def deepmac_proto_to_params(deepmac_config):
"""Convert proto to named tuple."""
loss = losses_pb2.Loss()
# Add dummy localization loss to avoid the loss_builder throwing error.
loss.localization_loss.weighted_l2.CopyFrom(
losses_pb2.WeightedL2LocalizationLoss())
loss.classification_loss.CopyFrom(deepmac_config.classification_loss)
classification_loss, _, _, _, _, _, _ = (losses_builder.build(loss))
return DeepMACParams(
dim=deepmac_config.dim,
classification_loss=classification_loss,
task_loss_weight=deepmac_config.task_loss_weight,
pixel_embedding_dim=deepmac_config.pixel_embedding_dim,
allowed_masked_classes_ids=deepmac_config.allowed_masked_classes_ids,
mask_size=deepmac_config.mask_size,
mask_num_subsamples=deepmac_config.mask_num_subsamples,
use_xy=deepmac_config.use_xy,
network_type=deepmac_config.network_type,
use_instance_embedding=deepmac_config.use_instance_embedding,
num_init_channels=deepmac_config.num_init_channels,
predict_full_resolution_masks=deepmac_config.
predict_full_resolution_masks,
postprocess_crop_size=deepmac_config.postprocess_crop_size)
def mask_proto_to_params(mask_config):
"""Converts CenterNet.MaskEstimation proto to parameter namedtuple."""
loss = losses_pb2.Loss()
# Add dummy localization loss to avoid the loss_builder throwing error.
loss.localization_loss.weighted_l2.CopyFrom(
losses_pb2.WeightedL2LocalizationLoss())
loss.classification_loss.CopyFrom(mask_config.classification_loss)
classification_loss, _, _, _, _, _, _ = (losses_builder.build(loss))
return center_net_meta_arch.MaskParams(
classification_loss=classification_loss,
task_loss_weight=mask_config.task_loss_weight,
mask_height=mask_config.mask_height,
mask_width=mask_config.mask_width,
score_threshold=mask_config.score_threshold,
heatmap_bias_init=mask_config.heatmap_bias_init)
def tracking_proto_to_params(tracking_config):
"""Converts CenterNet.TrackEstimation proto to parameter namedtuple."""
loss = losses_pb2.Loss()
# Add dummy localization loss to avoid the loss_builder throwing error.
# TODO(yuhuic): update the loss builder to take the localization loss
# directly.
loss.localization_loss.weighted_l2.CopyFrom(
losses_pb2.WeightedL2LocalizationLoss())
loss.classification_loss.CopyFrom(tracking_config.classification_loss)
classification_loss, _, _, _, _, _, _ = losses_builder.build(loss)
return center_net_meta_arch.TrackParams(
num_track_ids=tracking_config.num_track_ids,
reid_embed_size=tracking_config.reid_embed_size,
classification_loss=classification_loss,
num_fc_layers=tracking_config.num_fc_layers,
task_loss_weight=tracking_config.task_loss_weight)
def object_center_proto_to_params(oc_config):
"""Converts CenterNet.ObjectCenter proto to parameter namedtuple."""
loss = losses_pb2.Loss()
# Add dummy localization loss to avoid the loss_builder throwing error.
# TODO(yuhuic): update the loss builder to take the localization loss
# directly.
loss.localization_loss.weighted_l2.CopyFrom(
losses_pb2.WeightedL2LocalizationLoss())
loss.classification_loss.CopyFrom(oc_config.classification_loss)
classification_loss, _, _, _, _, _, _ = (losses_builder.build(loss))
return center_net_meta_arch.ObjectCenterParams(
classification_loss=classification_loss,
object_center_loss_weight=oc_config.object_center_loss_weight,
heatmap_bias_init=oc_config.heatmap_bias_init,
min_box_overlap_iou=oc_config.min_box_overlap_iou,
max_box_predictions=oc_config.max_box_predictions)
