def __build_anchors(anchor_parameters, features):
"""Builds anchors for the shape of the features from FPN.
Args:
anchor_parameters (AnchorParameters): Parameters that determine how
anchors are generated.
features (list): The FPN features.
Returns:
tensor: The anchors for the FPN features.
The shape is:
```
(batch_size, num_anchors, 4)
```
"""
if len(features) == 1:
anchors = Anchors(size=anchor_parameters.sizes[0],
stride=anchor_parameters.strides[0],
ratios=anchor_parameters.ratios,
scales=anchor_parameters.scales,
name='anchors')(features[0])
return anchors
else:
anchors = [
Anchors(size=anchor_parameters.sizes[i],
stride=anchor_parameters.strides[i],
ratios=anchor_parameters.ratios,
scales=anchor_parameters.scales,
name='anchors_{}'.format(i))(f)
for i, f in enumerate(features)
]
return Concatenate(axis=1, name='anchors')(anchors)
def __build_anchors(anchor_parameters, features, frames_per_batch=1):
"""Builds anchors for the shape of the features from FPN.
Args:
anchor_parameters (AnchorParameters): Parameters that determine how
anchors are generated.
features (list): The FPN features.
frames_per_batch (int): Size of z axis in generated batches.
If equal to 1, assumes 2D data.
Returns:
tensor: The anchors for the FPN features.
The shape is:
```
(batch_size, num_anchors, 4)
```
"""
if len(features) == 1:
if frames_per_batch > 1:
anchors = TimeDistributed(
Anchors(size=anchor_parameters.sizes[0],
stride=anchor_parameters.strides[0],
ratios=anchor_parameters.ratios,
scales=anchor_parameters.scales,
name='anchors'))(features[0])
else:
anchors = Anchors(size=anchor_parameters.sizes[0],
stride=anchor_parameters.strides[0],
ratios=anchor_parameters.ratios,
scales=anchor_parameters.scales,
name='anchors')(features[0])
return anchors
else:
if frames_per_batch > 1:
anchors = [
TimeDistributed(
Anchors(size=anchor_parameters.sizes[i],
stride=anchor_parameters.strides[i],
ratios=anchor_parameters.ratios,
scales=anchor_parameters.scales,
name='anchors_{}'.format(i)))(f)
for i, f in enumerate(features)
]
else:
anchors = [
Anchors(size=anchor_parameters.sizes[i],
stride=anchor_parameters.strides[i],
ratios=anchor_parameters.ratios,
scales=anchor_parameters.scales,
name='anchors_{}'.format(i))(f)
for i, f in enumerate(features)
]
return Concatenate(axis=-2, name='anchors')(anchors)