BatchParameters Class Reference

Structure containing a set of parameters for batch object detection. More...

Functions
	BatchParameters (bool enable=false, float id_retention_time=240.f, float batch_duration=2.f)
	Default constructor. More...
bool	save (String filename) const
	Saves the current set of parameters into a file to be reloaded with the load() method. More...
bool	load (String filename)
	Loads a set of parameters from the values contained in a previously saved file. More...
bool	encode (String &serialized_content) const
	Generate a JSON Object (with the struct type as a key) containing the serialized struct, converted into a string. More...
bool	decode (const String &serialized_content)
	Fill the structure from the serialized json object contained in the input string. More...
bool	operator== (const BatchParameters &param1) const
bool	operator!= (const BatchParameters &param1) const

Attributes
bool	enable = false
	Whether to enable the batch option in the object detection module. More...
float	id_retention_time = 240
	Max retention time in seconds of a detected object. More...
float	latency = 2.f
	Trajectories will be output in batch with the desired latency in seconds. More...

Detailed Description

Structure containing a set of parameters for batch object detection.

The default constructor sets all parameters to their default settings.

Note

Parameters can be adjusted by the user.

Constructor and Destructor

BatchParameters()

BatchParameters	(	bool	enable = false,
		float	id_retention_time = 240.f,
		float	batch_duration = 2.f
	)

Default constructor.

All the parameters are set to their default values.

Functions

save()

bool save

(

String

filename

)

const

Saves the current set of parameters into a file to be reloaded with the load() method.

Parameters

filename

: Name of the file which will be created to store the parameters (extension '.json' will be added if not set).

Returns

True if the file was successfully saved, otherwise false.

Warning

For security reasons, the file must not already exist.

In case a file already exists, the method will return false and existing file will not be updated.

load()

bool load

(

String

filename

)

Loads a set of parameters from the values contained in a previously saved file.

Parameters

filename

: Path to the file from which the parameters will be loaded (extension '.json' will be added at the end of the filename if not detected).

Returns

True if the file was successfully loaded, otherwise false.

encode()

bool encode

(

String &

serialized_content

)

const

Generate a JSON Object (with the struct type as a key) containing the serialized struct, converted into a string.

Parameters

serialized_content

output string containing the JSON Object

Returns

True if file was successfully saved, otherwise false.

decode()

bool decode

(

const String &

serialized_content

)

Fill the structure from the serialized json object contained in the input string.

Parameters

serialized_content

input string containing the JSON Object

Returns

True if the decoding was successful, otherwise false.

operator==()

bool operator==

(

const BatchParameters &

param1

)

const

Comparison operator ==

Parameters

param1

to compare

Returns

true if the two struct are identical

operator!=()

bool operator!=

(

const BatchParameters &

param1

)

const

Comparison operator !=

Parameters

param1

to compare

Returns

true if the two struct are different

Variables

enable

bool enable = false

Whether to enable the batch option in the object detection module.

Batch queueing system provides:

• deep-learning based re-identification
• trajectory smoothing and filtering

Note

To activate this option, enable must be set to true.

id_retention_time

float id_retention_time = 240

Max retention time in seconds of a detected object.

After this time, the same object will mostly have a different id.

latency

float latency = 2.f

Trajectories will be output in batch with the desired latency in seconds.

During this waiting time, re-identification of objects is done in the background.

Note

Specifying a short latency will limit the search (falling in timeout) for previously seen object ids but will be closer to real time output.

Specifying a long latency will reduce the change of timeout in re-identification but increase difference with live output.