frameworks.ultralytics.services.model.logger.object_detection

object_detection

Classes:

Name	Description
UltralyticsObjectDetectionMetricMapping	Defines the metric mapping for object detection tasks using the Ultralytics framework.
UltralyticsObjectDetectionLogger	Logger for Ultralytics-based object detection models.

UltralyticsObjectDetectionMetricMapping()

Bases: UltralyticsBaseMetricMapping

              flowchart TD
              picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionMetricMapping[UltralyticsObjectDetectionMetricMapping]
              picsellia_cv_engine.frameworks.ultralytics.services.model.logger.base.UltralyticsBaseMetricMapping[UltralyticsBaseMetricMapping]
              picsellia_cv_engine.core.services.model.logging.base_logger.MetricMapping[MetricMapping]

                              picsellia_cv_engine.frameworks.ultralytics.services.model.logger.base.UltralyticsBaseMetricMapping --> picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionMetricMapping
                                picsellia_cv_engine.core.services.model.logging.base_logger.MetricMapping --> picsellia_cv_engine.frameworks.ultralytics.services.model.logger.base.UltralyticsBaseMetricMapping
                



              click picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionMetricMapping href "" "picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionMetricMapping"
              click picsellia_cv_engine.frameworks.ultralytics.services.model.logger.base.UltralyticsBaseMetricMapping href "" "picsellia_cv_engine.frameworks.ultralytics.services.model.logger.base.UltralyticsBaseMetricMapping"
              click picsellia_cv_engine.core.services.model.logging.base_logger.MetricMapping href "" "picsellia_cv_engine.core.services.model.logging.base_logger.MetricMapping"
            

Defines the metric mapping for object detection tasks using the Ultralytics framework.

This mapping class registers framework-specific metric names and their corresponding standard names for both training and validation phases. It includes loss components, label metrics, and evaluation metrics.

Sets up metric associations for box loss, classification loss, distribution focal loss (DFL), precision, recall, and mAP values.

Methods:

Name	Description
add_metric	Add a metric to the specified phase.
get_mapping	Get mapping of framework names to standard names for a given phase.

Attributes:

Name	Type	Description
mappings	dict[str, list[Metric]]

mappings = {'train': [], 'val': [], 'test': []} instance-attribute

add_metric(phase, metric)

Add a metric to the specified phase.

Parameters:

Name	Type	Description	Default
phase	str	One of 'train', 'val', or 'test'.	required
metric	Metric	The metric to register.	required

get_mapping(phase=None)

Get mapping of framework names to standard names for a given phase.

Parameters:

Name	Type	Description	Default
phase	str | None	One of 'train', 'val', 'test'.	None

Returns:

Name	Type	Description
dict	dict[str, str]	Mapping of metric names.

UltralyticsObjectDetectionLogger(experiment, metric_mapping)

Bases: BaseLogger

              flowchart TD
              picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionLogger[UltralyticsObjectDetectionLogger]
              picsellia_cv_engine.core.services.model.logging.base_logger.BaseLogger[BaseLogger]

                              picsellia_cv_engine.core.services.model.logging.base_logger.BaseLogger --> picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionLogger
                


              click picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionLogger href "" "picsellia_cv_engine.frameworks.ultralytics.services.model.logger.object_detection.UltralyticsObjectDetectionLogger"
              click picsellia_cv_engine.core.services.model.logging.base_logger.BaseLogger href "" "picsellia_cv_engine.core.services.model.logging.base_logger.BaseLogger"
            

Logger for Ultralytics-based object detection models.

This logger uses an UltralyticsObjectDetectionMetricMapping to normalize metric names and logs them to a Picsellia experiment during training and validation phases.

Parameters:

Name	Type	Description	Default
experiment	Experiment	The experiment object used for logging.	required
metric_mapping	UltralyticsObjectDetectionMetricMapping	Mapping for translating framework-specific metrics.	required

Methods:

Name	Description
log_metric	Log a metric value (e.g. for line plot).
log_value	Log a scalar value (e.g., accuracy score).
log_image	Log an image file.
log_confusion_matrix	Log a confusion matrix as a heatmap.
log_table	Log a table (either a key-value dict or 2D matrix).
get_log_name	Construct log name with optional phase and mapped name.

Attributes:

Name	Type	Description
experiment
metric_mapping

experiment = experiment instance-attribute

metric_mapping = metric_mapping instance-attribute

log_metric(name, value, log_type=LogType.LINE, phase=None)

Log a metric value (e.g. for line plot).

Parameters:

Name	Type	Description	Default
name	str	Metric name.	required
value	float	Metric value.	required
log_type	LogType	Logging type (default LINE).	LINE
phase	str | None	Phase name.	None

log_value(name, value, phase=None, precision=4)

Log a scalar value (e.g., accuracy score).

Parameters:

Name	Type	Description	Default
name	str	Metric name.	required
value	float	Value to log.	required
phase	str | None	Phase name.	None
precision	int	Decimal precision to round.	4

log_image(name, image_path, phase=None)

Log an image file.

Parameters:

Name	Type	Description	Default
name	str	Log name.	required
image_path	str	Path to image.	required
phase	str | None	Phase name.	None

log_confusion_matrix(name, labelmap, matrix, phase=None)

Log a confusion matrix as a heatmap.

Parameters:

Name	Type	Description	Default
name	str	Log name.	required
labelmap	dict	Mapping of label indices to names.	required
matrix	ndarray	Confusion matrix.	required
phase	str | None	Phase name.	None

log_table(name, data, phase=None)

Log a table (either a key-value dict or 2D matrix).

Parameters:

Name	Type	Description	Default
name	str	Log name.	required
data	dict	Data to log.	required
phase	str | None	Phase name.	None

get_log_name(metric_name, phase=None)

Construct log name with optional phase and mapped name.

Parameters:

Name	Type	Description	Default
metric_name	str	Base metric name.	required
phase	str | None	Optional phase.	None

Returns:

Name	Type	Description
str	str	Full log name.