def build_metrics(self, training: bool = True):
"""Build detection metrics."""
metrics = []
if training:
metric_names = [
'total_loss', 'rpn_score_loss', 'rpn_box_loss',
'frcnn_cls_loss', 'frcnn_box_loss', 'mask_loss', 'model_loss'
]
for name in metric_names:
metrics.append(tf.keras.metrics.Mean(name, dtype=tf.float32))
else:
if self._task_config.use_coco_metrics:
self._build_coco_metrics()
if self._task_config.use_wod_metrics:
# To use Waymo open dataset metrics, please install one of the pip
# package `waymo-open-dataset-tf-*` from
# https://github.com/waymo-research/waymo-open-dataset/blob/master/docs/quick_start.md#use-pre-compiled-pippip3-packages-for-linux
# Note that the package is built with specific tensorflow version and
# will produce error if it does not match the tf version that is
# currently used.
try:
from official.vision.evaluation import wod_detection_evaluator # pylint: disable=g-import-not-at-top
except ModuleNotFoundError:
logging.error(
'waymo-open-dataset should be installed to enable Waymo'
' evaluator.')
raise
self.wod_metric = wod_detection_evaluator.WOD2dDetectionEvaluator(
)
return metrics
def build_metrics(self, training: bool = True):
"""Build detection metrics."""
metrics = []
metric_names = ['total_loss', 'cls_loss', 'box_loss', 'model_loss']
for name in metric_names:
metrics.append(tf.keras.metrics.Mean(name, dtype=tf.float32))
if not training:
if self.task_config.validation_data.tfds_name and self.task_config.annotation_file:
raise ValueError(
"Can't evaluate using annotation file when TFDS is used.")
if self._task_config.use_coco_metrics:
self.coco_metric = coco_evaluator.COCOEvaluator(
annotation_file=self.task_config.annotation_file,
include_mask=False,
per_category_metrics=self.task_config.per_category_metrics)
if self._task_config.use_wod_metrics:
# To use Waymo open dataset metrics, please install one of the pip
# package `waymo-open-dataset-tf-*` from
# https://github.com/waymo-research/waymo-open-dataset/blob/master/docs/quick_start.md#use-pre-compiled-pippip3-packages-for-linux
# Note that the package is built with specific tensorflow version and
# will produce error if it does not match the tf version that is
# currently used.
try:
from official.vision.evaluation import wod_detection_evaluator # pylint: disable=g-import-not-at-top
except ModuleNotFoundError:
logging.error(
'waymo-open-dataset should be installed to enable Waymo'
' evaluator.')
raise
self.wod_metric = wod_detection_evaluator.WOD2dDetectionEvaluator(
)
return metrics