a single ROI sampler or a list of ROI samplers for cascade
detection heads.
roi_aligner
the ROI aligner.
detection_generator
the detection generator.
mask_head
the mask head.
mask_sampler
the mask sampler.
mask_roi_aligner
the ROI alginer for mask prediction.
class_agnostic_bbox_pred
if True, perform class agnostic bounding box
prediction. Needs to be True for Cascade RCNN models.
cascade_class_ensemble
if True, ensemble classification scores over all
detection heads.
min_level
Minimum level in output feature maps.
max_level
Maximum level in output feature maps.
num_scales
A number representing intermediate scales added on each level.
For instances, num_scales=2 adds one additional intermediate anchor
scales [2^0, 2^0.5] on each level.
aspect_ratios
A list representing the aspect raito anchors added on each
level. The number indicates the ratio of width to height. For instances,
aspect_ratios=[1.0, 2.0, 0.5] adds three anchors on each scale level.
anchor_size
A number representing the scale of size of the base anchor to
the feature stride 2^level.
outer_boxes_scale
a float to scale up the bounding boxes to generate
more inclusive masks. The scale is expected to be >=1.0.
**kwargs
keyword arguments to be passed.
Attributes
checkpoint_items
Returns a dictionary of items to be additionally checkpointed.