def merge_branch_instances(instances, num_branch, nms_thrsh, topk_per_image):
"""
Merge detection results from different branches of TridentNet.
Return detection results by applying non-maximum suppression (NMS) on bounding boxes
and keep the unsuppressed boxes and other instances (e.g mask) if any.
Args:
instances (list[Instances]): A list of N * num_branch instances that store detection
results. Contain N images and each image has num_branch instances.
num_branch (int): Number of branches used for merging detection results for each image.
nms_thresh (float): The threshold to use for box non-maximum suppression. Value in [0, 1].
topk_per_image (int): The number of top scoring detections to return. Set < 0 to return
all detections.
Returns:
results: (list[Instances]): A list of N instances, one for each image in the batch,
that stores the topk most confidence detections after merging results from multiple
branches.
"""
if num_branch == 1:
return instances
batch_size = len(instances) // num_branch
results = []
for i in range(batch_size):
instance = Instances.cat(
[instances[i + batch_size * j] for j in range(num_branch)])
# Apply per-class NMS
keep = batched_nms(instance.pred_boxes.tensor, instance.scores,
instance.pred_classes, nms_thrsh)
keep = keep[:topk_per_image]
result = instance[keep]
results.append(result)
return results
def add_ground_truth_to_proposals_single_image(gt_boxes, proposals):
"""
Augment `proposals` with ground-truth boxes from `gt_boxes`.
Args:
Same as `add_ground_truth_to_proposals`, but with gt_boxes and proposals
per image.
Returns:
Same as `add_ground_truth_to_proposals`, but for only one image.
"""
device = proposals.objectness_logits.device
# Concatenating gt_boxes with proposals requires them to have the same fields
# Assign all ground-truth boxes an objectness logit corresponding to P(object) \approx 1.
gt_logit_value = math.log((1.0 - 1e-10) / (1 - (1.0 - 1e-10)))
gt_logits = gt_logit_value * torch.ones(len(gt_boxes), device=device)
gt_proposal = Instances(proposals.image_size)
gt_proposal.proposal_boxes = gt_boxes
gt_proposal.objectness_logits = gt_logits
new_proposals = Instances.cat([proposals, gt_proposal])
return new_proposals
