roiInputLayer

ROI input layer for Fast R-CNN

Description

An ROI input layer inputs images to a Fast R-CNN object detection network.

Creation

Syntax

layer = roiInputLayer

layer = roiInputLayer('Name',Name)

Description

layer = roiInputLayer creates an ROI input layer.

layer = roiInputLayer('Name',Name) creates an ROI input layer and sets the optional Name property.

Properties

Name — Layer name

'' (default) | character vector | string scalar

Layer name, specified as a character vector or a string scalar. To include a layer in a layer graph, you must specify a nonempty unique layer name. If you train a series network with the layer and Name is set to '', then the software automatically assigns a name to the layer at training time.

Data Types: char | string

NumOutputs — Number of outputs

1 (default)

Number of outputs of the layer. This layer has a single output only.

Data Types: double

OutputNames — Output names

{'out'} (default)

Output names of the layer. This layer has a single output only.

Data Types: cell

Examples

Connect ROI Input Layer to ROI Max Pooling Layer

Create an ROI input layer.

roiInput = roiInputLayer('Name','roi_input');

Create an ROI max pooling layer with output size [4 4].

outputSize = [4 4];
roiPool = roiMaxPooling2dLayer(outputSize,'Name','roi_pool');

Add the layers to a LayerGraph.

lgraph = layerGraph;
lgraph = addLayers(lgraph,roiInput);
lgraph = addLayers(lgraph,roiPool);

Specify that the output of the ROI input layer is the 'roi' input of the ROI max pooling layer.

lgraph = connectLayers(lgraph,'roi_input','roi_pool/roi');
plot(lgraph)