Table Of Contents
The DetectionLayer
plugin performs bounding boxes refinement of MaskRCNN's detection head and generate the final detection output of MaskRCNN. It is used in sampleMaskRCNN.
This plugin supports the NCHW format. It takes three input tensors: delta_bbox
, score
and roi
delta_bbox
is the refinement information of roi boxes generated from ProposalLayer
. delta_bbox
tensor's shape is [N, rois, num_classes*4, 1, 1]
where N
is batch size, rois
is the total number of ROI boxes candidates per image, and num_classes*4
means 4 refinement elements ([dy, dx, dh, dw]
) for each roi box as different classes.
score
is the predicted class scores of ROI boxes generated from ProposalLayer
of shape [N, rois, num_classes, 1, 1]
. There is argmax
operation in Detectionlayer
to determine the final class of detection candidates.
roi
is the coordinates of ROI boxes candidates from ProposalLayer
of shape [N, rois, 4]
.
This plugin generates output of shape [N, keep_topk, 6]
where keep_topk
is the maximum number of detections left after NMS and '6' means 6 elements of an detection [y1, x1, y2, x2, class_label, score]
This plugin has the plugin creator class DetectionlayerPluginCreator
and the plugin class Detectionlayer
.
The following parameters were used to create Detectionlayer
instance:
Type | Parameter | Description |
---|---|---|
int | num_classes | Number of detection classes(including background ). num_classes=81 for COCO dataset |
int | keep_topk | Number of detections will be kept after NMS. |
float | score_threshold | Confidence threshold value. This plugin will drop a detection if its class confidence(score) is under "score_threshold". |
float | iou_threshold | IOU threshold value used in NMS. |
The following resources provide a deeper understanding of the Detectionlayer
plugin:
For terms and conditions for use, reproduction, and distribution, see the TensorRT Software License Agreement documentation.
June 2019 This is the first release of this README.md
file.
There are no known issues in this plugin.