc2 – the descriptors corresponding to feat2

Returns:

a set of matching indices from feat1 to feat2

Match Features Bruteforce Algorithm

class match_features_bruteforce : public kwiver::arrows::ocv::match_features 

Feature matcher implementation using OpenCV’s brute-force feature matcher.

Public Functions

PLUGIN_INFO ("ocv_brute_force", "OpenCV feature matcher using brute force matching (exhaustive search).") match_features_bruteforce(): Constructor.

virtual ~match_features_bruteforce(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration vital::config_block is valid.

class priv

Public Functions

inline void create(): Create a new brute-force matcher instance and set our matcher param to it.

Public Members

int norm_type: Parameters.

Match Features Flannbased Algorithm

class match_features_flannbased : public kwiver::arrows::ocv::match_features 

Feature matcher implementation using OpenCV’s FLANN-based feature matcher.

Public Functions

PLUGIN_INFO ("ocv_flann_based", "OpenCV feature matcher using FLANN (Approximate Nearest Neighbors).") match_features_flannbased(): Constructor.

virtual ~match_features_flannbased(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s configuration vital::config_block is valid.

class priv

Public Functions

inline priv(): Constructor.

inline void create(): Create a new flann-based matcher instance and set our matcher param to it.

inline void cross_check_match(const cv::Mat &descriptors1, const cv::Mat &descriptors2, std::vector<cv::DMatch> &filtered_matches12) const

Compute descriptor matching from 1 to 2 and from 2 to 1.

Only return descriptor matches if the one of the top N matches from 1 to 2 is also a top N match from 2 to 1. Here N is defined by parameter cross_check_knn

Public Members

bool cross_check: Parameters.

Refine Detections Write To Disk Algorithm

class refine_detections_write_to_disk : public kwiver::vital::algo::refine_detections

A class for drawing various information about feature tracks.

Public Functions

PLUGIN_INFO ("ocv_write", "Debugging process for writing out detections") refine_detections_write_to_disk(): Constructor.

virtual ~refine_detections_write_to_disk(): Destructor.

virtual vital::config_block_sptr get_configuration() const: Get this algorithm’s configuration block .

virtual void set_configuration(vital::config_block_sptr config): Set this algorithm’s properties via a config block.

virtual bool check_configuration(vital::config_block_sptr config) const: Check that the algorithm’s currently configuration is valid.

virtual vital::detected_object_set_sptr refine(vital::image_container_sptr image_data, vital::detected_object_set_sptr detections) const

Refine all object detections on the provided image

This method analyzes the supplied image and and detections on it, returning a refined set of detections.

Parameters:

image_data – the image pixels
detections – detected objects

Returns:

vector of image objects refined

class priv

Split Image Algorithm

class split_image : public kwiver::vital::algo::split_image 

A class for writing out image chips around detections, useful as a debugging process for ensuring that the refine detections process is running on desired ROIs.

Public Functions

PLUGIN_INFO ("ocv", "Split an image into multiple smaller images using opencv functions") split_image(): Constructor.

virtual ~split_image(): Destructor.

inline virtual void set_configuration(kwiver::vital::config_block_sptr)

Set this algorithm’s properties via a config block

This method is called to pass a configuration to the algorithm. The implementation of this method should be light-weight and only save the necessary config values. Defer any substantial processing in another method.

Throws:

no_such_configuration_value_exception – Thrown if an expected configuration value is not present.
algorithm_configuration_exception – Thrown when the algorithm is given an invalid config_block or is otherwise unable to configure itself.

Parameters:

config – The config_block instance containing the configuration parameters for this algorithm

inline virtual bool check_configuration(kwiver::vital::config_block_sptr config) const

Check that the algorithm’s configuration config_block is valid

This checks solely within the provided config_block and not against the current state of the instance. This isn’t static for inheritance reasons.

Parameters:: config – The config block to check configuration of.
Returns:: true if the configuration check passed and false if it didn’t.

virtual std::vector<kwiver::vital::image_container_sptr> split(kwiver::vital::image_container_sptr img) const: Split image.