Metrics (empanada.metrics)#
- class empanada.metrics.ComposeMetrics(metrics_dict, class_names, reset_on_print=True)[source]#
Bundles multiple metrics together for easy evaluation, printing and logging during training.
- Parameters
metrics_dict – Dictionary, keys are the names of metrics and values are the _BaseMetric class than records/calculate that metric.
class_names – Dictionary, keys are class_ids and values are names.
reset_on_print – Bool. If True, the history of each metric is wiped after results are printed.
- class empanada.metrics.EMAMeter(momentum=0.98)[source]#
Computes and stores an exponential moving average and current value
- class empanada.metrics.F1(meter, labels, label_divisor, iou_thr=0.5, output_key='pan_seg', target_key='pan_seg', **kwargs)[source]#
Computes the F1 between output and target instance segmentation classes. Input is expected to be a dictionary for each.
- Parameters
meter – EMAMeter or AverageMeter to track
labels – List of all instance labels to compare
label_divisor – Integer. Label divisor used during postprocessing.
iou_thr – Float, IoU threshold at which to determine TP, FP, FN detections.
output_key – Key in the output dictionary to compare.
target_key – Key in the target dictionary to compare.
- class empanada.metrics.IoU(meter, labels, output_key='sem_logits', target_key='sem', **kwargs)[source]#
Computes the IoU between output and target. Input is expected to be a dictionary for each.
- Parameters
meter – EMAMeter or AverageMeter to track.
labels – List of all semantic/instance labels to compare.
output_key – Key in the output dictionary to compare.
target_key – Key in the target dictionary to compare.
- class empanada.metrics.PQ(meter, labels, label_divisor, output_key='pan_seg', target_key='pan_seg', **kwargs)[source]#
Computes the panoptic quality between output and target. Input is expected to be a dictionary for each.
- Parameters
meter – EMAMeter or AverageMeter to track
labels – List of all semantic/instance labels to compare
label_divisor – Integer. Label divisor used during postprocessing.
output_key – Key in the output dictionary to compare.
target_key – Key in the target dictionary to compare.