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rcnnBoxRegressionLayer

Box regression layer for Fast and Faster R-CNN

Description

A box regression layer refines bounding box locations by using a smooth L1 loss function. Use this layer to create a Fast or Faster R-CNN object detection network.

Creation

Description

layer = rcnnBoxRegressionLayer creates a box regression layer for a Fast or Faster R-CNN object detection network.

example

layer = rcnnBoxRegressionLayer('Name',Name) creates a box regression layer and sets the optional Name property.

Properties

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Layer name, specified as a character vector or a string scalar. For Layer array input, the trainNetwork (Deep Learning Toolbox), assembleNetwork (Deep Learning Toolbox), layerGraph (Deep Learning Toolbox), and dlnetwork (Deep Learning Toolbox) functions automatically assign names to layers with the name ''.

Data Types: char | string

This property is read-only.

Number of inputs of the layer. This layer accepts a single input only.

Data Types: double

This property is read-only.

Input names of the layer. This layer accepts a single input only.

Data Types: cell

Examples

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Create an R-CNN box regression layer with the name 'rcnn_box_reg'.

rcnnBoxRegression = rcnnBoxRegressionLayer('Name','rcnn_box_reg');

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced in R2018b