fiftyone.utils.eval.coco.COCODetectionResults

class documentation

class COCODetectionResults(DetectionResults): (source)

Constructor: COCODetectionResults(samples, config, eval_key, matches, ...)

Class that stores the results of a COCO detection evaluation.

Parameters
samples	the `fiftyone.core.collections.SampleCollection` used
config	the `COCOEvaluationConfig` used
eval_key	the evaluation key
matches	a list of `(gt_label, pred_label, iou, pred_confidence, gt_id, pred_id)` matches. Either label can be `None` to indicate an unmatched object
precision	an array of precision values of shape `num_iou_threshs x num_classes x num_recall`
recall	an array of recall values
iou_threshs	an array of IoU thresholds
classes	the list of possible classes
recall_sweep	an array of recall values of shape `num_iou x num_classes`
thresholds	an optional array of decision thresholds of shape `num_iou_threshs x num_classes x num_recall`
missing	a missing label string. Any unmatched objects are given this label for evaluation purposes
custom_metrics	an optional dict of custom metrics
backend	a `COCOEvaluation` backend

Method	`__init__`	Undocumented
Method	`mAP`	Computes COCO-style mean average precision (mAP) for the specified classes.
Method	`mAR`	Computes COCO-style mean average recall (mAR) for the specified classes.
Method	`plot_pr_curves`	Plots precision-recall (PR) curves for the results.
Instance Variable	`iou_threshs`	Undocumented
Instance Variable	`precision`	Undocumented
Instance Variable	`recall`	Undocumented
Instance Variable	`recall_sweep`	Undocumented
Instance Variable	`thresholds`	Undocumented
Class Method	`_from_dict`	Subclass implementation of `from_dict`.
Method	`_get_class_index`	Undocumented
Method	`_get_iou_thresh_inds`	Undocumented
Instance Variable	`_classwise_AP`	Undocumented
Instance Variable	`_classwise_AR`	Undocumented

Inherited from DetectionResults:

Instance Variable ious Undocumented

Inherited from BaseClassificationResults (via DetectionResults):

Method	`confusion_matrix`	Generates a confusion matrix for the results via `sklearn:sklearn.metrics.confusion_matrix`.
Method	`metrics`	Computes classification metrics for the results, including accuracy, precision, recall, and F-beta score.
Method	`plot_confusion_matrix`	Plots a confusion matrix for the evaluation results.
Method	`print_metrics`	Prints the metrics computed via `metrics`.
Method	`print_report`	Prints a classification report for the results via `sklearn:sklearn.metrics.classification_report`.
Method	`report`	Generates a classification report for the results via `sklearn:sklearn.metrics.classification_report`.
Instance Variable	`confs`	Undocumented
Instance Variable	`weights`	Undocumented
Instance Variable	`ypred`	Undocumented
Instance Variable	`ypred_ids`	Undocumented
Instance Variable	`ytrue`	Undocumented
Instance Variable	`ytrue_ids`	Undocumented
Method	`_confusion_matrix`	Undocumented
Method	`_parse_classes`	Undocumented

Inherited from BaseEvaluationResults (via DetectionResults, BaseClassificationResults):

Method	`_get_custom_metrics`	Undocumented
Method	`_print_metrics`	Undocumented

Inherited from BaseRunResults (via DetectionResults, BaseClassificationResults, BaseEvaluationResults, EvaluationResults):

Class Method	`from_dict`	Builds a `BaseRunResults` from a JSON dict representation of it.
Static Method	`base_results_cls`	Returns the results class for the given run type.
Method	`attributes`	Returns the list of class attributes that will be serialized by `serialize`.
Method	`save`	Saves the results to the database.
Method	`save_config`	Saves these results config to the database.
Property	`cls`	The fully-qualified name of this `BaseRunResults` class.
Property	`config`	The `BaseRunConfig` for these results.
Property	`key`	The run key for these results.
Property	`samples`	The `fiftyone.core.collections.SampleCollection` associated with these results.
Instance Variable	`_backend`	Undocumented
Instance Variable	`_config`	Undocumented
Instance Variable	`_key`	Undocumented
Instance Variable	`_samples`	Undocumented

def __init__(self, samples, config, eval_key, matches, precision, recall, iou_threshs, classes, recall_sweep=None, thresholds=None, missing=None, custom_metrics=None, backend=None): (source) ¶

overrides fiftyone.utils.eval.detection.DetectionResults.__init__

Undocumented

def mAP(self, classes=None): (source) ¶

Computes COCO-style mean average precision (mAP) for the specified classes.

See this page for more details about COCO-style mAP.

Parameters
classes:`None`	a list of classes for which to compute mAP
Returns
the mAP in `[0, 1]`

def mAR(self, classes=None): (source) ¶

Computes COCO-style mean average recall (mAR) for the specified classes.

See this page for more details about COCO-style mAR.

Parameters
classes:`None`	a list of classes for which to compute mAR
Returns
the mAR in `[0, 1]`

def plot_pr_curves(self, classes=None, iou_thresh=None, backend='plotly', **kwargs): (source) ¶

Plots precision-recall (PR) curves for the results.

Parameters
classes:`None`	a list of classes to generate curves for. By default, the top 3 AP classes will be plotted
iou_thresh:`None`	an optional IoU threshold or list of IoU thresholds for which to plot curves. If multiple thresholds are provided, precision data is averaged across these thresholds. By default, precision data is averaged over all IoU thresholds. Refer to `iou_threshs` to see the available thresholds
backend:"plotly"	the plotting backend to use. Supported values are `("plotly", "matplotlib")`
**kwargs	keyword arguments for the backend plotting method: "plotly" backend: `fiftyone.core.plots.plotly.plot_pr_curves` "matplotlib" backend: `fiftyone.core.plots.matplotlib.plot_pr_curves`
Returns
`one` of the following	a `fiftyone.core.plots.plotly.PlotlyNotebookPlot`, if you are working in a notebook context and the plotly backend is used a plotly or matplotlib figure, otherwise

iou_threshs = (source) ¶

Undocumented

precision = (source) ¶

Undocumented

recall = (source) ¶

Undocumented

recall_sweep: None = (source) ¶

Undocumented

thresholds: None = (source) ¶

Undocumented

@classmethod
def _from_dict(cls, d, samples, config, eval_key, **kwargs): (source) ¶

overrides fiftyone.utils.eval.detection.DetectionResults._from_dict

Subclass implementation of from_dict.

Parameters
d	a JSON dict
samples	the `fiftyone.core.collections.SampleCollection` for the run
config	the `BaseRunConfig` for the run
eval_key	Undocumented
key	the run key
**kwargs	Undocumented
Returns
a `BaseRunResults`

def _get_class_index(self, label): (source) ¶

Undocumented

def _get_iou_thresh_inds(self, iou_thresh=None): (source) ¶

Undocumented

_classwise_AP = (source) ¶

Undocumented

_classwise_AR = (source) ¶

Undocumented