Table Of Contents
Some object detection neural networks such as Faster R-CNN and SSD use region proposal networks that require anchor boxes to generate predicted bounding boxes. This plugin is included in TensorRT and used in sampleUffSSD to run SSD.
The gridAnchorPlugin generates anchor boxes (prior boxes) from the feature map in object detection models such as SSD. It generates anchor box coordinates [x_min, y_min, x_max, y_max] with variances (scaling factors) [var_0, var_1, var_2, var_3] for the downstream bounding box decoding steps. It uses a series of CUDA kernels in the gridAnchorLayer.cu file to accelerate the process in TensorRT.
If the feature maps are square, then the GridAnchor_TRT plugin should be used. If the feature maps
are rectangular but non-square, then the GridAnchorRect_TRT plugin should be used.
The GridAnchorGenerator plugin takes no inputs. However, it uses the attributes from GridAnchorParameters array typed mParam, the number of the feature maps we are generating anchor boxes for, and generates mNumLayers outputs (one per each feature map).
Each output has shape of [2, H x W x mNumPriors x 4, 1]. The first dimension has two channels.
- The first channel is for the coordinates of the proposed anchor box. The position consists of four coordinates
[x_min, y_min, x_max, y_max]. - The second channel is for the variance pre-calculated for bounding box decoding. The variance was copied from the
GridAnchorParameters.variancethat you provided to create the plugin.
The GridAnchor_TRT plugin consists of the plugin creator class GridAnchorPluginCreator and the plugin class GridAnchorGenerator.
The GridAnchorRect_TRT plugin consists of the plugin creator class GridAnchorRectPluginCreator and the plugin class GridAnchorGenerator.
GridAnchorPluginCreator and GridAnchorPluginCreator both take the following parameters as user input:
| Type | Parameter | Description |
|---|---|---|
float |
minSize |
Scale of anchors corresponding to finest resolution with respect to the height of input image. It corresponds to the s_min of the SSD paper. Default value is 0.2F. |
float |
maxSize |
Scale of anchors corresponding to coarsest resolution with respect to the height of input image. It corresponds to the s_max of the SSD paper. Default value is 0.95F. |
float* |
aspectRatios |
List of aspect ratios to place on each grid point. |
int* |
featureMapShapes |
Shapes of the feature maps. If creating a GridAnchorRect_TRT plugin, this must be a list of size numLayers * 2 where the height and width of each feature map is listed in order. If creating a GridAnchor_TRT plugin, this must be list of size numLayers where the height (or width) of each feature map is listed in order. |
float* |
variance |
Variance for adjusting the prior boxes. |
int |
numLayers |
Number of feature maps. Default value is 6. |
GridAnchorGenerator's constructor takes numLayers and an array of GridAnchorParameters typed parameters. The corresponding GridAnchorParameters are created internally by GridAnchorPluginCreator (not the plugin user's responsibility). GridAnchorParameters consists of the following parameters:
| Type | Parameter | Description |
|---|---|---|
float |
minSize |
Scale of anchors corresponding to finest resolution with respect to the height of input image. It corresponds to the s_min of the SSD paper. |
float |
maxSize |
Scale of anchors corresponding to coarsest resolution with respect to the height of input image. It corresponds to the s_max of the SSD paper. |
float* |
aspectRatios |
List of aspect ratios to place on each grid point. |
int |
numAspectRatios |
Number of elements in aspectRatios. |
int |
H |
Height of feature map to generate anchors for. |
int |
W |
Width of feature map to generate anchors for. |
float[4] |
variance |
Variance for adjusting the prior boxes. |
If we were to create a GridAnchorGenerator for a SSD network consisting of 6 layers, then the following parameters would be passed to the plugin creator class GridAnchorPluginCreator:
numLayers=6,
minSize=0.2,
maxSize=0.95,
aspectRatios=[1.0, 2.0, 0.5, 3.0, 0.33],
variance=[0.1, 0.1, 0.2, 0.2],
featureMapShapes=[19, 10, 5, 3, 2, 1]
The GridAnchorGenerator uses distinct GridAnchorParameters for each feature map to generate anchor boxes, therefore, it takes an array of GridAnchorParameters with a length of the number of feature maps (mNumLayers) to create the plugin. In the above example, we have 6 layers, the plugin needs an array of 6 GridAnchorParameters to create the plugin. In this particular example, all the GridAnchorParameters except for the first one in the array are the same according to the SSD model settings. After the plugin is created, each feature map, except for the first feature map, will have 5 + 1 anchor boxes, where 5 is the number of elements in aspectRatios and 1 is an additional default anchor box with an aspect ratio of 1.0. The first layer, as described in the SSD: Single Shot MultiBox Detector paper, has fewer number of anchor boxes. In our case, it was set to 3, in our code, int numFirstLayerARs = 3, and there will be no additional default anchor box of aspect ratio 1.0. The feature map shapes also supports rectangular inputs. The height and width of the feature maps are put in order in the list above.
Note: The above settings are slightly different to the original published SSD paper.
The following resources provide a deeper understanding of the gridAnchorPlugin plugin:
Networks:
- SSD: Single Shot MultiBox Detector
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Documentation:
For terms and conditions for use, reproduction, and distribution, see the TensorRT Software License Agreement documentation.
May 2019
This is the first release of this README.md file.
There are no known issues in this plugin.