# ProposalLayer Plugin [DEPRECATED]

**This plugin is deprecated since TensorRT 10.12 and will be removed in a future release. No alternatives are planned to be provided.**

**Table Of Contents**
- [Description](#description)
    * [Structure](#structure)
- [Parameters](#parameters)
- [Additional resources](#additional-resources)
- [License](#license)
- [Changelog](#changelog)
- [Known issues](#known-issues)

## Description

The `ProposalLayer` plugin generates the first-stage detection (ROI candidates) out of the scores, refinement info from RPN (Region Proposal Network) and pre-defined anchors. It is used in `sampleUffMaskRCNN`.

### Structure

This plugin supports the NCHW format. It takes two input tenosrs: `object_score` and `object_delta` 

`object_score` is the objectness score from RPN. `object_score`'s shape is `[N, anchors, 2, 1]` where `N` is the batch_size, `anchors` is the total number of anchors and `2` means 2 classes of objectness - foreground and background.

`object_delta` is the refinement info from RPN of shape `[N, anchors, 4, 1]`. `4` refers to the 4 elements of refinement information - `[dy, dx, dh, dw]`

This plugin generates one output tensor of shape `[N, keep_topk, 4]` where `keep_topk` is the maximum number of detections left after NMS and `4` refers to coordinates of ROI
candidates `[y1, x1, y2, x2]`

The default anchors are generated in this plugin during `initialization` method.
For ResNet101 with 1024*1024 input image, the number of anchors can be computed as:
```
Anchors in feature map P2: 256*256*3 
Anchors in feature map P3: 128*128*3
Anchors in feature map P4: 64*64*3
Anchors in feature map P5: 32*32*3
Anchors in feature map P6(maxpooling): 16*16*3  

total number of anchors: 87296*3 = 261888
```

## Parameters

This plugin has the plugin creator class `ProposalLayerPluginCreator` and the plugin class `ProposalLayer`.
  
The following parameters were used to create `ProposalLayer` instance:

| Type              | Parameter                        | Description
|-------------------|----------------------------------|--------------------------------------------------------
|`int`              |`prenms_topk`                     |The number of ROIs which will be kept before NMS. 
|`int`              |`keep_topk`                       |Number of detections will be kept after NMS.
|`float`            |`iou_threshold`                   |IOU threshold value used in NMS.
|`int[3]`           |`image_size`                      |Input image size in CHW. Only supports C=3 and defaults to [3,1024,1024].

## Limitations

The number of anchors is capped at 1024 to support embedded devices with smaller shared memory capacity.

To enable support for a device with higher memory, calls to `sortPerClass`, `PerClassNMS` and `KeepTopKGather` can be modified in `proposalRefineBatchClassNMS` ([maskRCNNKernels.cu](https://github.com/NVIDIA/TensorRT/blob/main/plugin/common/kernels/maskRCNNKernels.cu)).


## Limitations

The attribute `prenms_topk` is capped at 1024 to support embedded devices with smaller shared memory capacity.

To enable support for a device with higher memory, calls to `sortPerClass`, `PerClassNMS` and `KeepTopKGather` can be modified in `proposalRefineBatchClassNMS` ([maskRCNNKernels.cu](https://github.com/NVIDIA/TensorRT/blob/main/plugin/common/kernels/maskRCNNKernels.cu)).


## Additional resources

The following resources provide a deeper understanding of the `ProposalLayer` plugin:

- [MaskRCNN](https://github.com/matterport/Mask_RCNN)


## License

For terms and conditions for use, reproduction, and distribution, see the [TensorRT Software License Agreement](https://docs.nvidia.com/deeplearning/sdk/tensorrt-sla/index.html) 
documentation.


## Changelog

May 2025
Add deprecation note.

January 2022: The [Limitations](#limitations) section was added to this `README.md` file to document limitations of the plugin related to the maximum number of anchors it can support. 

July 2020: Add (optional) plugin parameter for specifying image size.

June 2019: First release of proposeLayerPlugin.


## Known issues

There are no known issues in this plugin.