def GenerateProposalLabels(self, blobs_in):
"""Op for generating training labels for RPN proposals. This is used
when training RPN jointly with Fast/Mask R-CNN (as in end-to-end
Faster R-CNN training).
blobs_in:
- 'rpn_rois': 2D tensor of RPN proposals output by GenerateProposals
- 'roidb': roidb entries that will be labeled
- 'im_info': See GenerateProposals doc.
blobs_out:
- (variable set of blobs): returns whatever blobs are required for
training the model. It does this by querying the data loader for
the list of blobs that are needed.
"""
name = 'GenerateProposalLabelsOp:' + ','.join(
[str(b) for b in blobs_in])
# The list of blobs is not known before run-time because it depends on
# the specific model being trained. Query the data loader to get the
# list of output blob names.
blobs_out = fast_rcnn_roi_data.get_fast_rcnn_blob_names(
is_training=self.train)
blobs_out = [core.ScopedBlobReference(b) for b in blobs_out]
self.net.Python(GenerateProposalLabelsOp().forward)(blobs_in,
blobs_out,
name=name)
return blobs_out
def GenerateProposalLabels(self, blobs_in):
name = 'GenerateProposalLabelsOp:' + ','.join(
[str(b) for b in blobs_in])
# The list of blobs is not known before run-time because it depends on
# the specific model being trained. Query the data loader to get the
# list of output blob names.
blobs_out = fast_rcnn_roi_data.get_fast_rcnn_blob_names(
is_training=self.train)
blobs_out = [core.ScopedBlobReference(b) for b in blobs_out]
self.net.Python(GenerateProposalLabelsOp().forward)(blobs_in,
blobs_out,
name=name)
return blobs_out
