def multibox_detection_gpu(cls_prob,
loc_pred,
anchor,
clip=True,
threshold=0.01,
nms_threshold=0.5,
force_suppress=False,
variances=(0.1, 0.1, 0.2, 0.2),
nms_topk=-1):
"""Convert multibox detection predictions.
Parameters
----------
cls_prob : tvm.Tensor
Class probabilities.
loc_pred : tvm.Tensor
Location regression predictions.
anchor : tvm.Tensor
Prior anchor boxes.
clip : boolean
Whether to clip out-of-boundary boxes.
nms_threshold : float
Non-maximum suppression threshold.
force_suppress : boolean
Whether to suppress all detections regardless of class_id.
threshold : float
Threshold to be a positive prediction.
variances : tuple of float
Variances to be decoded from box regression output.
nms_topk : int
Keep maximum top k detections before nms, -1 for no limit.
Returns
-------
out : tvm.Tensor
3-D tensor with shape (batch_size, num_anchors, 6)
"""
inter_out = multibox_transform_loc(cls_prob, loc_pred, anchor, clip,
threshold, variances)
out = non_max_suppression(inter_out[0],
inter_out[1],
max_output_size=-1,
iou_threshold=nms_threshold,
force_suppress=force_suppress,
top_k=nms_topk,
return_indices=False)
return out
def multibox_detection_gpu(cls_prob, loc_pred, anchor, clip=True, threshold=0.01, nms_threshold=0.5,
force_suppress=False, variances=(0.1, 0.1, 0.2, 0.2), nms_topk=-1):
"""Convert multibox detection predictions.
Parameters
----------
cls_prob : tvm.Tensor
Class probabilities.
loc_pred : tvm.Tensor
Location regression predictions.
anchor : tvm.Tensor
Prior anchor boxes.
clip : boolean
Whether to clip out-of-boundary boxes.
nms_threshold : float
Non-maximum suppression threshold.
force_suppress : boolean
Whether to suppress all detections regardless of class_id.
threshold : float
Threshold to be a positive prediction.
variances : tuple of float
Variances to be decoded from box regression output.
nms_topk : int
Keep maximum top k detections before nms, -1 for no limit.
Returns
-------
out : tvm.Tensor
3-D tensor with shape (batch_size, num_anchors, 6)
"""
inter_out = multibox_transform_loc(cls_prob, loc_pred, anchor,
clip, threshold, variances)
out = non_max_suppression(inter_out[0], inter_out[1], max_output_size=-1,
iou_threshold=nms_threshold, force_suppress=force_suppress,
top_k=nms_topk, return_indices=False)
return out